CN113311706B - Automatic tracking method for high-frequency noise power gain of high-performance advanced observer - Google Patents

Automatic tracking method for high-frequency noise power gain of high-performance advanced observer Download PDF

Info

Publication number
CN113311706B
CN113311706B CN202110578913.1A CN202110578913A CN113311706B CN 113311706 B CN113311706 B CN 113311706B CN 202110578913 A CN202110578913 A CN 202110578913A CN 113311706 B CN113311706 B CN 113311706B
Authority
CN
China
Prior art keywords
signal
transfer function
noise
filter
inputting
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202110578913.1A
Other languages
Chinese (zh)
Other versions
CN113311706A (en
Inventor
李军
陈锦攀
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Guangdong Power Grid Co Ltd
Electric Power Research Institute of Guangdong Power Grid Co Ltd
Original Assignee
Guangdong Power Grid Co Ltd
Electric Power Research Institute of Guangdong Power Grid Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Guangdong Power Grid Co Ltd, Electric Power Research Institute of Guangdong Power Grid Co Ltd filed Critical Guangdong Power Grid Co Ltd
Priority to CN202110578913.1A priority Critical patent/CN113311706B/en
Publication of CN113311706A publication Critical patent/CN113311706A/en
Application granted granted Critical
Publication of CN113311706B publication Critical patent/CN113311706B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F01—MACHINES OR ENGINES IN GENERAL; ENGINE PLANTS IN GENERAL; STEAM ENGINES
    • F01K—STEAM ENGINE PLANTS; STEAM ACCUMULATORS; ENGINE PLANTS NOT OTHERWISE PROVIDED FOR; ENGINES USING SPECIAL WORKING FLUIDS OR CYCLES
    • F01K13/00—General layout or general methods of operation of complete plants
    • F01K13/003—Arrangements for measuring or testing

Landscapes

  • Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Computation (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Feedback Control In General (AREA)

Abstract

The invention provides an automatic tracking method and system for improving high-frequency noise power gain of a high-performance advanced observer, which utilize noise interference signals contained in signals to complete online calculation of the high-frequency noise power gain, wherein the signals generally contain the high-frequency noise interference signals in the actual process, the high-frequency noise power gain of the improved high-performance advanced observer is automatically tracked and controlled to be given to a preset number of high-frequency noise power gains, the performance of the improved high-performance advanced observer is controlled in the optimal state, and the online work influence on the improved high-performance advanced observer is small.

