CN111852673A - Kalman filtering-based rotating speed noise suppression method and rotating speed noise suppression module - Google Patents
Kalman filtering-based rotating speed noise suppression method and rotating speed noise suppression module Download PDFInfo
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- CN111852673A CN111852673A CN202010756773.8A CN202010756773A CN111852673A CN 111852673 A CN111852673 A CN 111852673A CN 202010756773 A CN202010756773 A CN 202010756773A CN 111852673 A CN111852673 A CN 111852673A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D29/00—Controlling engines, such controlling being peculiar to the devices driven thereby, the devices being other than parts or accessories essential to engine operation, e.g. controlling of engines by signals external thereto
- F02D29/06—Controlling engines, such controlling being peculiar to the devices driven thereby, the devices being other than parts or accessories essential to engine operation, e.g. controlling of engines by signals external thereto peculiar to engines driving electric generators
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D31/00—Use of speed-sensing governors to control combustion engines, not otherwise provided for
- F02D31/001—Electric control of rotation speed
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/24—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means
- F02D41/26—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means using computer, e.g. microprocessor
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
- F02D2041/1409—Introducing closed-loop corrections characterised by the control or regulation method using at least a proportional, integral or derivative controller
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
- F02D2041/1413—Controller structures or design
- F02D2041/1415—Controller structures or design using a state feedback or a state space representation
- F02D2041/1417—Kalman filter
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D2200/00—Input parameters for engine control
- F02D2200/02—Input parameters for engine control the parameters being related to the engine
- F02D2200/10—Parameters related to the engine output, e.g. engine torque or engine speed
- F02D2200/101—Engine speed
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- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- Microelectronics & Electronic Packaging (AREA)
- Combined Controls Of Internal Combustion Engines (AREA)
Abstract
The invention discloses a Kalman filtering-based rotating speed noise suppression method and a rotating speed noise suppression module. The rotational speed noise suppression module employs a microcontroller, and a processor within the microcontroller is configured to execute a kalman filter-based rotational speed noise suppression method via execution of the executable instructions. The invention can be used for a rotating speed control system in the field of motion control.
Description
Technical Field
The invention relates to a diesel engine rotating speed control method, in particular to a rotating speed noise suppression method and a rotating speed noise suppression module based on Kalman filtering and applied to a marine diesel engine, and belongs to the technical field of diesel engines.
Background
With the continuous development of marine industry, the capacity of a ship alternating current power system is continuously enlarged, and the automation degree is continuously improved, the requirements on ship technology and the quality requirements on the power generation energy of a power generation device are higher and higher. The frequency of a power grid is a key factor influencing the quality of electric energy, and has a close relation with a diesel engine rotating speed control system, the change of the rotating speed can cause the change of the frequency of the power grid, if the frequency of a diesel engine power system is stable, a diesel generator set is required to realize the stable and constant-speed operation of the rotating speed, and therefore, in order to realize the stable operation of the diesel engine and improve the quality of the electric energy of a ship power system, the research, the improvement and the design of the diesel generator set rotating speed control system are very critical.
The rotating speed control in the diesel engine rotating speed control system generally adopts a PID control technology, noise interference in the diesel engine rotating speed system can generate certain influence on the operation of the control system, and a good control effect cannot be achieved. In order to meet the high-standard strict requirement of modern industrial development on the control process, the optimization of a rotating speed control system and the regulation of the rotating speed of a diesel generator to keep the rotating speed constant are particularly important.
Disclosure of Invention
The invention aims to provide a rotating speed noise suppression method and a rotating speed noise suppression module based on Kalman filtering, which aim to solve the defect that the rotating speed of a diesel generator is difficult to keep constant in the prior art.
The purpose of the invention is realized by the following technical scheme:
a rotating speed noise suppression method based on Kalman filtering comprises the following steps:
inputting a rotating speed output signal n which is used for measuring noise V and is polluted by the noise into a Kalman filter, filtering, and inputting the signal into a rotating speed controller, wherein the filtering method of the Kalman filter comprises the following steps:
1. initial state x (0) of calculating rotation speed signal
The statistical properties of the initial state x (0) of the rotational speed signal are determined, assuming
According to
So p (0) ═ var [ x (0)](ii) a Wherein E represents an integer function, var represents the variance, and p (0) represents the estimated covariance value;
2. calculating an estimated covariance p (1) at the time when k is 1; updating the correction matrix H (1) at that moment
p(1)＝A(1)p(0)A(1)T+B(1)Q(0)B(1)T(1)
H(1)＝p(1)C(1)T[C(1)p(1)C(1)T+R(1)]-1(2)
In the formula (1), A (1) represents a functional relation between input and output at the moment, B (1) represents a system control matrix, C (1) represents a measurement matrix in the formula (2), and R (1) represents measurement noise covariance;
3. calculating the optimal estimated value of the moment when k is 1; refresh mean square error matrix P (1)
P(1)＝[I-H(1)C(1)]p(1) (4)
Y (1) in formula (3) represents an observed signal vector; carrying P (1) and H (1) obtained by calculating the formulas (1) and (2) into a formula (4) to obtain P (1), wherein I represents an identity matrix;
4. repeating the steps to obtain the optimal estimated value of k 1 and 2
5. According to
And obtaining the rotating speed output value at the k moment.
