CN105334737B - A kind of sliding mode observer optimization method and system - Google Patents
A kind of sliding mode observer optimization method and system Download PDFInfo
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- CN105334737B CN105334737B CN201510857467.2A CN201510857467A CN105334737B CN 105334737 B CN105334737 B CN 105334737B CN 201510857467 A CN201510857467 A CN 201510857467A CN 105334737 B CN105334737 B CN 105334737B
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- 238000005457 optimization Methods 0.000 title claims abstract description 56
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000009415 formwork Methods 0.000 claims description 9
- 238000009795 derivation Methods 0.000 claims description 8
- 230000009897 systematic effect Effects 0.000 claims description 6
- 238000010276 construction Methods 0.000 claims description 5
- 230000000694 effects Effects 0.000 claims description 4
- 238000003860 storage Methods 0.000 claims description 3
- 238000013459 approach Methods 0.000 claims 1
- 238000005516 engineering process Methods 0.000 description 3
- 244000145845 chattering Species 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
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- 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
Abstract
This application discloses a kind of sliding mode observer optimization methods and system, this method to include：According to the parameter of electric machine, the state space of sliding mode observer is constructed；Wherein, the type of above-mentioned sliding mode observer is power tendency rate type, and above-mentioned state space includes the switching function of above-mentioned sliding mode observer；The power of power item is configured to reflect the first function of the robustness of above-mentioned sliding mode observer as variable using in switching function, and is configured to reflect the second function of the observation error of above-mentioned sliding mode observer；Linear superposition is carried out to first function and second function, obtains the object function using power as variable；Using one-dimensional optimization, optimizing processing is carried out to object function, and the optimizing value accordingly obtained is determined as to the optimal value of power.In the application, by one-dimensional optimization, thus the observation error of sliding mode observer can be reduced to obtain corresponding optimizing value by carrying out optimizing processing to above-mentioned object function, and ensure that sliding mode observer has enough robustness simultaneously.
Description
Technical field
The present invention relates to sliding formwork control technical field, more particularly to a kind of sliding mode observer optimization method and system.
Background technology
Sliding mode observer is a kind of state observer designed using sliding formwork control principle, with simple in structure, robust
The advantages that property is strong and good dynamic response characteristic.
However, during practical application, the switching function of sliding mode observer can cause chattering phenomenon, to increase cunning
The observation error of mould observer.
In summary as can be seen that how to reduce the observation error of sliding mode observer, and ensure that sliding mode observer has foot
Enough robustness are that have problem to be solved at present.
Invention content
In view of this, the purpose of the present invention is to provide a kind of sliding mode observer optimization method and system, cunning can be reduced
The observation error of mould observer, while it is also ensured that sliding mode observer has enough robustness.Its concrete scheme is as follows：
A kind of sliding mode observer optimization method, including：
According to the parameter of electric machine, the state space of sliding mode observer is constructed；Wherein, the type of the sliding mode observer is power
Tendency rate type, the state space include the switching function of the sliding mode observer；
Using the power of power item in the switching function as variable, it is configured to reflect the robust of the sliding mode observer
The first function of property, and be configured to reflect the second function of the observation error of the sliding mode observer；
Linear superposition is carried out to the first function and the second function, obtains the target letter using the power as variable
Number；
Using one-dimensional optimization, optimizing processing is carried out to the object function, and the optimizing value accordingly obtained is determined as
The optimal value of the power.
Preferably, described to utilize one-dimensional optimization, the process of optimizing processing is carried out to the object function, including：It utilizes
Fibonacci method carries out optimizing processing to the object function.
Preferably, the state space is：
Gain coefficient k in the state space1、k2、k3And k4Meet following condition：
Wherein, sign () indicates sign function；x1=iab, iabIndicate the current value between a phases and b phases；x3=uab,
uabIndicate the current value between a phases and b phases；x2=ibc, ibcIndicate the current value between b phases and c phases；x4=ebc, ebcIndicate b
The mutually inverse electromotive force between c phases；v1=uab, uabIndicate the voltage value between a phases and b phases；v2=ubc, ubcIndicate b phases and
Voltage value between c phases；α1=-R/L1, α2=-1/L1, R expression armature internal resistances, L1It indicates between armature inductance and alternate mutual inductance
Difference；e3Expression pairCarry out the value obtained after derivation；e4Expression pairCarry out the value obtained after derivation；S indicate with it is described
The corresponding switching surface function of sliding mode observer；α indicates the power；Wherein, the formula (3) in the state space and formula (4) structure
At the switching function.