Description

Automatic tracking method for high-frequency noise power gain of high-performance advanced observer
Technical Field
The invention relates to the technical field of process control of thermal power generating units, in particular to an automatic tracking method and system for improving high-frequency noise power gain of a high-performance advanced observer.
Background
In the field of thermal power unit process control, advance information of process response can be acquired by advanced observation, and the method has important significance for improving process control performance. In 2019, the "advanced High Performance Learning Observer (HPLO)" published by the "automatic science and literature" in the prior publication of the chinese knowledge network in the field of industrial process control, the development and prospect of the basic control technology, which is referred to as the "literature", issued a High performance advanced observer, which made a breakthrough in advanced observation mechanisms. The high performance lead observer may be used alone. However, the look-ahead observation has the problem of noise interference amplification, mainly high frequency noise interference amplification. When the High frequency noise interference level is High, for example, the High Frequency Noise Power Gain (HFNPG) is High, serious interference may be caused to the output signal of the High performance advance observer, and even the High performance advance observer may not work normally. In engineering, the problem of online control of the high-frequency noise power gain of the high-performance advanced observer needs to be solved firstly. To a large extent, the high frequency noise power gain of the high performance lead observer represents the high frequency noise disturbance level of the high performance lead observer. In addition, the high performance advanced observer has a relatively complex structure, and engineering improvement is required, that is, an Improved high performance advancing observer (IHPLO) is required.
Disclosure of Invention
In order to solve the above problems, the present invention provides an automatic tracking method and system for improving the High frequency noise power gain of a High performance advanced observer, which utilize noise interference signals contained in signals to complete online calculation of the High frequency noise power gain, wherein the signals generally contain the High frequency noise interference signals in the actual process, and the performance of an IHPLO is controlled in an optimal state by automatically tracking and controlling the High frequency noise power gain of the improved High performance advanced observer, namely the IHPLO, to a preset number of High Frequency Noise Power Gain Given (HFNPGG), and the online work of the IHPLO is less influenced. The improved high-performance advanced observer is used for advanced observation of feedwater flow process response of a thermal power generating unit.
The first aspect of the invention provides an automatic tracking method for improving high-frequency noise power gain of a high-performance advanced observer, which comprises the following steps:
acquiring noise filtering original parameters of a noise filter, and constructing a second noise filter according to the noise filtering original parameters; acquiring an input signal of a second noise filter, and inputting the input signal of the second noise filter into the second noise filter to obtain an output signal of the second noise filter;
acquiring an input signal of an improved high-performance advanced observer, and inputting the input signal of the improved high-performance advanced observer and an output signal of a second noise filter into a high-frequency noise power gain calculation unit to obtain a second high-frequency noise power gain;
acquiring a preset high-frequency noise amplitude gain, and inputting the preset high-frequency noise amplitude gain and the second high-frequency noise power gain to a nonlinear deviation integral control unit to obtain an integral control signal;
inputting the integral control signal and the noise filtering original parameter into a multiplier to obtain an inertial lag time constant given signal;
inputting the given signal of the inertial lag time constant into a second noise filter, adjusting the second noise filter, and inputting the given signal of the inertial lag time constant and the original noise filtering parameter into a first-order inertial filter to obtain a noise filtering parameter control signal;
and inputting the input signal of the improved high-performance advanced observer and the noise filtering parameter control signal to the improved high-performance advanced observer to obtain an output signal of the improved high-performance advanced observer.
Further, the transfer function of the improved high-performance advanced observer is as follows:
Figure GDA0003613225170000031
where IHPLO(s) is a transfer function for improving the high performance lead observer, KGCGain for improving gain compensation of high performance lead observers, KIPCTo improve the gain of the internal proportional control of the high performance lead observer, NF(s) is the transfer function of the noise filter, TNFPFor the noise filter raw parameters, ESWF(s) is the transfer function of the engineered sliding window filter, nESWFOrder of an engineered sliding window filter, TIHPLOTo improve the time constant of the high performance lead observer, s is the laplacian operator.
Further, the transfer function of the second noise filter is:
Figure GDA0003613225170000032
wherein FN S(s) is the transfer function of the second noise filter, TNFP:SFor the original noise filtering parameters, FTCCV is S (t) which is a second noise filtering parameter control signal, s is a Laplace operator, and t is a time value.
Further, the inputting the preset high-frequency noise amplitude gain and the second high-frequency noise power gain to a nonlinear deviation integral control unit to obtain an integral control signal includes:
inputting the preset high-frequency noise amplitude gain to a first square root operation unit to obtain a first square root operation signal;
inputting the second high-frequency noise power gain to a second square root operation unit to obtain a second square root operation signal;
inputting the first square root operation signal and the second square root operation signal to a comparator to obtain a comparison signal;
and acquiring an output signal of automatic tracking-stopping, and inputting the comparison signal, the output signal of automatic tracking-stopping and a constant 1 into an integral controller to obtain an integral control signal.
Further, the transfer functions of the first square root operation unit and the second square root operation unit are:
Figure GDA0003613225170000041
wherein S isSRO:A(t) is the transfer function of the first square root operation unit, HFNPGC is the preset high frequency noise amplitude gain, SSRO:B(t) is the transfer function of the second square root unit, HFNPG is S (t) is the second high frequency noise power gain, and t is the time value.
Further, the transfer function of the comparator is:
Figure GDA0003613225170000042
wherein S isC(t) is the transfer function of the comparator, SSRO:A(t) is the transfer function of the first square root arithmetic unit, SSRO:B(t) is the transfer function of the second square root arithmetic unit, DZCThe dead band of the comparator, t is the time value.
Further, the transfer function of the integral controller is:
Figure GDA0003613225170000043
wherein S isIC(t) is the transfer function of the integral controller, TI is the tracking input of the integral controller, OTC is the output tracking control of the integral controller, AT/S is the output signal of automatic tracking-stop, SC(t) is the transfer function of the comparator, and t is the time value.
Further, the transfer function of the multiplier is:
NFPCV:S(t)＝SIC(t)NFPOV；
wherein, NFPCV is the transfer function of the multiplier, S (t)IC(t) is the transfer function of the integral controller, NFPOV is the noise filtering raw parameter, and t is the time value.
Further, the transfer function of the first order inertial filter is:
Figure GDA0003613225170000051
Figure GDA0003613225170000052
wherein FOIF(s) is a transfer function of a first order inertial filter, TFOIFNFPCV (t) is a time constant of a first-order inertial filter, NFPCV (t) is a noise-filtered original parameter control value, GI is a tracking input of the first-order inertial filter, NFPOV is a noise-filtered original parameter, OGC is a tracking control of the first-order inertial filter, an output signal of AT/S automatic tracking-stop, L is a time constant of the first-order inertial filter, NFPCV (t) is a noise-filtered original parameter control value, and OGC is a tracking control signal of the first-order inertial filter-1For inverse laplace transform, NFPCV is S (t) which is a second noise filtering parameter control value process, s is the laplace operator, and t is a time value.
Further, the inputting the input signal of the improved high-performance advanced observer and the output signal of the second noise filter into a high-frequency noise power gain calculation unit to obtain a second high-frequency noise power gain includes:
inputting the input signal of the improved high-performance advanced observer into a first high-pass filtering unit to obtain a first high-pass filtering signal; inputting the first high-pass filtering signal to a first square operation unit to obtain a first square operation signal; inputting the first square operation signal to a first average operation unit to obtain a first average signal;
inputting the output signal of the second noise filter to a second high-pass filtering unit to obtain a second high-pass filtering signal; inputting the second high-pass filtering signal to a second square operation unit to obtain a second square operation signal; inputting the second square operation signal to a second average value operation unit to obtain a second average value signal;
and inputting the first average value signal and the second average value signal to a division operation unit to obtain a second high-frequency noise power gain.
Further, the transfer function of the high frequency noise power gain calculation unit is:
Figure GDA0003613225170000061
wherein HFNPG (t) is a transfer function of the high frequency noise power gain calculation unit, L-1For inverse Laplace transform, MOV B(s) is the transfer function of the second average operation unit, HPF B(s) is the transfer function of the second high-pass filtering unit, OSHPF:B(t) second high-pass filtering of the output signal, OSSO:B(t) IS the second square operation output signal process, IS, B and t are the second input signals, MOV, A and s are the transfer functions of the first average operation unit, HPF, A and s are the transfer functions of the first high-pass filter unit, OSHPF:A(t) first high-pass filtering the output signal process, OSSO:A(T) IS the output signal process of the first squaring unit, IS (A), (T) IS the first input signal, TMTIs the average time, T, common to the first and second averaging unitsHPFThe time constant of the high-pass filtering common to the first high-pass filtering unit and the second high-pass filtering unit is s, which is a Laplace operator, and t is a time value.
A second aspect of the present invention provides an automatic tracking system for improving a high frequency noise power gain of a high performance advanced observer, comprising:
the second noise filter establishing and operating module is used for acquiring noise filtering original parameters of the noise filter and constructing a second noise filter according to the noise filtering original parameters; acquiring an input signal of a second noise filter, and inputting the input signal of the second noise filter into the second noise filter to obtain an output signal of the second noise filter;
the high-frequency noise power gain calculation module is used for acquiring an input signal of the improved high-performance advanced observer, and inputting the input signal of the improved high-performance advanced observer and an output signal of the second noise filter into the high-frequency noise power gain calculation unit to obtain a second high-frequency noise power gain;
the nonlinear deviation integral control module is used for acquiring a preset high-frequency noise amplitude gain and inputting the preset high-frequency noise amplitude gain and the second high-frequency noise power gain to the nonlinear deviation integral control unit to obtain an integral control signal;
the multiplier operation module is used for inputting the integral control signal and the noise filtering original parameter into a multiplier to obtain an inertia lag time constant given signal;
the first-order inertial filter operation module is used for inputting the inertial lag time constant given signal to a second noise filter, adjusting the second noise filter, and inputting the inertial lag time constant given signal and the noise filtering original parameter to the first-order inertial filter to obtain a noise filtering parameter control signal;
and the improved high-performance advanced observer operation module is used for inputting the input signal of the improved high-performance advanced observer and the noise filtering parameter control signal to the improved high-performance advanced observer to obtain an output signal of the improved high-performance advanced observer.
Further, the transfer function of the improved high-performance advanced observer is as follows:
Figure GDA0003613225170000081
where IHPLO(s) is a transfer function for improving the high performance lead observer, KGCGain for improving gain compensation of high performance lead observers, KIPCTo improve the gain of the internal proportional control of the high performance lead observer, NF(s) is the transfer function of the noise filter, TNFPFor the noise filter raw parameters, ESWF(s) is the transfer function of the engineered sliding window filter, nESWFOrder of an engineered sliding window filter, TIHPLOTo improve the time constant of the high performance lead observer, s is the laplacian operator.
Further, the transfer function of the second noise filter is:
Figure GDA0003613225170000082
where FN S(s) is the transfer function of the second noise filter, TNFP:SFor the original noise filtering parameters, FTCCV is S (t) which is a second noise filtering parameter control signal, s is a Laplace operator, and t is a time value.