A rotational speed noise suppression module, the module employing a microcontroller, a memory within the microcontroller for storing executable instructions, a processor within the microcontroller configured to perform the aforementioned kalman filter-based rotational speed noise suppression method via execution of the executable instructions.
The invention can be further realized by the following technical measures:
the method for suppressing the rotational speed noise of the diesel engine based on the Kalman filtering is characterized in that a PLC (programmable logic controller) is adopted as a rotational speed controller.
According to the diesel engine rotating speed noise suppression method based on Kalman filtering, a PID control method is adopted by a rotating speed controller.
Compared with the prior art, the invention has the following beneficial effects:
a Kalman filter-based control algorithm is added into a diesel generating set rotating speed control system, so that noise pollution in the control and measurement processes is inhibited, a required rotating speed signal is better separated, the diesel engine rotating speed control stability is improved, stable transition can be completed by the rotating speed in the power grid load change process, and the constancy of power supply frequency is realized.
Description of the drawings:
FIG. 1 is a diagram of a diesel generator set system architecture;
FIG. 2 is a block diagram of a rotational speed control system of a diesel generator set;
FIG. 3 is a block diagram of a diesel engine speed control system based on Kalman filtering;
FIG. 4 is a Kalman filter calculation flow chart;
FIG. 5 is a diagram of an embodiment of a diesel engine speed control system using a PLC;
FIG. 6 is a flow chart of PID control of the diesel engine rotating speed based on Kalman filtering.
The specific implementation mode is as follows:
the technical solution of the present invention will be further described in detail with reference to the following specific examples.
As shown in fig. 1, the diesel generator set system is composed of a rotation speed sensor, a rotation speed controller, an actuator, a rotation speed feedback unit, a diesel engine (a throttle valve, a flywheel), and the like.
Fig. 2 and 3 show block diagrams of a speed control system of a diesel generator set, which is composed of a speed control system, a transmission device, a generator and an electric load. The rotating speed control system of the diesel generating set comprises a rotating speed controller, an actuator, a rotating speed sensor, a diesel engine and the like. A Kalman filter is added into a control algorithm of the whole rotating speed control system to inhibit the rotating speed output by a rotating speed controller and noise pollution of the rotating speed detected after the throttle valve is regulated, a required signal is separated, a filtered rotating speed signal is fed back to a rotating speed PID controller, and the influence of noise on the whole control system is reduced, so that the diesel engine can be ensured to run more stably. In FIG. 3W is the control disturbance noise signal, V is the measurement noise, n is the rotation speed output signal contaminated by the noise, neIs a rotating speed output signal corrected by a Kalman filter.
As shown in fig. 3, a kalman filter calculation flowchart is shown, and the whole process mainly includes: predicting and updating, wherein the specific work flow is as follows:
firstly, calculating a signal initial state x (0), and obtaining the statistical characteristics of the signal initial state x (0) through a system, assuming that
According to
So p (0) ═ var [ x (0)]. Where p (0) represents the estimated covariance.
Then p (1) and the correction matrix H (1) at this time of refresh are calculated.
p(1)＝A(1)p(0)A(1)T+B(1)Q(0)B(1)T(5)
H(1)＝p(1)C(1)T[C(1)p(1)C(1)T+R(1)]-1(6)
In equation (5), a (1) represents a functional relationship between input and output at this time, B (1) represents a system control matrix, equation (6) C (1) represents a measurement matrix, and R (1) represents a measurement noise covariance.
Then, an optimal estimation value is calculated, namely:
in the formula (7), y (1) represents an observed signal vector.
The mean square error matrix P (1) ([ I-H (1) C (1) ] P (1)) is refreshed, and P (1) can be obtained by taking the calculated P (1) and H (1) into an equation. Where I denotes an identity matrix.
Repeating the steps until the optimal estimation value at any time is obtained
Finally according to
And obtaining the output value of the rotating speed of the observation vector at each moment.
The method for suppressing the rotating speed noise based on the Kalman filtering can be operated in a rotating speed noise suppression module, and the module adopts a microcontroller, such as a single chip microcomputer, an ARM and the like. A memory within the microcontroller is to store executable instructions, and a processor within the microcontroller is configured to perform a kalman filter-based rotational speed noise suppression method via execution of the executable instructions.
As shown in fig. 5, a diesel engine speed control system according to an embodiment of the present invention includes: the PLC is connected with the input/output module, the diesel engine speed sensor, the lubricating oil pressure relay, the touch screen, the alarm module, the safety protection module and the like, the servo amplifier and the servo motor are connected through the high-speed optical fiber communication cable, and the motor is controlled to adjust the opening of the throttle valve so as to control the rotating speed of the diesel generating set to stably operate. The control system acquires a rotating speed signal of the diesel engine through the rotating speed sensor, the rotating speed controller adopts a control method combining Kalman filtering and PID, and the controller processes and calculates the acquired signal and then controls the servo system, so that the servo motor is controlled to adjust the opening of the throttle valve.