Preferably, the first function is：
Wherein, α indicates the power；Em(α) is indicated in the case where systematic parameter matching error is m, counter electromotive force letter
Number relative error standard deviation；E0(α) is indicated in the case where systematic parameter matching error is 0, the phase of back-emf signal
To the standard deviation of error.
Preferably, the second function is specially B (α), wherein B (α) indicates the observation and reality of the sliding mode observer
The standard deviation of relative error between actual value.
Preferably, described that linear superposition is carried out to the first function and the second function, obtain be with the power
The process of the object function of variable, including：
The respectively described first function assigns corresponding weight coefficient with the second function and carries out being added processing, obtains
The object function；Wherein, the object function is：
F (α)=PA (α)+QB (α)
Wherein, P indicates the weight coefficient of the first function A (α)；Q indicates the weight coefficient of the second function B (α).
Preferably, the weight coefficient of the weight coefficient and second function B (α) of the first function A (α) determined
Journey, including：
Obtain performance expectation information input by user；The performance expectation information includes user to the sliding mode observer
The expectation index of the expectation index and the observation error to the sliding mode observer of robustness；
According to the performance expectation information, the corresponding relation data between preset expected performance information and weight coefficient
In library, the weight coefficient of the weight coefficient and the second function B (α) of the first function A (α) is correspondingly found out.
Preferably, the sliding mode observer optimization method further includes：
After having carried out optimization processing to each sliding mode observer, according to preset assessment strategy, to this suboptimization place
The effect of optimization of reason process is assessed automatically, and by obtained assessment information storage to assessing information database；
According to the preset amendment period, periodically using the assessment information database to being protected in the corresponding relation database
The correspondence deposited carries out corresponding automatic amendment.
The invention also discloses a kind of sliding mode observer optimization systems, including：
State space constructing module, for according to the parameter of electric machine, constructing the state space of sliding mode observer；Wherein, described
The type of sliding mode observer is power tendency rate type, and the state space includes the switching function of the sliding mode observer；
Function construction module, for using the power of power item in the switching function as variable, being configured to reflection institute
The first function of the robustness of sliding mode observer is stated, and is configured to reflect the second of the observation error of the sliding mode observer
Function；
Function superposition module is obtained for carrying out linear superposition to the first function and the second function with described
Power is the object function of variable；
Function optimizing module carries out optimizing processing, and will be mutually deserved for utilizing one-dimensional optimization to the object function
To optimizing value be determined as the optimal value of the power.
Preferably, the function optimizing module, is specifically used for utilizing Fibonacci method, and optimizing is carried out to the object function
Processing.
In the present invention, sliding mode observer optimization method includes：According to the parameter of electric machine, the state for constructing sliding mode observer is empty
Between；Wherein, the type of above-mentioned sliding mode observer is power tendency rate type, and above-mentioned state space includes cutting for above-mentioned sliding mode observer
Exchange the letters number；The power of power item is configured to reflect the robustness of above-mentioned sliding mode observer as variable using in switching function
First function, and be configured to reflect the second function of the observation error of above-mentioned sliding mode observer；To first function and second
Function carries out linear superposition, obtains the object function using power as variable；Using one-dimensional optimization, optimizing is carried out to object function
It handles, and the optimizing value accordingly obtained is determined as to the optimal value of power.As it can be seen that in the present invention, by with the power in power item
It is secondary to be used as variable, construct the first function of the robustness for reflecting above-mentioned sliding mode observer and for reflecting above-mentioned sliding formwork
The second function of the observation error of observer, then by one-dimensional optimization, to what is obtained using first function and second function
Linear object function carries out optimizing processing, to obtain corresponding optimizing value, using the optimizing value as the optimal of above-mentioned power
Value, thus can reduce the observation error of above-mentioned sliding mode observer, and ensure that sliding mode observer has enough robustness simultaneously.
Description of the drawings
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The embodiment of invention for those of ordinary skill in the art without creative efforts, can also basis
The attached drawing of offer obtains other attached drawings.