Further, the nonlinear deviation integral control module is further configured to:
inputting the preset high-frequency noise amplitude gain to a first square root operation unit to obtain a first square root operation signal;
inputting the second high-frequency noise power gain to a second square root operation unit to obtain a second square root operation signal;
inputting the first square root operation signal and the second square root operation signal to a comparator to obtain a comparison signal;
and acquiring an output signal of automatic tracking-stopping, and inputting the comparison signal, the output signal of automatic tracking-stopping and a constant 1 into an integral controller to obtain an integral control signal.
Further, the transfer functions of the first square root operation unit and the second square root operation unit are:
Figure GDA0003613225170000091
wherein S isSRO:A(t) is the transfer function of the first square root operation unit, HFNPGC is the preset high frequency noise amplitude gain, SSRO:B(t) is the transfer function of the second square root unit, HFNPG is S (t) is the second high frequency noise power gain, and t is the time value.
Further, the transfer function of the comparator is:
Figure GDA0003613225170000092
wherein S isC(t) is the transfer function of the comparator, SSRO:A(t) is the transfer function of the first square root arithmetic unit, SSRO:B(t) is the transfer function of the second square root arithmetic unit, DZCThe dead band of the comparator, t is the time value.
Further, the transfer function of the integral controller is:
Figure GDA0003613225170000093
wherein S isIC(t) is the transfer function of the integral controller, TI is the tracking input of the integral controller, OTC is the output tracking control of the integral controller, AT/S is the output signal of automatic tracking-stop, SC(t) is the transfer function of the comparator, and t is the time value.
Further, the transfer function of the multiplier is:
NFPCV:S(t)＝SIC(t)NFPOV；
wherein, NFPCV is the transfer function of the multiplier, S (t)IC(t) is the transfer function of the integral controller, NFPOV is the noise filtering raw parameter, and t is the time value.
Further, the transfer function of the first order inertial filter is:
Figure GDA0003613225170000101
wherein FOIF(s) is a transfer function of a first order inertial filter, TFOIFNFPCV (t) is a time constant of a first-order inertial filter, NFPCV (t) is a noise-filtered original parameter control value, GI is a tracking input of the first-order inertial filter, NFPOV is a noise-filtered original parameter, OGC is a tracking control of the first-order inertial filter, an output signal of AT/S automatic tracking-stop, L is a time constant of the first-order inertial filter, NFPCV (t) is a noise-filtered original parameter control value, and OGC is a tracking control signal of the first-order inertial filter-1For inverse laplace transform, NFPCV is S (t) which is a second noise filtering parameter control value process, s is the laplace operator, and t is a time value.
Further, the high frequency noise power gain calculation module is further configured to:
inputting the input signal of the improved high-performance advanced observer into a first high-pass filtering unit to obtain a first high-pass filtering signal; inputting the first high-pass filtering signal to a first square operation unit to obtain a first square operation signal; inputting the first square operation signal to a first average operation unit to obtain a first average signal;
inputting the output signal of the second noise filter to a second high-pass filtering unit to obtain a second high-pass filtering signal; inputting the second high-pass filtering signal to a second square operation unit to obtain a second square operation signal; inputting the second square operation signal to a second average value operation unit to obtain a second average value signal;
and inputting the first average value signal and the second average value signal to a division operation unit to obtain a second high-frequency noise power gain.
Further, the transfer function of the high frequency noise power gain calculation unit is:
Figure GDA0003613225170000111
wherein HFNPG (t) is high frequency noise power gain meterTransfer function of the computing unit, L-1For inverse Laplace transform, MOV B(s) is the transfer function of the second average operation unit, HPF B(s) is the transfer function of the second high-pass filtering unit, OSHPF:B(t) second high-pass filtering of the output signal, OSSO:B(t) IS the second square operation output signal process, IS, B and t are the second input signals, MOV, A and s are the transfer functions of the first average operation unit, HPF, A and s are the transfer functions of the first high-pass filter unit, OSHPF:A(t) first high-pass filtering the output signal process, OSSO:A(t) IS the output signal process of the first square operation unit, IS: A (t) IS the first input signal, MOV: A(s) IS the transfer function of the first average operation unit, OSSO:A(T) IS the output signal process of the first squaring unit, IS (A), (T) IS the first input signal, TMTIs the average time, T, common to the first and second averaging unitsHPFThe time constant of the high-pass filtering common to the first high-pass filtering unit and the second high-pass filtering unit is s, which is a Laplace operator, and t is a time value.
Compared with the prior art, the embodiment of the invention has the beneficial effects that:
the invention provides an automatic tracking method and system for improving high-frequency noise power gain of a high-performance advanced observer, wherein the method comprises the following steps: acquiring noise filtering original parameters of a noise filter, and constructing a second noise filter according to the noise filtering original parameters; acquiring an input signal of a second noise filter, and inputting the input signal of the second noise filter into the second noise filter to obtain an output signal of the second noise filter; acquiring an input signal of an improved high-performance advanced observer, and inputting the input signal of the improved high-performance advanced observer and an output signal of a second noise filter into a high-frequency noise power gain calculation unit to obtain a second high-frequency noise power gain; acquiring a preset high-frequency noise amplitude gain, and inputting the preset high-frequency noise amplitude gain and the second high-frequency noise power gain to a nonlinear deviation integral control unit to obtain an integral control signal; inputting the integral control signal and the noise filtering original parameter into a multiplier to obtain an inertial lag time constant given signal; inputting the given signal of the inertial lag time constant into a second noise filter, adjusting the second noise filter, and inputting the given signal of the inertial lag time constant and the original noise filtering parameter into a first-order inertial filter to obtain a noise filtering parameter control signal; inputting the input signal of the improved high-performance advanced observer and the noise filtering parameter control signal to the improved high-performance advanced observer to obtain an output signal of the improved high-performance advanced observer; the input signal of the improved high-performance advanced observer is the feedwater flow of the thermal power generating unit. The invention provides an automatic tracking method and system for improving high-frequency noise power gain of a high-performance advanced observer, which utilize noise interference signals contained in signals to complete online calculation of the high-frequency noise power gain, the signals generally contain the high-frequency noise interference signals in the actual process, the high-frequency noise power gain of the improved high-performance advanced observer is automatically tracked and controlled to be given to a preset number of high-frequency noise power gains, the performance of the improved high-performance advanced observer is controlled in the optimal state, and the online work influence on the improved high-performance advanced observer is small.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a method for improving the automatic tracking of the high frequency noise power gain of a high performance advanced observer according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for improving the automatic tracking of the high frequency noise power gain of the high performance lead observer according to another embodiment of the present invention;
FIG. 3 is a flow chart of a method for improving the automatic tracking of the high frequency noise power gain of a high performance lead observer according to yet another embodiment of the present invention;
FIG. 4 is a schematic diagram of a method for improving the automatic tracking of the high frequency noise power gain of a high performance lead observer according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of an improved high performance advanced observer according to an embodiment of the present invention;
FIG. 6 is a signal flow diagram of a second noise filter according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a nonlinear deviation integral control and feedback process control provided by an embodiment of the present invention;
FIG. 8 is a flow chart of feedback process control quantities and auto-tracking quantities provided by one embodiment of the present invention;
FIG. 9 is a schematic diagram of a high frequency noise power gain calculation provided by an embodiment of the present invention;
FIG. 10 is a graph of simulation results of an improved high performance advanced observer input signal process provided by an embodiment of the present invention;
FIG. 11 is a diagram illustrating simulation results of a second noise filter output signal process according to an embodiment of the present invention;
fig. 12 is a diagram illustrating a simulation experiment result of a second high-frequency noise power gain process according to an embodiment of the present invention;
fig. 13 is a diagram illustrating a simulation experiment result of a process of controlling a second noise filtering parameter according to an embodiment of the present invention;
fig. 14 is a diagram illustrating a simulation experiment result of a noise filtering parameter control value according to an embodiment of the present invention;
FIG. 15 is a schematic diagram of an apparatus for improving the gain of the high frequency noise power of the high performance advanced observer in an automatic tracking system according to an embodiment of the present invention;
fig. 16 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be understood that the step numbers used herein are for convenience of description only and are not intended as limitations on the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to and includes any and all possible combinations of one or more of the associated listed items.
A first aspect.
Referring to fig. 1-3, an embodiment of the present invention provides an automatic tracking method for improving high frequency noise power gain of a high performance advanced observer, including:
s10, acquiring noise filtering original parameters of a noise filter, and constructing a second noise filter according to the noise filtering original parameters; and acquiring an input signal of a second noise filter, and inputting the input signal of the second noise filter into the second noise filter to obtain an output signal of the second noise filter.
Specifically, the transfer function of the second noise filter is:
Figure GDA0003613225170000151
wherein FN S(s) is the transfer function of the second noise filter, TNFP:SFor the original noise filtering parameters, FTCCV is S (t) which is a second noise filtering parameter control signal, s is a Laplace operator, and t is a time value.
And S20, acquiring an input signal of the improved high-performance advance observer, and inputting the input signal of the improved high-performance advance observer and an output signal of the second noise filter into a high-frequency noise power gain calculation unit to obtain a second high-frequency noise power gain.
In a specific embodiment, the step S20 includes:
s21, inputting the input signal of the improved high-performance lead observer into a first high-pass filtering unit to obtain a first high-pass filtering signal; inputting the first high-pass filtering signal to a first square operation unit to obtain a first square operation signal; and inputting the first square operation signal to a first average value operation unit to obtain a first average value signal.
S22, inputting the output signal of the second noise filter into a second high-pass filtering unit to obtain a second high-pass filtering signal; inputting the second high-pass filtering signal to a second square operation unit to obtain a second square operation signal; and inputting the second square operation signal to a second average value operation unit to obtain a second average value signal.
And S23, inputting the first average value signal and the second average value signal to a division operation unit to obtain a second high-frequency noise power gain.
Specifically, the transfer function of the high frequency noise power gain calculating unit is:
Figure GDA0003613225170000161
wherein HFNPG (t) is a transfer function of the high frequency noise power gain calculation unit, L-1For inverse Laplace transform, MOV, B(s) is the secondThe transfer function of the mean value arithmetic unit, HPF, B(s), is the transfer function of the second high-pass filtering unit, OSHPF:B(t) second high-pass filtering of the output signal, OSSO:B(t) IS the second square operation output signal process, IS, B and t are the second input signals, MOV, A and s are the transfer functions of the first average operation unit, HPF, A and s are the transfer functions of the first high-pass filter unit, OSHPF:A(t) first high-pass filtering the output signal process, OSSO:A(T) IS the output signal process of the first squaring unit, IS (A), (T) IS the first input signal, TMTThe average time, T, common to the first and second averaging unitsHPFThe time constant of the high-pass filtering common to the first high-pass filtering unit and the second high-pass filtering unit is s, which is a Laplace operator, and t is a time value.