The pressure relay is used for detecting the pressure of the lubricating oil, and an alarm signal can be sent out when the system is abnormal. The PLC in the control system is also connected with a touch screen HMI which is a man-machine conversation interface, related parameter setting can be carried out through the touch screen, and information such as working conditions of the rotating speed control system can be displayed on the touch screen, so that the real-time monitoring of workers is facilitated.
As shown in fig. 6, which is a flow chart of the diesel engine rotating speed PID control based on kalman filtering, the rotating speed of the diesel generator set is compared with a given value, then a PID command is started and controlled according to the deviation of the speed, the system controls the motion of the throttle valve motor through calculation, and the kalman filter continues to process the output signal u after passing through the PLD controller and the rotating speed signal of the throttle valve motor, so as to finally realize the constant speed control of the diesel generator set.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and any simple modification, equivalent change and modification made to the above embodiment according to the technical spirit of the present invention are within the scope of the technical solution of the present invention.
Claims (4)
1. A rotating speed noise suppression method based on Kalman filtering is characterized by comprising the following steps:
inputting a rotating speed output signal n which is used for measuring noise V and is polluted by the noise into a Kalman filter, filtering, and inputting the signal into a rotating speed controller, wherein the filtering method of the Kalman filter comprises the following steps:
1) initial state x (0) of calculating rotation speed signal
The statistical properties of the initial state x (0) of the rotational speed signal are determined, assuming
According to
So p (0) ═ var [ x (0)](ii) a WhereinE represents an integer function, var represents the variance, and p (0) represents the estimated covariance value;
2) calculating an estimated covariance p (1) at the time when k is 1; updating the correction matrix H (1) at that moment
p(1)＝A(1)p(0)A(1)T+B(1)Q(0)B(1)T(1)
H(1)＝p(1)C(1)T[C(1)p(1)C(1)T+R(1)]-1(2)
In the formula (1), A (1) represents a functional relation between input and output at the moment, B (1) represents a system control matrix, C (1) represents a measurement matrix in the formula (2), and R (1) represents measurement noise covariance;
3) calculating the optimal estimated value of the moment when k is 1; refresh mean square error matrix P (1)
P(1)＝[I-H(1)C(1)]p(1)(4)
Y (1) in formula (3) represents an observed signal vector; carrying P (1) and H (1) obtained by calculating the formulas (1) and (2) into a formula (4) to obtain P (1), wherein I represents an identity matrix;
4) repeating the steps to obtain the optimal estimated value of k 1 and 2
5) According to
And obtaining the rotating speed output value at the k moment.
2. A rotational speed noise suppression module, characterized in that the module employs a microcontroller, a memory within the microcontroller being configured to store executable instructions, and a processor within the microcontroller being configured to execute the aforementioned kalman filter-based rotational speed noise suppression method via execution of the executable instructions.
3. The Kalman filtering based rotational speed noise suppression method according to claim 1, wherein the rotational speed controller adopts a PLC.
4. The Kalman filtering based rotational speed noise suppression method according to claim 1, characterized in that the rotational speed controller adopts a PID control method.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102427341A (en) * | 2011-11-22 | 2012-04-25 | 上海大学 | Transmission noise suppression method of remote iterative learning control system based on Kalman filtering |
| CN103166233A (en) * | 2013-03-13 | 2013-06-19 | 中冶南方工程技术有限公司 | Continuous time state estimation method based on Kalman-Bucy filter |
| US20140281779A1 (en) * | 2013-03-12 | 2014-09-18 | Raytheon Company | Iterative kalman filtering |
| CN105835721A (en) * | 2016-03-31 | 2016-08-10 | 电子科技大学 | Four-wheel hub electric vehicle speed control method |
| CN110987449A (en) * | 2019-12-13 | 2020-04-10 | 山东大学 | Electronic throttle opening estimation method and system based on Kalman filtering |
-
2020
- 2020-07-31 CN CN202010756773.8A patent/CN111852673A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102427341A (en) * | 2011-11-22 | 2012-04-25 | 上海大学 | Transmission noise suppression method of remote iterative learning control system based on Kalman filtering |
| US20140281779A1 (en) * | 2013-03-12 | 2014-09-18 | Raytheon Company | Iterative kalman filtering |
| CN103166233A (en) * | 2013-03-13 | 2013-06-19 | 中冶南方工程技术有限公司 | Continuous time state estimation method based on Kalman-Bucy filter |
| CN105835721A (en) * | 2016-03-31 | 2016-08-10 | 电子科技大学 | Four-wheel hub electric vehicle speed control method |
| CN110987449A (en) * | 2019-12-13 | 2020-04-10 | 山东大学 | Electronic throttle opening estimation method and system based on Kalman filtering |
Non-Patent Citations (1)
| Title |
|---|
| 李响: "基于推广卡尔曼滤波的永磁同步电机无位置传感器控制", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
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