Fig. 1 is a kind of sliding mode observer optimization method flow chart disclosed by the embodiments of the present invention；
Fig. 2 is a kind of specific sliding mode observer optimization method flow chart disclosed by the embodiments of the present invention；
Fig. 3 is a kind of sliding mode observer optimization system structural schematic diagram disclosed by the embodiments of the present invention.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation describes, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Shown in Figure 1 the embodiment of the invention discloses a kind of sliding mode observer optimization method, this method includes：
Step S11：According to the parameter of electric machine, the state space of sliding mode observer is constructed；Wherein, the class of above-mentioned sliding mode observer
Type is power tendency rate type, and above-mentioned state space includes the switching function of above-mentioned sliding mode observer；
Step S12：The power of power item is configured to reflect above-mentioned sliding mode observer as variable using in switching function
The first function of robustness, and be configured to reflect the second function of the observation error of above-mentioned sliding mode observer；
Step S13：Linear superposition is carried out to first function and second function, obtains the target letter using above-mentioned power as variable
Number；
Step S14：Using one-dimensional optimization, optimizing processing is carried out to object function, and the optimizing value accordingly obtained is true
It is set to the optimal value of above-mentioned power.
In the embodiment of the present invention, sliding mode observer optimization method includes：According to the parameter of electric machine, the shape of sliding mode observer is constructed
State space；Wherein, the type of above-mentioned sliding mode observer is power tendency rate type, and above-mentioned state space includes above-mentioned sliding mode observer
Switching function；The power of power item is configured to reflect the robust of above-mentioned sliding mode observer as variable using in switching function
The first function of property, and be configured to reflect the second function of the observation error of above-mentioned sliding mode observer；To first function and
Second function carries out linear superposition, obtains the object function using power as variable；Using one-dimensional optimization, object function is carried out
Optimizing is handled, and the optimizing value accordingly obtained is determined as to the optimal value of power.
As it can be seen that in the embodiment of the present invention, by using the power in power item as variable, constructing for reflecting above-mentioned cunning
The second function of the first function of the robustness of mould observer and observation error for reflecting above-mentioned sliding mode observer, then
By one-dimensional optimization, optimizing processing is carried out to the linear object function obtained using first function and second function, to
Corresponding optimizing value is obtained, using the optimizing value as the optimal value of above-mentioned power, thus can reduce the sight of above-mentioned sliding mode observer
Error is surveyed, and ensures that sliding mode observer has enough robustness simultaneously.
The embodiment of the invention discloses a kind of specific sliding mode observer optimization methods, relative to a upper embodiment, this reality
It applies example and further instruction and optimization has been made to technical solution.Specifically：
Shown in Figure 2, upper embodiment step S14 carries out optimizing specifically, using Fibonacci method to object function
Processing.It should be noted that above-mentioned Fibonacci method is a kind of one dimensional optimization method.Certainly, user can also according to itself
Actual needs carries out optimizing processing, such as quadratic interpolattion using other kinds of one-dimensional optimization to above-mentioned object function.
In addition, the state space in above-described embodiment step S11 is specifically as follows：
Gain coefficient k in above-mentioned state space1、k2、k3And k4Meet following condition：
Wherein, sign () indicates sign function；x1=iab, iabIndicate the current value between a phases and b phases；x3=uab,
uabIndicate the current value between a phases and b phases；x2=ibc, ibcIndicate the current value between b phases and c phases；x4=ebc, ebcIndicate b
The mutually inverse electromotive force between c phases；v1=uab, uabIndicate the voltage value between a phases and b phases；v2=ubc, ubcIndicate b phases and
Voltage value between c phases；α1=-R/L1, α2=-1/L1, R expression armature internal resistances, L1It indicates between armature inductance and alternate mutual inductance
Difference；e3Expression pairCarry out the value obtained after derivation；e4Expression pairCarry out the value obtained after derivation；S is indicated and sliding formwork
The corresponding switching surface function of observer；α indicates power item | s |αIn power；Wherein, the formula in state space (3) and formula (4)
Constitute switching function.
The condition met is needed it is found that when power α changes from above-mentioned state space and gain coefficient, and sliding formwork is seen
The robustness and observation error for surveying device can change, and the variation tendency of the two is just on the contrary, that is, work as power α
When changing, if robustness is deteriorated, observation error if, can be reduced；If robustness enhances, observation error if, can increase.For
In the case where ensureing that sliding mode observer has enough robustness, observation error is reduced as much as possible, just need according to user
Actual demand, optimizing processing is carried out to power α, to determine optimal power α, to meet the needs of users.