And S30, acquiring a preset high-frequency noise amplitude gain, and inputting the preset high-frequency noise amplitude gain and the second high-frequency noise power gain to a nonlinear deviation integral control unit to obtain an integral control signal.
In a specific embodiment, the step S30 includes:
and S31, inputting the preset high-frequency noise amplitude gain to a first square root operation unit to obtain a first square root operation signal.
And S32, inputting the second high-frequency noise power gain to a second square root operation unit to obtain a second square root operation signal.
And S33, inputting the first square root operation signal and the second square root operation signal into a comparator to obtain a comparison signal.
And S34, acquiring an output signal of automatic tracking-stopping, and inputting the comparison signal, the output signal of automatic tracking-stopping and a constant 1 into an integral controller to obtain an integral control signal.
Specifically, the transfer functions of the first square root operation unit and the second square root operation unit are:
Figure GDA0003613225170000171
wherein S isSRO:A(t) is the transfer function of the first square root operation unit, HFNPGC is the preset high frequency noise amplitude gain, SSRO:B(t) is a transfer function of the second square root operation unit, HFNPG is S (t) is a second high frequency noise power gain, and t is a time value.
The transfer function of the comparator is:
Figure GDA0003613225170000172
wherein S isC(t) is the transfer function of the comparator, SSRO:A(t) is the transfer function of the first square root arithmetic unit, SSRO:B(t) is the transfer function of the second square root arithmetic unit, DZCThe dead band of the comparator, t is the time value.
The transfer function of the integral controller is:
Figure GDA0003613225170000181
wherein S isIC(t) is the transfer function of the integral controller, TI is the tracking input of the integral controller, OTC is the output tracking control of the integral controller, AT/S is the output signal of automatic tracking-stop, SC(t) is the transfer function of the comparator, and t is the time value.
And S40, inputting the integral control signal and the noise filtering original parameter into a multiplier to obtain an inertia lag time constant given signal.
Specifically, the transfer function of the multiplier is:
NFPCV:S(t)＝SIC(t)NFPOV；
wherein, NFPCV is the transfer function of the multiplier, S (t)IC(t) is the transfer function of the integral controller, NFPOV is the noise filtering raw parameter, and t is the time value.
And S50, inputting the inertial lag time constant given signal to a second noise filter, adjusting the second noise filter, and inputting the inertial lag time constant given signal and the noise filtering original parameter to a first-order inertial filter to obtain a noise filtering parameter control signal.
Specifically, the transfer function of the first order inertial filter is:
Figure GDA0003613225170000182
wherein FOIF(s) is a transfer function of a first order inertial filter, TFOIFNFPCV (t) is a time constant of a first-order inertial filter, NFPCV (t) is a noise-filtered original parameter control value, GI is a tracking input of the first-order inertial filter, NFPOV is a noise-filtered original parameter, OGC is a tracking control of the first-order inertial filter, an output signal of AT/S automatic tracking-stop, L is a time constant of the first-order inertial filter, NFPCV (t) is a noise-filtered original parameter control value, and OGC is a tracking control signal of the first-order inertial filter-1For inverse laplace transform, NFPCV is the second noise filtering parameter control value process, with s being the laplace operator and t being the time value.
And S60, inputting the input signal of the improved high-performance advance observer and the noise filtering parameter control signal to the improved high-performance advance observer to obtain an output signal of the improved high-performance advance observer.
The input signal of the improved high-performance advanced observer is the feedwater flow of the thermal power generating unit.
Specifically, the transfer function of the improved high-performance advanced observer is as follows:
Figure GDA0003613225170000191
where IHPLO(s) is a transfer function for improving the high performance lead observer, KGCGain for improving gain compensation of high performance lead observers, KIPCTo improve the gain of the internal proportional control of the high performance lead observer, NF(s) is the transfer function of the noise filter, TNFPFor noise filtering raw parameters of noise filters, ESWF(s) being of engineered sliding window filtersTransfer function, nESWFOrder of an engineered sliding window filter, TIHPLOTo improve the time constant of the high performance lead observer, s is the laplacian operator.
The invention provides an automatic tracking method for improving high-frequency noise power gain of a high-performance advanced observer, which is characterized in that the online calculation of the high-frequency noise power gain is completed by utilizing noise interference signals contained in signals, the signals generally contain the high-frequency noise interference signals in the actual process, the high-frequency noise power gain of the improved high-performance advanced observer is automatically tracked and controlled to be given to a preset number of high-frequency noise power gains, the performance of the improved high-performance advanced observer is controlled in the optimal state, and the online work influence on the improved high-performance advanced observer is small.
In a specific embodiment, a schematic diagram of an automatic tracking method for improving the high-frequency noise power gain of a high-performance advanced observer is shown in fig. 4. The method specifically comprises the following steps:
automatic tracking/stopping control
Auto tracking/Stop (AT/S), AT/S being 0 represents a Stop state, AT/S being 1 represents an Auto tracking state. The control output of [ automatic tracking/stopping ] is directly represented by AT/S and is BOOL variable.
Improved high-performance advanced observer
The improved high performance lead observer, i.e., IHPLO, architecture is shown in fig. 5.
Said IHPLO, expressed as
Figure GDA0003613225170000201
Wherein IHPLO(s) is a transfer function of the IHPLO. KGCThe Gain of the Gain Compensation (GC) of the IHPLO is in dimensionless units. KIPCThe gain of the Internal Proportional Control (IPC) of the IHPLO is expressed in dimensionless units. NF(s) is the transfer function of a Noise Filter (NF). T isNFPNoise filtering parameters (No) for said NFise filter parameters, NFP) in units of s. ESWF(s) is the transfer function of the Engineering Sliding Window Filter (ESWF). n isESWFIs the order of the ESWF in dimensionless units. T isIHPLOIs the time constant of the IHPLO in s.
The decomposition is performed on equation (1) as follows:
1) the IHPLO input signal IS connected to the reduced number input end of the Subtraction Operation (SO), and IS IS usedIHPLO(t) expressing the IHPLO input signal process in dimensionless units.
2) And connecting the subtraction output end to the input end of the ESWF.
3) And connecting the output end of the ESWF to the input end of the IPC.
4) And connecting the output end of the IPC to the input end of the decrement for subtracting the SO.
5) And connecting the SO-reduced output end to the input end of the GC.
6) And connecting the output end of the GC to the input end of the NF.
7) And obtaining the IHPLO output signal at the output end of the NF. By OSIHPLO(t) expressing the IHPLO output signal process in dimensionless units.
Noise Filter Parameter Selection (NFPS), expressed as NFPS
Figure GDA0003613225170000211
Wherein nfpso (t) selects an output process for the noise filtering parameter, with the unit of s. NFPOV is the Noise Filter Parameters Original Value (NFPOV) in s. NFPCV (t) is a Noise Filter Parameters Control Value (NFPCV) process in units of s. AT/S is [ auto track/stop ]]And the control output is BOOL variable. T is a unit ofNFPThe unit is s for the noise filtering parameter.
The decomposition is performed on equation (2) as follows:
1) and connecting the NFPOV to the NFPOV input end of the NFPS.
2) (t) accessing the NFPCV to an NFPCV input of the NFPS.
3) And connecting the AT/S to the NFPS input end of the NFPS.
4) And obtaining the noise filtering parameter selection output process, namely, nfpso (t), at an SO output end (SO) of the NFPS.
5) Setting the T with the NFPSO (T)NFPI.e. TNFPNfpso (t). If the AT/S is 0, the TNFPNFPOV. If the AT/S is 1, the TNFP＝NFPCV(t)。
A second noise filter having the same structure as the noise filter
The structure of the Noise filter is obtained, and a second Noise filter (NF: S) having the same structure as the Noise filter is constructed, as shown in fig. 6.
Said second noise filter, expressed as
Figure GDA0003613225170000221
Wherein NF is S(s) is a transfer function of the second noise filter. T isNFPThe Noise filter Noise filtering parameter (NFP: S) is expressed in S. NFPCV S (t) is a second Noise filter parameter control value of second, NFPCV S process, in units of S.
The decomposition is performed on equation (3) as follows:
1) the noise filter input signal process is switched in to the input of the second noise filter.
2) Obtaining a second noise filter output signal at the output of said second noise filter, using the OSNF:S(t) expressing said second noise filter output signal process in dimensionless units.
3) NFPCV: S transfusion that interfaces the NFPCV: S (t) to the NF: SAnd (4) entering the terminal. Setting the T with the NFPSO S (T)NFP:SI.e. TNFP:S＝NFPSO:S(t)。
Non-linear deviation integral control and feedback process control
A schematic diagram of Nonlinear Deviation Integration Control (NDIC) and feedback process control is shown in fig. 7.
The Square root operation A (SRO: A) and the Square root operation B (SRO: B) are expressed as
Figure GDA0003613225170000231
Wherein S isSRO:AAnd (t) is a square root operation A signal process with dimensionless units. HFNPGG is given by the power gain of high-frequency noise of a preset number, and the unit is dimensionless; sSRO:BAnd (t) is a square root operation B signal process, and the unit is dimensionless. HFNPG (t) is a second High frequency noise power gain (HFNPG: S) process, in dimensionless units.
The Comparator (C) is expressed as
Figure GDA0003613225170000232
Wherein S isCAnd (t) is a comparative signal process, and the unit is dimensionless. SSRO:AAnd (t) is the square root operation A signal process, and the unit is dimensionless. SSRO:BAnd (t) is the process of square root operation B signal, and the unit is dimensionless. DZCIs the comparator Dead Zone (DZ) in dimensionless units.
Integral control is expressed as
Figure GDA0003613225170000233
Where IC(s) is the transfer function of Integral Control (IC). T isICIs the integration time constant of the integration control and has the unit of s.
Tracking control of integral control, expressed as
Figure GDA0003613225170000241
Wherein S isICAnd (t) is the integral control signal process, and the unit is dimensionless. TI is the Tracking Input (TI) of the integral control, and has a dimensionless unit. The OTC is an Output Tracking Control (OTC) of the integral control, and is a BOOL variable. AT/S is [ auto track/stop ]]And the control output is BOOL variable. SCAnd (t) is the comparison signal process, and the unit is dimensionless.
The integral control tracking control steps are as follows:
1) a constant 1 is connected to the TI input of the integration control.
2) And connecting the AT/S to the OTC input end of the integral control.
3) If the AT/S is equal to 0, then the OTC is equal to AT/S is equal to 0, then the integral control signal is SIC(t) tracking constant 1, i.e. SIC(t)＝TI＝1。
4) If the AT/S is equal to 1, then the OTC is equal to AT/S is equal to 1, then the integral control signal is SIC(t) is the process for the comparison signal, namely SCNegative integral of (t). Said integral control signal being SIC(t) has an initial memory effect, and after OTC is AT/S is 1, S isIC(t) will vary on a constant 1 basis.
In the comparator dead zone DZ C0, the feedback control system is expressed as
Figure GDA0003613225170000242
Wherein, HFNPGC: S (S) is a transfer function of a second High frequency noise power gain control (HFNPGC: S). NDIC(s) is the integral of the non-linear deviationThe transfer function of the control. HFNPGCP: S (S) is a transfer function of a second High frequency noise power gain control process (HFNPGCP: S), approximating a Nonlinear Proportional System (NPS). BPFGIHPLO:NF:SAnd outputting the Band Pass Filter Gain (BPFG) of the second noise filter relative to the input of the improved high-performance advanced observer, wherein the unit is dimensionless. BPFBIHPLO:NF:SAnd outputting a Band Pass Filter Bandwidth (BPFB) for the second noise filter, wherein the BPFB has a unit of rad/s relative to the input of the improved high-performance advanced observer. INBIHPLOThe Input noise bandwidth (INFB) of the high-performance lead observer is improved, and the unit is rad/s.
Specifically, the following description is provided: ndic(s) is only one symbol used to express the non-linear deviation integral control transfer function. In practice, the transfer function of the nonlinear deviation integral control is difficult to accurately express.
Feedback process control quantity and automatic tracking quantity
The flow of the feedback process control quantity and the automatic tracking quantity is shown in fig. 8.
The feedback process control quantity is expressed as
NFPCV:S(t)＝SIC(t)NFPOV(9)
And NFPCV is the process of controlling the value of the second noise filtering parameter, wherein S (t) is the process of controlling the value of the second noise filtering parameter, and the unit is s. SICAnd (t) is the integral control signal process, and the unit is dimensionless. NFPOV is the original value of the noise filter parameter in s. NFPCV, S (t), is the feedback process control quantity and this description is not essential.
The automatic tracking quantity is expressed as
Figure GDA0003613225170000251
Wherein FOIF(s) is a transfer function of a First Order Inertial Filter (FOIF). T isFOIFIs the time constant of the first-order inertial filterThe bit is s; nfpcv (t) is the noise filtering parameter control value in s. TI is the tracking input of the first order inertial filter in dimensionless units. NFPOV is the original value of the noise filter parameter in s. The OTC is the tracking control of the first order inertial filter and is a BOOL variable. AT/S is [ auto track/stop ]]And the control output is BOOL variable. L is-1Is the inverse laplace transform. And NFPCV is the process of controlling the value of the second noise filtering parameter, and the process is S (t). Nfpcv (t) is the auto-trace quantity, and this description is not essential.
The first-order inertial filter tracking control steps are as follows:
1) the original value of the noise filtering parameter, namely NFPOV, is connected to the TI input of the first-order inertial filter, namely TI ═ NFPOV.
2) And connecting the AT/S to an OTC input end of the first-order inertia filter, namely OTC (AT/S).
3) If AT/S is 0, then OTC is 0, then the first order inertial filter output signal process, NFPCV, S (t) tracks the NFPOV, NFPCV, S (t) TI NFPOV.
4) If AT/S is 1, OTC is 1, then the first order inertial filter output signal process, NFPCV (t), is a first order inertial filter tracking of the second noise filter parameter control value process, NFPCV: S (t); the NFPCV (t) has an initial memory function, and after OTC (AT/S) 1, NFPCV (t) will change based on the NFPOV.
High frequency noise power gain calculation
Fig. 9 is a schematic diagram of the measurement of the power gain of the high-frequency noise.
And obtaining a calculation result of the high-frequency noise power gain of the Input signal B (Input signal of B, IS: B) relative to the Input signal A (Input signal of A, IS: A) through the high-frequency noise power gain calculation, and outputting the high-frequency noise power gain calculation result at the OS output end of the high-frequency noise power gain calculation.
The high frequency noise power gain calculation is expressed as:
Figure GDA0003613225170000271
wherein, hfnpg (t) is the high frequency noise power gain calculation process, and the unit is dimensionless; l is a radical of an alcohol-1Is an inverse laplace transform. MOV B(s) is the transfer function of the Mean value operation B (MVO B). HPF B(s) is the transfer function of the High pass filter B (HPF B). OSHPF:BAnd (t) is the process of outputting signals by the high-pass filtering B, and the unit is dimensionless. OSSO:BAnd (t) is the process of Square operation of B (SO: B) output signal, and the unit is dimensionless. The unit of IS (B), (t) IS the process of an input signal B and IS dimensionless; MOV A(s) is the transfer function of Mean value operation A (MVO: A). HPF: A(s) is the transfer function of the High pass filter A (HPF: A). OSHPF:AAnd (t) is the process of outputting the signal by the high-pass filtering A, and the unit is dimensionless. OSSO:A(t) is the process of Square operation A (SO: A) output signal, and the unit is dimensionless. A (t) IS the process of the input signal A, and the unit IS dimensionless; MOV A(s) is the transfer function of Mean value operation A (MVO: A). OSSO:A(t) is the process of Square operation A (SO: A) output signal, and the unit is dimensionless. A (t) IS the process of the input signal A, and the unit IS dimensionless; t isMTThe Mean Time (MT) length of MOV: B(s) and MOV: A(s) in s. T isHPFIs the high-pass filtering time constant common to HPF: B(s) and HPF: A(s) in units of s.
Equation (17) is decomposed as follows:
1) the input signal B is connected to the input of the high-pass filter B.
2) And connecting the output end of the high-pass filtering B to the input end of the square operation B.
3) And connecting the output end of the square operation B to the input end of the average operation B.
4) The input signal a is coupled to an input of the high-pass filter a.
5) And connecting the output end of the high-pass filter A to the input end of the square operation A.
6) And connecting the output end of the square operation A to the input end of the average operation A.
7) And connecting the output end of the average value operation B to the dividend input end of Division Operation (DO). And connecting the output end of the average value operation A to the divisor input end of the Division Operation (DO). And obtaining the high-frequency noise power gain calculation process at the output end of the division operation. The high frequency noise power gain calculation process is expressed in units of dimensionless terms by hfnpg (t).
8) Outputting the high frequency noise power gain calculation process, HFNPG (t), at the OS output of the high frequency noise power gain calculation.
Automatic tracking control for improving high-frequency noise power gain of high-performance advanced observer
Using HFNPGIHPLO(t) expressing the high-frequency noise power gain process of the improved high-performance advanced observer, wherein the unit is dimensionless.
Build feedback Process control step
1) Inputting the improved high-performance advanced observer into the signal process, namely ISIHPLO(t) IS connected to the IS: a input of said high frequency noise power gain calculation. The second noise filter output signal OSNF:S(t) IS connected to the IS: B input of said high frequency noise power gain calculation. (s (t)) obtaining the second high frequency noise power gain process at the output of the high frequency noise power gain calculation.
2) The given high-frequency noise power gain of the preset number, namely HFNPGG is connected to the input end of the square root operation A, and the process of obtaining a square root operation A signal at the output end of the square root operation A, namely SSRO:A(t)。
3) S (t) is connected to the input end of the square root operation B, and the process of obtaining the square root operation B signal, namely S, is obtained at the output end of the square root operation BSRO:B(t)。
4) The square root operation a signal process is switched in to the positive input of the comparator. And connecting the square root operation B signal process to the negative input end of the comparator. Obtaining a comparison signal process at the output of the comparator, i.e. SC(t)。
5) The comparison signal process is connected to the input of the integral control. Obtaining an integral control signal, S, at an output of the integral controlIC(t)。
6) Integrating the control signal process, i.e. SIC(t) is coupled to a first input of said multiplication and said noise filter parameter original value, NFPOV, is coupled to a second input of said multiplication. And obtaining the second noise filtering parameter control value at the output end of the multiplier, namely NFPCV: S (t).
7) The second noise filtering parameter control value process, NFPCV: S (T), is coupled to the NFPCV: S input of the second noise filter for the given second noise filtering parameter, TpNFP:SI.e. TNFP:S＝NFPCV:S(t)。
8) A second noise filtering parameter control value process, NFPCV: S (t), is coupled to an input of the first order inertial filter. And obtaining the noise filtering parameter control value process namely NFPCV (t) at the output end of the first-order inertia filter.
9) Accessing the noise filtering parameter control value process (NFPCV) (T) to the NFPCV input of the improved high-performance advanced observer for setting the noise filtering parameter (T)NFPMaking the improved high performance advanced observer high frequency noise power gain process HFNPGIHPLO(t) automatically tracking the second high frequency noise power gain process HFNPG: S (t).
Automatic tracking/stop state
1) Setting the stop state, namely AT/S is equal to 0, the feedback process control stops working, and the integral control signal process is SIC(t) 1, and the second noise filtering parameter control value process, i.e., NFPCV, S (t) SIC(t) NFPOV ═ NFPOV, and the noise filtering parameter control value process, namely, nfpcv (t) ═ NFPOV. The second noise filter parameterNumber is TNFP:SNFPOV. The noise filtering parameter is TNFP＝NFPOV。
2) Setting the automatic tracking state, i.e. AT/S is 1, the feedback process control starts to work, and the second noise filtering parameter control value process, i.e. NFPCV, S (t) is SIC(t) NFPOV, the noise filter parameter control value process, NFPCV (t), being the first order inertial filter tracking output to the NFPCV: S (t). The second noise filtering parameter is TNFP:SNFPCV: s (t). The noise filtering parameter is TNFP＝NFPCV(t)。
Feedback process control
In the automatic tracking state, namely AT/S is equal to 1, the feedback process controls the second noise filtering parameter T by taking the second noise filtering parameter control value process, namely NFPCV S (T), as a control quantityNFP:SBy means of, i.e. TNFP:S(ii) controlling the second high frequency noise power gain process, HFNPG, (t), to the predetermined number of high frequency noise power gain setpoints, HFNPGG; obtaining the noise filtering parameter control value process (NFPCV) (t) by performing first-order inertial filtering tracking on the second noise filtering parameter control value process (NFPCV: S (t)), and enabling the improved high-performance advanced observer high-frequency noise power gain process (HFNPG)IHPLO(t) automatically tracking the second noise filter high frequency noise power gain process HFNPG: S (t). After the feedback process control enters a steady state, finally, the improved high-performance advanced observer high-frequency noise power gain process (HFNPG)IHPLO(t) automatically tracking the preset number of high frequency noise power gain settings, HFNPGG.
Due to the instability of noise interference signals, after the feedback process control enters a steady state, the second noise filtering parameter control value process, namely NFPCV: S (t), fluctuates around the Average Value (AV), and the Average value of the NFPCV: S (t) is expressed by the NFPCV: S: AV and is expressed by the unit of S. Because the first-order inertial filtering tracking is carried out on the second noise filtering parameter control value process, namely NFPCV (S) (t), to obtain the filtering parameter control value process, namely NFPCV (t), relative to NFPCV (S) (t), NFPCV (t) is smoother
Feedback process control
In the starting state, the second noise filtering parameter T is controlled by the feedback process control by taking the second noise filtering parameter control value process (NFPCV: S (T)) as a control quantity to control the second noise filtering parameter TNFP:SBy means of, i.e. TNFP:SAnd controlling the second high-frequency noise power gain process, namely HFNPG(s) (t), to be HFNPGG, namely the high-frequency noise power gain given value of the preset number.
In the start-up state, the feedback process control is debugged if a debug state is selected, i.e. AT/S is 0.
In the starting state, if an automatic tracking state (AT/S is 1), a second noise filtering parameter control value process (NFPCV: S (t)) is used for carrying out first-order inertial filtering tracking to obtain a noise filtering parameter control value process (NFPCV (t)), so that the improved high-performance advanced observer high-frequency noise power gain process (HFNPG) is usedIHPLO(t) tracking the second high frequency noise power gain process, HFNPG: S (t). After the feedback process control enters a steady state, finally, the improved high-performance advanced observer high-frequency noise power gain process (HFNPG)IHPLO(t) tracking the predetermined number of high frequency noise power gain settings, HFNPGG.
Due to the instability of noise interference signals, after the feedback process control enters a steady state, the second noise filtering parameter control value process, namely NFPCV: S (t), fluctuates around the Average Value (AV), and the Average value of the NFPCV: S (t) is expressed by the NFPCV: S: AV and is expressed by the unit of S. Because the first-order inertial filtering tracking is carried out on the second noise filtering parameter control value process, namely NFPCV: S (t), to obtain the filtering parameter control value process, namely NFPCV (t), the process is smoother compared with the process of NFPCV: S (t), and NFPCV (t) is smoother.
In a specific embodiment, the parameters of the improved high-performance advanced observer are as follows: t isHPLO＝150s，KFGC＝10，KGC＝11，nESWFNFPOV 15s, 8. Setting T of the high frequency noise power gain calculationMTSetting K of said high-pass filtering to 600sHPF30 s; setting DZ of the comparatorC0.25. Setting T of the integral controlIC1150 s; setting T of the first order inertial filteringFOIF500 s; and setting the given high-frequency noise power gain of the preset number to be 6.5, namely HFNPGG.
The IHPLO input signal has a slope change at the process time t of 3000 s-4000 s, the slope rising rate is 1/1000s, the slope time length is 1000s, and the influence of the IHPLO input signal process change on the second high-frequency noise power gain process (HFNPG: S (t)), the second noise filter parameter control value process (NFPCV) (t) and the noise filter parameter control value process (NFPCV) (t) is examined. And simulating a noise interference signal in the input signal of the improved high-performance advanced observer by using a pseudo-random signal, wherein the output range of the pseudo-random signal is +/-0.01, and the unit is dimensionless.
AT a digital discrete measurement interval of 1S, the automatic tracking state is set starting from the process time t equal to 0S, i.e. AT/S equal to 1. The result of the simulation experiment of the input signal of the improved high-performance advanced observer is shown in fig. 10. The result of the simulation experiment of the output signal of the second noise filter is shown in fig. 11. The result of the simulation experiment of the second high-frequency noise power gain is obtained and is shown in fig. 12. The result of the simulation experiment of the second noise filtering parameter control value is obtained and is shown in fig. 13. The simulation experiment result of the noise filtering parameter control value is obtained and is shown in fig. 14.
As shown in fig. 12, in the given process time t, which is in the range of 0 to 8000s, starting from t, which is 0s, s (t) gradually converges to the predetermined number of high frequency noise power gains, which is HFNPGG, which is 2.5, and finally fluctuates around 2.5; as shown in fig. 13, starting from t ═ 0S, the second noise filtering parameter control value process, NFPCV: S (t), gradually decreases from 15S, and finally fluctuates around the average value of NFPCV: S (t), NFPCV: S: AV. Wherein NFPCV: S (t) has an average value at t of 700S to 8000S, i.e. NFPCV: S: AV is equal to' 6.4S. FIG. 14 shows that the NFPCV (t) is more even than the NFPCV: S (t).