Further, the first function in above-described embodiment step S12 is specially：
Wherein, α is power item | s |αIn power；Em(α) is indicated in the case where systematic parameter matching error is m, instead
The standard deviation of the relative error of electromotive force signal；E0(α) is indicated in the case where systematic parameter matching error is 0, counter electromotive force
The standard deviation of the relative error of signal.
And the second function in above-described embodiment step S12 is specially B (α), wherein B (α) indicates the sight of sliding mode observer
The standard deviation of relative error between measured value and actual value.
In addition, the detailed process of upper embodiment step S13 is：Respectively first function and second function assign corresponding
Weight coefficient simultaneously carries out addition processing, obtains object function；Wherein, object function is：
F (α)=PA (α)+QB (α)
Wherein, P indicates the weight coefficient of first function A (α)；Q indicates the weight coefficient of second function B (α).
Preferably, the determination process of the weight coefficient of the weight coefficient and second function B (α) of above-mentioned first function A (α),
It can specifically include：Obtain performance expectation information input by user；Performance expectation information includes Shandong of the user to sliding mode observer
The expectation index of the expectation index and the observation error to sliding mode observer of stick；According to performance expectation information, from the preset phase
It hopes in the corresponding relation database between performance information and weight coefficient, correspondingly finds out the weight coefficient of first function A (α)
With the weight coefficient of second function B (α).
Certainly, the weight coefficient of above-mentioned first function A (α) and the weight coefficient of second function B (α) can also be straight by user
Input is connect to obtain.
Continuous perfect in order to be carried out to above-mentioned corresponding relation database, the present embodiment can also include：To each cunning
After mould observer has carried out optimization processing, according to preset assessment strategy, to the effect of optimization of this optimization process into
The automatic assessment of row, and by obtained assessment information storage to assessing information database；According to the preset amendment period, periodically utilize
Assessment information database carries out corresponding automatic amendment to the correspondence preserved in above-mentioned corresponding relation database.
Shown in Figure 3 the embodiment of the invention also discloses a kind of sliding mode observer optimization system, which includes：
State space constructing module 31, for according to the parameter of electric machine, constructing the state space of sliding mode observer；Wherein, on
The type for stating sliding mode observer is power tendency rate type, and above-mentioned state space includes the switching function of above-mentioned sliding mode observer；
Function construction module 32, the power for the power item using in switching function are configured to reflect above-mentioned as variable
The first function of the robustness of sliding mode observer, and be configured to reflect the second letter of the observation error of above-mentioned sliding mode observer
Number；
Function superposition module 33, for carrying out linear superposition to first function and second function, obtain be with above-mentioned power
The object function of variable；
Function optimizing module 34 carries out optimizing processing, and will accordingly obtain for utilizing one-dimensional optimization to object function
Optimizing value be determined as the optimal value of above-mentioned power.
Wherein, above-mentioned function optimizing module 34 is specifically used for utilizing Fibonacci method, be carried out at optimizing to object function
Reason.It should be noted that above-mentioned Fibonacci method is a kind of one dimensional optimization method.It is of course also possible to according to actual needs, use
Other kinds of one-dimensional optimization carries out optimizing processing, such as quadratic interpolattion to above-mentioned object function.
Closing modules in this present embodiment, more specifically effect please refers to previous embodiment, and details are not described herein.
In the embodiment of the present invention, sliding mode observer optimization system includes：State space constructing module, for being joined according to motor
Number, constructs the state space of sliding mode observer；Wherein, the type of above-mentioned sliding mode observer is power tendency rate type, above-mentioned state
Space includes the switching function of above-mentioned sliding mode observer；Function construction module, for being made with the power of power item in switching function
For variable, it is configured to reflect the first function of the robustness of above-mentioned sliding mode observer, and be configured to reflect above-mentioned sliding formwork
The second function of the observation error of observer；Function superposition module, for carrying out linear superposition to first function and second function,
It obtains using above-mentioned power as the object function of variable；Function optimizing module carries out object function for utilizing one-dimensional optimization
Optimizing is handled, and the optimizing value accordingly obtained is determined as to the optimal value of above-mentioned power.