As can be seen from fig. 12, 13 and 14, the slope change of the improved high-performance advanced observer input signal at the process time t of 3000s to 4000s has no significant influence on the second high-frequency noise power gain process, the second noise filter parameter control value process and the noise filter parameter control value process.
According to the technical scheme, the embodiment of the invention has the following advantages:
the embodiment of the invention provides an automatic tracking method and device for improving the high-frequency noise power gain of a high-performance advanced observer, which utilize noise interference signals contained in signals to complete the on-line calculation of the second high-frequency noise power gain, and the signals generally contain the high-frequency noise interference signals in the actual process. Controlling the second noise filtering parameter T by using the second noise filtering parameter control value process NFPCV S (T) as a control quantity through the feedback process controlNFP:SBy means of, i.e. TNFP:S(vi) s (t), controlling said second high frequency noise power gain process, HFNPG, s (t) to said predetermined number of high frequency noise power gain settings, HFNPGG; in an automatic tracking mode, a first-order inertial filtering tracking is carried out on the second noise filtering parameter control value process NFPCV: S (t) to obtain a noise filtering parameter control value process NFPCV (t), and a high-frequency noise power gain process HFNPG (high frequency noise plus Power gain) of the improved high-performance advanced observer is enabled to be obtainedIHPLO(t) tracking the second frequency high frequency noise power gain process HFNPG: S (t). After the feedback process control enters a steady state, finally, the improved high-performance advanced observer high-frequency noise power gain process (HFNPG)IHPLO(t) tracking to the preset number of high frequency noise power gain settings, HFNPGG; the obvious characteristics are that: and tracking the high-frequency noise power gain of the improved high-performance advance observer to the preset number of given high-frequency noise power gains through automatic tracking control, and controlling the performance of the improved high-performance advance observer in an optimal state.
A second aspect.
Referring to fig. 15, an embodiment of the present invention provides an automatic tracking system for improving the high frequency noise power gain of a high performance advanced observer, including:
the second noise filter establishing and calculating module 10 is configured to obtain a noise filtering original parameter of a noise filter, and construct a second noise filter according to the noise filtering original parameter; and acquiring an input signal of a second noise filter, and inputting the input signal of the second noise filter into the second noise filter to obtain an output signal of the second noise filter.
Specifically, the transfer function of the second noise filter is:
Figure GDA0003613225170000341
wherein FN S(s) is the transfer function of the second noise filter, TNFP:SFor the original noise filtering parameters, FTCCV is S (t) which is a second noise filtering parameter control signal, s is a Laplace operator, and t is a time value.
And a high-frequency noise power gain calculation module 20, configured to obtain an input signal of the improved high-performance advanced observer, and input the input signal of the improved high-performance advanced observer and an output signal of the second noise filter to a high-frequency noise power gain calculation unit, so as to obtain a second high-frequency noise power gain.
In a specific embodiment, the high frequency noise power gain calculation module 20 is further configured to:
inputting the input signal of the improved high-performance advanced observer into a first high-pass filtering unit to obtain a first high-pass filtering signal; inputting the first high-pass filtering signal to a first square operation unit to obtain a first square operation signal; inputting the first square operation signal to a first average operation unit to obtain a first average signal;
inputting the output signal of the second noise filter to a second high-pass filtering unit to obtain a second high-pass filtering signal; inputting the second high-pass filtering signal to a second square operation unit to obtain a second square operation signal; inputting the second square operation signal to a second average value operation unit to obtain a second average value signal;
and inputting the first average value signal and the second average value signal to a division operation unit to obtain a second high-frequency noise power gain.
Specifically, the transfer function of the high-frequency noise power gain calculation unit is:
Figure GDA0003613225170000351
wherein HFNPG (t) is a transfer function of the high frequency noise power gain calculation unit, L-1For inverse Laplace transform, MOV B(s) is the transfer function of the second average operation unit, HPF B(s) is the transfer function of the second high-pass filtering unit, OSHPF:B(t) second high-pass filtering of the output signal, OSSO:B(t) IS the second square operation output signal process, IS, B and t are the second input signals, MOV, A and s are the transfer functions of the first average operation unit, HPF, A and s are the transfer functions of the first high-pass filter unit, OSHPF:A(t) first high-pass filtering the output signal process, OSSO:A(T) IS the output signal process of the first squaring unit, IS (A), (T) IS the first input signal, TMTIs the average time, T, common to the first and second averaging unitsHPFThe time constant of the high-pass filtering common to the first high-pass filtering unit and the second high-pass filtering unit is s, which is a Laplace operator, and t is a time value.
The nonlinear deviation integral control module 30 is configured to obtain a preset high-frequency noise amplitude gain, and input the preset high-frequency noise amplitude gain and the second high-frequency noise power gain to a nonlinear deviation integral control unit to obtain an integral control signal.
In a specific embodiment, the nonlinear deviation integral control module 30 is further configured to:
inputting the preset high-frequency noise amplitude gain to a first square root operation unit to obtain a first square root operation signal;
inputting the second high-frequency noise power gain to a second square root operation unit to obtain a second square root operation signal;
inputting the first square root operation signal and the second square root operation signal to a comparator to obtain a comparison signal;
and acquiring an output signal of automatic tracking-stopping, and inputting the comparison signal, the output signal of automatic tracking-stopping and a constant 1 into an integral controller to obtain an integral control signal.
Specifically, the transfer functions of the first square root operation unit and the second square root operation unit are:
Figure GDA0003613225170000361
wherein S isSRO:A(t) is the transfer function of the first square root operation unit, HFNPGC is the preset high frequency noise amplitude gain, SSRO:B(t) is the transfer function of the second square root unit, HFNPG is S (t) is the second high frequency noise power gain, and t is the time value.
The transfer function of the comparator is:
Figure GDA0003613225170000371
wherein S isC(t) is the transfer function of the comparator, SSRO:A(t) is the transfer function of the first square root arithmetic unit, SSRO:B(t) is the transfer function of the second square root arithmetic unit, DZCThe dead band of the comparator, t is the time value.
The transfer function of the integral controller is:
Figure GDA0003613225170000372
wherein S isIC(t) is the transfer function of the integral controller, TI is the tracking input of the integral controller, OTC is the output tracking control of the integral controller, AT/S is the output signal of automatic tracking-stop，SC(t) is the transfer function of the comparator, and t is the time value.
And the multiplier operation module 40 is used for inputting the integral control signal and the noise filtering original parameter into a multiplier to obtain an inertial lag time constant given signal.
Specifically, the transfer function of the multiplier is:
NFPCV:S(t)＝SIC(t)NFPOV；
wherein, NFPCV is the transfer function of the multiplier, S (t)IC(t) is the transfer function of the integral controller, NFPOV is the noise filtering raw parameter, and t is the time value.
The first-order inertial filter operation module 50 is configured to input the inertial lag time constant given signal to a second noise filter, adjust the second noise filter, and input the inertial lag time constant given signal and the noise filtering original parameter to the first-order inertial filter to obtain a noise filtering parameter control signal.
Specifically, the transfer function of the first order inertial filter is:
Figure GDA0003613225170000381
wherein FOIF(s) is a transfer function of a first order inertial filter, TFOIFNFPCV (t) is a time constant of a first-order inertial filter, NFPCV (t) is a noise-filtered original parameter control value, GI is a tracking input of the first-order inertial filter, NFPOV is a noise-filtered original parameter, OGC is a tracking control of the first-order inertial filter, an output signal of AT/S automatic tracking-stop, L is a time constant of the first-order inertial filter, NFPCV (t) is a noise-filtered original parameter control value, and OGC is a tracking control signal of the first-order inertial filter-1For inverse laplace transform, NFPCV is S (t) which is a second noise filtering parameter control value process, s is the laplace operator, and t is a time value.
And the improved high-performance advanced observer operating module 60 is configured to input the input signal of the improved high-performance advanced observer and the noise filtering parameter control signal to the improved high-performance advanced observer, so as to obtain an output signal of the improved high-performance advanced observer.
The input signal of the improved high-performance advanced observer is the feedwater flow of the thermal power generating unit.
Specifically, the transfer function of the improved high-performance advanced observer is as follows:
Figure GDA0003613225170000382
where IHPLO(s) is a transfer function for improving the high performance lead observer, KGCGain for improving gain compensation of high performance lead observers, KIPCTo improve the gain of the internal proportional control of the high performance lead observer, NF(s) is the transfer function of the noise filter, TNFPFor the noise filter raw parameters, ESWF(s) is the transfer function of the engineered sliding window filter, nESWFOrder of an engineered sliding window filter, TIHPLOTo improve the time constant of the high performance lead observer, s is the laplacian operator.
The invention provides an automatic tracking system for improving high-frequency noise power gain of a high-performance advanced observer, which utilizes noise interference signals contained in signals to complete online calculation of the high-frequency noise power gain, wherein the signals generally contain the high-frequency noise interference signals in the actual process, and the performance of the improved high-performance advanced observer is controlled in the optimal state by automatically tracking and controlling the high-frequency noise power gain of the improved high-performance advanced observer to a preset number of given high-frequency noise power gains, and the online work influence on the improved high-performance advanced observer is small.
In a third aspect.
The present invention provides an electronic device, including:
a processor, a memory, and a bus;
the bus is used for connecting the processor and the memory;
the memory is used for storing operation instructions;
the processor is configured to invoke the operation instruction, and the executable instruction causes the processor to perform the operation corresponding to the automatic tracking method for improving the high-frequency noise power gain of the high-performance advanced observer, as shown in the first aspect of the present application.
In an alternative embodiment, there is provided an electronic device, as shown in fig. 16, an electronic device 5000 shown in fig. 16 including: a processor 5001 and a memory 5003. The processor 5001 and the memory 5003 are coupled, such as via a bus 5002. Optionally, the electronic device 5000 may also include a transceiver 5004. It should be noted that the transceiver 5004 is not limited to one in practical application, and the structure of the electronic device 5000 is not limited to the embodiment of the present application.
The processor 5001 may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 5001 may also be a combination of computing functions, e.g., comprising one or more microprocessors, a combination of a DSP and a microprocessor, or the like.
Bus 5002 can include a path that conveys information between the aforementioned components. The bus 5002 may be a PCI bus or EISA bus, etc. The bus 5002 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 16, but this is not intended to represent only one bus or type of bus.
The memory 5003 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 5003 is used for storing application program codes for executing the present solution, and the execution is controlled by the processor 5001. The processor 5001 is configured to execute application program code stored in the memory 5003 to implement the teachings of any of the foregoing method embodiments.
Wherein, the electronic device includes but is not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like.
A fourth aspect.
The present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements an automatic tracking method for improving high frequency noise power gain of a high performance advanced observer as set forth in the first aspect of the present application.
Yet another embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, which, when run on a computer, enables the computer to perform the corresponding content of the foregoing method embodiments.

Claims (2)

1. An automatic tracking method for improving high-frequency noise power gain of a high-performance advanced observer is applied to process control of a thermal power generating unit, and comprises the following steps:
acquiring noise filtering original parameters of a noise filter, and constructing a second noise filter according to the noise filtering original parameters; acquiring an input signal of a second noise filter, and inputting the input signal of the second noise filter into the second noise filter to obtain an output signal of the second noise filter;
the transfer function of the second noise filter is:
Figure FDA0003613225160000011
wherein FN (S) (S) is a transfer function of a second noise filter, TNFP (S) is a noise filtering original parameter, FTCCV (S) (t) is a second noise filtering parameter control signal, S is a Laplace operator, and t is a time value;
acquiring an input signal of an improved high-performance advanced observer, and inputting the input signal of the improved high-performance advanced observer and an output signal of a second noise filter into a high-frequency noise power gain calculation unit to obtain a second high-frequency noise power gain; the method comprises the following steps:
inputting the input signal of the improved high-performance advanced observer to a first high-pass filtering unit to obtain a first high-pass filtering signal; inputting the first high-pass filtering signal to a first square operation unit to obtain a first square operation signal; inputting the first square operation signal to a first average operation unit to obtain a first average signal;
inputting the output signal of the second noise filter to a second high-pass filtering unit to obtain a second high-pass filtering signal; inputting the second high-pass filtering signal to a second square operation unit to obtain a second square operation signal; inputting the second square operation signal to a second average value operation unit to obtain a second average value signal;
inputting the first average value signal and the second average value signal to a division operation unit to obtain a second high-frequency noise power gain;
the transfer function of the improved high-performance advanced observer is as follows:
Figure FDA0003613225160000021
where IHPLO(s) is a transfer function for improving the high performance lead observer, KGCGain, K, for improving the gain compensation of a high performance lead observerIPCTo improve the gain of the internal proportional control of the high performance lead observer, NF(s) is the transfer function of the noise filter, TNFPFor the noise filter raw parameters, ESWF(s) is the transfer function of the engineered sliding window filter, nESWFFor engineering purposesOrder of sliding window filter, TIHPLOIn order to improve the time constant of the high-performance advanced observer, s is a Laplace operator;
the transfer function of the high-frequency noise power gain calculation unit is as follows:
Figure FDA0003613225160000022
wherein HFNPG (t) is a transfer function of the high frequency noise power gain calculation unit, L-1For inverse Laplace transform, MOV B(s) is the transfer function of the second average operation unit, HPF B(s) is the transfer function of the second high-pass filtering unit, OSHPF:B(t) second high-pass filtering of the output signal, OSSO:B(t) IS the second square operation output signal process, IS, B, and t are the second input signals, MOV, A, and s are the transfer functions of the first average operation unit, HPF, A, and s are the transfer functions of the first high-pass filter unit, OSHPF:A(t) IS the first high-pass filtered output signal process, IS (A), (t) IS the first input signal, OSSO:A(T) a process of outputting a signal by the first squaring unit, TMTIs the average time, T, common to the first and second averaging unitsHPFThe time constant is a common high-pass filtering time constant of the first high-pass filtering unit and the second high-pass filtering unit, s is a Laplace operator, and t is a time value;
acquiring a preset high-frequency noise amplitude gain, and inputting the preset high-frequency noise amplitude gain and the second high-frequency noise power gain to a nonlinear deviation integral control unit to obtain an integral control signal; the method comprises the following steps:
inputting the preset high-frequency noise amplitude gain to a first square root operation unit to obtain a first square root operation signal;
inputting the second high-frequency noise power gain to a second square root operation unit to obtain a second square root operation signal;
the transfer functions of the first square root operation unit and the second square root operation unit are as follows:
Figure FDA0003613225160000031
wherein S isSRO:A(t) is the transfer function of the first square root operation unit, HFNPGC is the preset high frequency noise amplitude gain, SSRO:B(t) is a transfer function of the second square root unit, HFNPG(s) (t) is a second high frequency noise power gain, and t is a time value;
inputting the first square root operation signal and the second square root operation signal to a comparator to obtain a comparison signal;
the transfer function of the comparator is:
Figure FDA0003613225160000041
wherein S isC(t) is the transfer function of the comparator, SSRO:A(t) is the transfer function of the first square root arithmetic unit, SSRO:B(t) is the transfer function of the second square root arithmetic unit, DZCIs the dead zone of the comparator, t is the time value;
acquiring an output signal of automatic tracking-stopping, and inputting the comparison signal, the output signal of automatic tracking-stopping and a constant 1 into an integral controller to obtain an integral control signal;
the transfer function of the integral controller is:
Figure FDA0003613225160000042
wherein S isIC(t) is the transfer function of the integral controller, TI is the tracking input of the integral controller, OTC is the output tracking control of the integral controller, AT/S is the output signal of automatic tracking-stop, SC(t) is the transfer function of the comparator, t is the time value;
inputting the integral control signal and the noise filtering original parameter into a multiplier to obtain an inertial lag time constant given signal;
the transfer function of the multiplier is:
NFPCV:S(t)＝SIC(t)NFPOV；
wherein, NFPCV is the transfer function of the multiplier, S (t)IC(t) is a transfer function of the integral controller, NFPOV is a noise filtering original parameter, and t is a time value;
inputting the given signal of the inertial lag time constant into a second noise filter, adjusting the second noise filter, and inputting the given signal of the inertial lag time constant and the original noise filtering parameter into a first-order inertial filter to obtain a noise filtering parameter control signal;
the transfer function of the first order inertial filter is:
Figure FDA0003613225160000051
Figure FDA0003613225160000052
wherein FOIF(s) is a transfer function of a first order inertial filter, TFOIFNFPCV (t) is a time constant of a first-order inertial filter, NFPCV (t) is a noise-filtered original parameter control value, GI is a tracking input of the first-order inertial filter, NFPOV is a noise-filtered original parameter, OGC is a tracking control of the first-order inertial filter, an output signal of AT/S automatic tracking-stop, L is a time constant of the first-order inertial filter, NFPCV (t) is a noise-filtered original parameter control value, and OGC is a tracking control signal of the first-order inertial filter-1For inverse Laplace transform, NFPCV is the process of controlling the value of the second noise filtering parameter by S (t), s is Laplace operator, and t is the time value;
and inputting the input signal of the improved high-performance advanced observer and the noise filtering parameter control signal to the improved high-performance advanced observer to obtain an output signal of the improved high-performance advanced observer.
2. An automatic tracking system for improving high-frequency noise power gain of a high-performance advanced observer is applied to process control of a thermal power generating unit, and comprises:
the second noise filter establishing and operating module is used for acquiring noise filtering original parameters of the noise filter and constructing a second noise filter according to the noise filtering original parameters; acquiring an input signal of a second noise filter, and inputting the input signal of the second noise filter into the second noise filter to obtain an output signal of the second noise filter;
the transfer function of the second noise filter is:
Figure FDA0003613225160000053
s (S) is a transfer function of a second noise filter, S is a noise filtering original parameter, FTCCV (S) (t) is a second noise filtering parameter control signal, S is a Laplace operator, and t is a time value;
the high-frequency noise power gain calculation module is used for acquiring an input signal of the improved high-performance advanced observer, and inputting the input signal of the improved high-performance advanced observer and an output signal of the second noise filter into the high-frequency noise power gain calculation unit to obtain a second high-frequency noise power gain; the method comprises the following steps:
inputting the input signal of the improved high-performance advanced observer into a first high-pass filtering unit to obtain a first high-pass filtering signal; inputting the first high-pass filtering signal to a first square operation unit to obtain a first square operation signal; inputting the first square operation signal to a first average operation unit to obtain a first average signal;
inputting the output signal of the second noise filter to a second high-pass filtering unit to obtain a second high-pass filtering signal; inputting the second high-pass filtering signal to a second square operation unit to obtain a second square operation signal; inputting the second square operation signal to a second average value operation unit to obtain a second average value signal;
inputting the first average value signal and the second average value signal to a division operation unit to obtain a second high-frequency noise power gain;
the transfer function of the improved high-performance advanced observer is as follows:
Figure FDA0003613225160000061
wherein IHPLO(s) is a transfer function for improving the high performance advanced observer, KGCGain, K, for improving the gain compensation of a high performance lead observerIPCTo improve the gain of the internal proportional control of the high performance lead observer, NF(s) is the transfer function of the noise filter, TNFPFor the noise filter raw parameters, ESWF(s) is the transfer function of the engineered sliding window filter, nESWFOrder of an engineered sliding window filter, TIHPLOIn order to improve the time constant of the high-performance advanced observer, s is a Laplace operator;
the transfer function of the high-frequency noise power gain calculation unit is as follows:
Figure FDA0003613225160000071
wherein HFNPG (t) is a transfer function of the high frequency noise power gain calculation unit, L-1For inverse Laplace transform, MOV B(s) is the transfer function of the second average operation unit, HPF B(s) is the transfer function of the second high-pass filtering unit, OSHPF:B(t) second high-pass filtering of the output signal, OSSO:B(t) IS the second square operation output signal process, IS, B and t are the second input signals, MOV, A and s are the transfer functions of the first average operation unit, HPF, A and s are the transfer functions of the first high-pass filter unit, OSHPF:A(t) IS the first high-pass filtered output signal process, IS (A), (t) IS the first input signal, OSSO:A(T) a process of outputting a signal by the first squaring unit, TMTThe first average operation unit and the second average operation unit are commonAverage time of (T)HPFThe time constant is a common high-pass filtering time constant of the first high-pass filtering unit and the second high-pass filtering unit, s is a Laplace operator, and t is a time value;
the nonlinear deviation integral control module is used for acquiring a preset high-frequency noise amplitude gain and inputting the preset high-frequency noise amplitude gain and the second high-frequency noise power gain to the nonlinear deviation integral control unit to obtain an integral control signal; the method comprises the following steps:
inputting the preset high-frequency noise amplitude gain to a first square root operation unit to obtain a first square root operation signal;
inputting the second high-frequency noise power gain to a second square root operation unit to obtain a second square root operation signal;
the transfer functions of the first square root operation unit and the second square root operation unit are as follows:
Figure FDA0003613225160000081
wherein S isSRO:A(t) is the transfer function of the first square root operation unit, HFNPGC is the preset high frequency noise amplitude gain, SSRO:B(t) is a transfer function of the second square root unit, HFNPG(s) (t) is a second high frequency noise power gain, and t is a time value;
inputting the first square root operation signal and the second square root operation signal to a comparator to obtain a comparison signal;
the transfer function of the comparator is:
Figure FDA0003613225160000082
wherein S isC(t) is the transfer function of the comparator, SSRO:A(t) is the transfer function of the first square root arithmetic unit, SSRO:B(t) is the transfer function of the second square root arithmetic unit, DZCIs the dead zone of the comparator, t is the time value；
Acquiring an output signal of automatic tracking-stopping, and inputting the comparison signal, the output signal of automatic tracking-stopping and a constant 1 into an integral controller to obtain an integral control signal;
the transfer function of the integral controller is:
Figure FDA0003613225160000083
wherein S isIC(t) is the transfer function of the integral controller, TI is the tracking input of the integral controller, OTC is the output tracking control of the integral controller, AT/S is the output signal of automatic tracking-stop, SC(t) is the transfer function of the comparator, t is the time value;
the multiplier operation module is used for inputting the integral control signal and the noise filtering original parameter into a multiplier to obtain an inertia lag time constant given signal;
the transfer function of the multiplier is:
NFPCV:S(t)＝SIC(t)NFPOV；
wherein, NFPCV is the transfer function of the multiplier, S (t)IC(t) is a transfer function of the integral controller, NFPOV is a noise filtering original parameter, and t is a time value;
the first-order inertial filter operation module is used for inputting the inertial lag time constant given signal to a second noise filter, adjusting the second noise filter, and inputting the inertial lag time constant given signal and the noise filtering original parameter to the first-order inertial filter to obtain a noise filtering parameter control signal; the transfer function of the first order inertial filter is:
Figure FDA0003613225160000091
Figure FDA0003613225160000092
wherein FOIF(s) is a transfer function of a first order inertial filter, TFOIFNFPCV (t) is a time constant of a first-order inertial filter, NFPCV (t) is a noise-filtered original parameter control value, GI is a tracking input of the first-order inertial filter, NFPOV is a noise-filtered original parameter, OGC is a tracking control of the first-order inertial filter, an output signal of AT/S automatic tracking-stop, L is a time constant of the first-order inertial filter, NFPCV (t) is a noise-filtered original parameter control value, and OGC is a tracking control signal of the first-order inertial filter-1For inverse Laplace transform, NFPCV is the process of controlling the value of the second noise filtering parameter by S (t), s is Laplace operator, and t is the time value;
and the improved high-performance advanced observer operation module is used for inputting the input signal of the improved high-performance advanced observer and the noise filtering parameter control signal to the improved high-performance advanced observer to obtain an output signal of the improved high-performance advanced observer.
CN202110578913.1A 2021-05-26 2021-05-26 Automatic tracking method for high-frequency noise power gain of high-performance advanced observer Active CN113311706B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110578913.1A CN113311706B (en) 2021-05-26 2021-05-26 Automatic tracking method for high-frequency noise power gain of high-performance advanced observer