As it can be seen that in the embodiment of the present invention, function construction module is by using the power in power item as variable, constructing use
In the first function of the robustness that reflects above-mentioned sliding mode observer and observation error for reflecting above-mentioned sliding mode observer
Second function, then function optimizing module is by one-dimensional optimization, linear to being obtained using first function and second function
Object function carries out optimizing processing, to obtain corresponding optimizing value, using the optimizing value as the optimal value of above-mentioned power, thus
The observation error of above-mentioned sliding mode observer can be reduced, and ensures that sliding mode observer has enough robustness simultaneously.
Finally, it is to be noted that, herein, relational terms such as first and second and the like be used merely to by
One entity or operation are distinguished with another entity or operation, without necessarily requiring or implying these entities or operation
Between there are any actual relationship or orders.Moreover, the terms "include", "comprise" or its any other variant meaning
Covering non-exclusive inclusion, so that the process, method, article or equipment including a series of elements includes not only that
A little elements, but also include other elements that are not explicitly listed, or further include for this process, method, article or
The intrinsic element of equipment.In the absence of more restrictions, the element limited by sentence "including a ...", is not arranged
Except there is also other identical elements in the process, method, article or apparatus that includes the element.
A kind of sliding mode observer optimization method provided by the present invention and system are described in detail above, herein
Applying specific case, principle and implementation of the present invention are described, and the explanation of above example is only intended to help
Understand the method and its core concept of the present invention；Meanwhile for those of ordinary skill in the art, according to the thought of the present invention,
There will be changes in the specific implementation manner and application range, in conclusion the content of the present specification should not be construed as to this
The limitation of invention.
Claims (9)
1. a kind of sliding mode observer optimization method, which is characterized in that including：
According to the parameter of electric machine, the state space of sliding mode observer is constructed；Wherein, the type of the sliding mode observer approaches for power
Rate type, the state space include the switching function of the sliding mode observer；
Using the power of power item in the switching function as variable, it is configured to reflect the robustness of the sliding mode observer
First function, and be configured to reflect the second function of the observation error of the sliding mode observer；
Linear superposition is carried out to the first function and the second function, is obtained using the power as the object function of variable；
Using one-dimensional optimization, optimizing processing is carried out to the object function, and the optimizing value accordingly obtained is determined as described
The optimal value of power；
Wherein, the state space is：
Gain coefficient k in the state space1、k2、k3And k4Meet following condition：
Wherein, sign () indicates sign function；x1=iab, iabIndicate the current value between a phases and b phases；x3=uab, uabIt indicates
Voltage value between a phases and b phases；x2=ibc, ibcIndicate the current value between b phases and c phases；x4=ebc, ebcIndicate b phases and c phases
Between inverse electromotive force；v1=uab, uabIndicate the voltage value between a phases and b phases；v2=ubc, ubcIt indicates between b phases and c phases
Voltage value；α1=-R/L1, α2=-1/L1, R expression armature internal resistances, L1Indicate the difference between armature inductance and alternate mutual inductance；
e3Expression pairCarry out the value obtained after derivation；e4Expression pairCarry out the value obtained after derivation；S indicates to observe with the sliding formwork
The corresponding switching surface function of device；α indicates the power；Wherein, the formula (3) in the state space and formula (4) constitute described
Switching function.
2. sliding mode observer optimization method according to claim 1, which is characterized in that
It is described to utilize one-dimensional optimization, the process of optimizing processing is carried out to the object function, including：Using Fibonacci method,
Optimizing processing is carried out to the object function.
3. sliding mode observer optimization method according to claim 1, which is characterized in that the first function is：
Wherein, α indicates the power；Em(α) is indicated in the case where systematic parameter matching error is m, the phase of back-emf signal
To the standard deviation of error；E0(α) is indicated in the case where systematic parameter matching error is 0, the relative error of back-emf signal
Standard deviation.
4. sliding mode observer optimization method according to claim 3, which is characterized in that the second function is specially B
(α), wherein B (α) indicates the standard deviation of the relative error between the observation and actual value of the sliding mode observer.
5. sliding mode observer optimization method according to claim 4, which is characterized in that described to the first function and institute
It states second function and carries out linear superposition, obtain using the power as the process of the object function of variable, including：
The respectively described first function assigns corresponding weight coefficient with the second function and carries out being added processing, obtains described
Object function；Wherein, the object function is：
F (α)=PA (α)+QB (α)
Wherein, P indicates the weight coefficient of the first function A (α)；Q indicates the weight coefficient of the second function B (α).
6. sliding mode observer optimization method according to claim 5, which is characterized in that the weight of the first function A (α)
The determination process of the weight coefficient of coefficient and the second function B (α), including：
Obtain performance expectation information input by user；The performance expectation information includes robust of the user to the sliding mode observer
Property expectation index and the observation error to the sliding mode observer expectation index；
According to the performance expectation information, the corresponding relation database between preset expected performance information and weight coefficient
In, correspondingly find out the weight coefficient of the weight coefficient and the second function B (α) of the first function A (α).
7. sliding mode observer optimization method according to claim 6, which is characterized in that further include：
After having carried out optimization processing to each sliding mode observer, according to preset assessment strategy, to this optimization processing mistake
The effect of optimization of journey is assessed automatically, and by obtained assessment information storage to assessing information database；
According to the preset amendment period, periodically using the assessment information database to preserving in the corresponding relation database
Correspondence carries out corresponding automatic amendment.
8. a kind of sliding mode observer optimization system, which is characterized in that including：
State space constructing module, for according to the parameter of electric machine, constructing the state space of sliding mode observer；Wherein, the sliding formwork
The type of observer is power tendency rate type, and the state space includes the switching function of the sliding mode observer；
Function construction module, for using the power of power item in the switching function as variable, being configured to reflect the cunning
The first function of the robustness of mould observer, and be configured to reflect the second letter of the observation error of the sliding mode observer
Number；
Function superposition module is obtained for carrying out linear superposition to the first function and the second function with the power
For the object function of variable；
Function optimizing module carries out optimizing processing, and will accordingly obtain for utilizing one-dimensional optimization to the object function
Optimizing value is determined as the optimal value of the power；
Wherein, the state space is：
Gain coefficient k in the state space1、k2、k3And k4Meet following condition：
Wherein, sign () indicates sign function；x1=iab, iabIndicate the current value between a phases and b phases；x3=uab, uabIt indicates
Voltage value between a phases and b phases；x2=ibc, ibcIndicate the current value between b phases and c phases；x4=ebc, ebcIndicate b phases and c phases
Between inverse electromotive force；v1=uab, uabIndicate the voltage value between a phases and b phases；v2=ubc, ubcIt indicates between b phases and c phases
Voltage value；α1=-R/L1, α2=-1/L1, R expression armature internal resistances, L1Indicate the difference between armature inductance and alternate mutual inductance；
e3Expression pairCarry out the value obtained after derivation；e4Expression pairCarry out the value obtained after derivation；S indicates to observe with the sliding formwork
The corresponding switching surface function of device；α indicates the power；Wherein, the formula (3) in the state space and formula (4) constitute described
Switching function.
9. sliding mode observer optimization system according to claim 8, which is characterized in that the function optimizing module, specifically
For utilizing Fibonacci method, optimizing processing is carried out to the object function.
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| CN108549400B (en) * | 2018-05-28 | 2021-08-03 | 浙江工业大学 | Self-adaptive control method of four-rotor aircraft based on logarithm enhanced double-power approach law and fast terminal sliding mode surface |
| CN109358502B (en) * | 2018-10-20 | 2022-02-25 | 台州学院 | Discrete multi-period sliding mode repetitive control method for motor servo system |
| CN110426957B (en) * | 2019-07-31 | 2020-03-13 | 深圳信息职业技术学院 | Water plant dosing system self-adaptive sliding mode control method based on time delay observer |
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| US20100237817A1 (en) * | 2009-03-23 | 2010-09-23 | Jingbo Liu | Method and Apparatus for Estimating Rotor Position in a Sensorless Synchronous Motor |
| CN101964624B (en) * | 2010-10-15 | 2012-08-22 | 浙江工业大学 | Sensorless control system of permanent magnet synchronous motor |
| KR101302746B1 (en) * | 2012-05-17 | 2013-08-30 | 부산대학교 산학협력단 | Method for measuring external force of robot |
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| CN103647490B (en) * | 2013-09-27 | 2016-06-08 | 天津大学 | A kind of sliding mode control strategy of magneto |
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