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110578913.1A CN113311706B (en) 2021-05-26 2021-05-26 Automatic tracking method for high-frequency noise power gain of high-performance advanced observer

Publications (2)

Publication Number Publication Date
CN113311706A CN113311706A (en) 2021-08-27
CN113311706B true CN113311706B (en) 2022-05-27

Family

ID=77375169

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110578913.1A Active CN113311706B (en) 2021-05-26 2021-05-26 Automatic tracking method for high-frequency noise power gain of high-performance advanced observer

Country Status (1)

Country Link
CN (1) CN113311706B (en)

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002318280A (en) * 2001-04-24 2002-10-31 Mitsubishi Electric Corp Method for determining position of target and method for determining moving route of target in sensor installation error estimation
TW200841141A (en) * 2006-11-21 2008-10-16 Yaskawa Denki Seisakusho Kk Servo control apparatus and control method thereof
CN101454969A (en) * 2006-05-26 2009-06-10 株式会社安川电机 Servo controller
CN104201962A (en) * 2014-08-26 2014-12-10 中国科学院电工研究所 Method for identifying traction induction motor parameter of high-speed train
CN109270836A (en) * 2018-11-08 2019-01-25 广东电网有限责任公司 A kind of integrated signal extracting method, device and equipment
CN109901385A (en) * 2019-03-19 2019-06-18 广东电网有限责任公司 A kind of look-ahead method and device
CN109932898A (en) * 2019-03-29 2019-06-25 广东电网有限责任公司 A kind of adjustable look-ahead device
CN110045408A (en) * 2019-04-25 2019-07-23 东南大学 One kind being based on the approximate satellite/inertia depth coupling process of code phase
CN110601624A (en) * 2019-08-16 2019-12-20 南京埃斯顿自动化股份有限公司 Servo control device
CN111552177A (en) * 2020-04-22 2020-08-18 深圳市科润宝实业有限公司 Method and device for improving performance of controller, computer equipment and storage medium

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002318280A (en) * 2001-04-24 2002-10-31 Mitsubishi Electric Corp Method for determining position of target and method for determining moving route of target in sensor installation error estimation
CN101454969A (en) * 2006-05-26 2009-06-10 株式会社安川电机 Servo controller
TW200841141A (en) * 2006-11-21 2008-10-16 Yaskawa Denki Seisakusho Kk Servo control apparatus and control method thereof
CN104201962A (en) * 2014-08-26 2014-12-10 中国科学院电工研究所 Method for identifying traction induction motor parameter of high-speed train
CN109270836A (en) * 2018-11-08 2019-01-25 广东电网有限责任公司 A kind of integrated signal extracting method, device and equipment
CN109901385A (en) * 2019-03-19 2019-06-18 广东电网有限责任公司 A kind of look-ahead method and device
CN109932898A (en) * 2019-03-29 2019-06-25 广东电网有限责任公司 A kind of adjustable look-ahead device
CN110045408A (en) * 2019-04-25 2019-07-23 东南大学 One kind being based on the approximate satellite/inertia depth coupling process of code phase
CN110601624A (en) * 2019-08-16 2019-12-20 南京埃斯顿自动化股份有限公司 Servo control device
CN111552177A (en) * 2020-04-22 2020-08-18 深圳市科润宝实业有限公司 Method and device for improving performance of controller, computer equipment and storage medium

Non-Patent Citations (9)

* Cited by examiner, † Cited by third party
Title
A Hybrid-Type Variable-Structure Instantaneous Torque Control With a Robust Adaptive Torque Observer for a High-Performance Direct-Drive PMSM;Yasser Abdel-Rady 等;《IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS》;20071031;第54卷(第5期);全文 *
Discrete Implementation and Generalization of the Extended State Observer;Robert Miklosovic 等;《Proceedings of the 2006 American Control Conference》;20060716;全文 *
Flux-Observer-Based High-Performance Control of Synchronous Reluctance Motors by Including Cross Saturation;Alfredo Vagati 等;《IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS》;19990731;第35卷(第3期);全文 *
Implementation Issues and Performance Evaluation of Sinusoidal, Surface-Mounted PM Machine Drives With Hall-Effect Position Sensors and a Vector-Tracking Observer;Michael C. Harke;《IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS》;20080228;第44卷(第1期);全文 *
Superheated steam temperature control based on closed loop control of temperature-reducing water flow;Huang WeiJian 等;《International Forum on Electrical Engineering and Automation》;20200731;全文 *
一种新型基础控制器的介绍;刘昌一 等;《技术纵横》;20200131;全文 *
一种新型控制策略在脱硝控制中的应用;陈云强 等;《湖北电力》;20191031;第43卷(第5期);全文 *
一种新型高性能控制器的研究与应用;李军 等;《自动化学报》;20201231;第46卷(第12期);全文 *
在工业过程控制领域: 基础控制技术的进展与展望;李军 等;《自动化学报》;20190507;全文 *

Also Published As

Publication number Publication date
CN113311706A (en) 2021-08-27

Similar Documents

Publication Publication Date Title
CN109856978B (en) Method and device for obtaining controlled object model
CN112356683B (en) Anti-shaking method, device and equipment based on electric automobile and storage medium
CN113311708B (en) Method and system for tracking high-frequency noise amplitude gain adjustment control strategy parameters
CN113359413B (en) Parameter adjusting system and method of actual differentiator
CN113341720B (en) Control method, system and device for linear steepest tracking filter
CN113311706B (en) Automatic tracking method for high-frequency noise power gain of high-performance advanced observer
CN113296411B (en) Method and system for tracking high-frequency noise power gain adjustment control strategy parameters
CN113311755B (en) Automatic tracking improvement method and system for high-frequency noise amplitude gain
CN113312585B (en) High-frequency noise power gain online tracking method for parameter adjustment of high-order control strategy
CN113311699B (en) Automatic tracking method for high-frequency noise amplitude gain of high-performance advanced observer
Tepljakov et al. Implementation and real-time simulation of a fractional-order controller using a MATLAB based prototyping platform
CN113325710B (en) Automatic tracking system and method for high-frequency noise amplitude gain
CN104035462A (en) Power supply control method and device
CN111294014B (en) Signal integration deviation removing method and system and electronic equipment thereof
CN113189919B (en) Control system and method for high-frequency noise power gain
CN113296396B (en) Automatic tracking system and method for high-frequency noise power gain
CN113193848B (en) Online measurement method for improving high-frequency noise power gain of novel basic controller
CN113204230A (en) On-line measurement method for high-frequency noise power gain of sliding window tracking differentiator
CN113204876B (en) Noise gain calculation method, device, equipment and medium of PD controller
CN113189965B (en) Online measurement method and system for noise power gain of novel cascade controller
CN116505810B (en) Method, device, equipment and medium for suppressing oscillation of wave trap and servo system
CN113176729A (en) Noise interference detection method, device, equipment and medium for PID controller
CN115045769B (en) Engine load control system and method, electronic terminal and storage medium
CN113300676B (en) System and method for automatically tracking noise power gain of actual differentiator
CN113114119A (en) Method and system for judging noise interference level of novel feedback controller on line

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant