CN110850715A - Anti-interference control method of singular perturbation system - Google Patents

Anti-interference control method of singular perturbation system Download PDF

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CN110850715A
CN110850715A CN201911098179.8A CN201911098179A CN110850715A CN 110850715 A CN110850715 A CN 110850715A CN 201911098179 A CN201911098179 A CN 201911098179A CN 110850715 A CN110850715 A CN 110850715A
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郭雷
谢一嘉
乔建忠
余翔
许昱涵
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Beihang University
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Abstract

The invention relates to an anti-interference control method of a singular perturbation system, aiming at the problem that a fast state variable and a slow state variable in the singular perturbation system respectively have fast-varying interference and slow-varying interference, firstly analyzing the interference of the system under a complex environment condition, and establishing a system model containing external interference; secondly, converting the system model into a singular perturbation system model according to a singular perturbation theory, and performing singular perturbation decomposition on the system to obtain a fast subsystem and a slow subsystem; thirdly, designing a disturbance observer for each subsystem respectively to realize accurate estimation of external disturbance; finally, designing a state feedback controller to realize accurate compensation of external interference and quick control of each subsystem; the invention has the characteristics of strong anti-interference capability, high control precision and high convergence speed, and can be used for high-precision and rapid control of aerospace singular perturbation systems such as satellites, unmanned planes, missiles and the like.

Description

Anti-interference control method of singular perturbation system
Technical Field
The invention relates to an anti-interference control method of a singular perturbation system, which aims at the problem that a fast state variable and a slow state variable in the singular perturbation system respectively have fast-varying interference and slow-varying interference, establishes a singular perturbation system model containing external fast-slow interference, realizes the estimation and compensation of interference and the improvement of system rapidity, and can be used for the high-precision rapid control of aerospace singular perturbation systems such as satellites, unmanned planes, missiles and the like.
Background
In the engineering fields of aerospace and the like, such as aircraft attitude control, and the modeling process of high-precision control of a multi-joint mechanical arm, a large number of small time constants, inertia, conductance or capacitance exist, so that the model has a quite high order, and numerical characteristics of pathological states appear in a differential equation. Early processing methods generally neglect these small-magnitude values directly to reach model reduction, i.e. neglect high frequency and only consider low frequency part, or do not consider the influence of small time constant, etc., and this simplified processing method makes the design effect often far from the expected requirement. Later, such systems were considered differential equations with small parameters, i.e., singular perturbation problems, where the parameters may occur naturally reflecting certain physical properties or may be introduced artificially. With the increasingly complex system structure and task requirements, the factors influencing the control accuracy and stability of the system are increasing, and the system is simultaneously influenced by internal interference such as model uncertainty, sensor noise and actuator deviation and external environment interference in the control process. Under the condition of multi-source interference influence, the precision of a control system still needs to be ensured, and great requirements are provided for the anti-interference capability of the controller.
In the existing control methods of the singular perturbation system, as proposed in patent application numbers 201811581068.8, 201810124039.2 and 201810124028.4, the control method based on the singular perturbation only considers the control problem under ideal conditions, does not consider the influence of the system on internal interference and external environment interference such as model uncertainty, sensor noise, actuator deviation and the like, and is difficult to ensure the control precision of the system. In view of this, the control accuracy of the conventional control method under the simultaneous influence of multi-source interference factors such as external interference, internal interference, modeling errors and the like is severely restricted, and a singular perturbation system control method with an anti-interference capability needs to be researched urgently.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the problem that a fast state variable and a slow state variable in a singular perturbation system respectively have fast-varying interference and slow-varying interference, the defects of the prior art are overcome, the anti-interference control method of the singular perturbation system is provided, the problems of fast and slow interference estimation and compensation of the singular perturbation system are solved, and the accuracy and the rapidity of the system are improved.
The technical solution of the invention is as follows: an anti-interference control method of a singular perturbation system is characterized by comprising the following steps:
firstly, analyzing the interference of a system under a complex environment condition, and establishing a system model containing external interference; secondly, converting the system model into a singular perturbation system according to a singular perturbation theory, and performing singular perturbation decomposition on the system to obtain a fast subsystem and a slow subsystem; thirdly, designing a disturbance observer to estimate and compensate external fast and slow disturbance respectively; finally, designing a state feedback controller to realize accurate and rapid control on the subsystem; the method comprises the following specific steps:
firstly, establishing a system model containing external interference, and writing a state space expression as follows:
Figure BDA0002269010040000021
wherein x is a system state variable and x is a system state variable,
Figure BDA0002269010040000022
representing the first derivative of the state variable x with respect to time, u the control input, d the external disturbance, a, B the coefficient matrix of known dimensions.
Secondly, transforming the original system model, and establishing a standard singular perturbation system model as follows:
Figure BDA0002269010040000023
wherein x is1A slow state variable representing the system is shown,representing the first derivative of the slow state variable with respect to time, x2A fast state variable representing the system is shown,
Figure BDA0002269010040000025
representing the first derivative of the fast state variable with respect to time, 0<μ<1 denotes the perturbation parameter, y denotes the system output, A11,A12,A21,A22,B1,B2,C1,C2And obtaining a coefficient matrix of the singular perturbation system according to the coefficient matrix of the system, wherein the dimension is known. Singular perturbation decomposition is carried out on the system, and the obtained slow subsystem is as follows:
Figure BDA0002269010040000031
wherein the content of the first and second substances,
Figure BDA0002269010040000032
Figure BDA0002269010040000033
xsrepresenting the state variable of the slow subsystem, ysRepresents the slow subsystem output, usRepresenting slow subsystem control inputs, dsRepresents slow subsystem interference, represented by the following model:
Figure BDA0002269010040000034
wherein, wsFor the state variables of the slow subsystem external disturbance model,
Figure BDA0002269010040000035
denotes wsFirst derivative with respect to time, V1，W1Is a matrix of known coefficients. The express subsystem is as follows:
Figure BDA0002269010040000036
wherein x isfRepresenting the state variable of the fast subsystem, ufIndicating a fast subsystem control input, yfThe output of the fast subsystem is represented,
Figure BDA0002269010040000037
dfexpress the fast subsystem interference, expressed by the following model:
Figure BDA0002269010040000038
wherein, wfFor the state variables of the external disturbance model of the fast subsystem,
Figure BDA0002269010040000039
denotes wfFirst derivative with respect to time, V2，W2Is a matrix of known coefficients.
And thirdly, designing interference observers respectively aiming at the interference in the fast and slow subsystems obtained in the second step, and estimating and compensating the interference in the fast and slow subsystems.
Aiming at external interference in the fast subsystem, designing an interference observer to estimate the external interference in real time and obtaining an estimated value
Figure BDA00022690100400000310
Further obtaining interference estimation error of the fast subsystem Is wfIs determined by the estimated value of (c),
Figure BDA00022690100400000313
to representFirst derivative with respect to time, LfIs the observer gain.
Figure BDA0002269010040000041
The observer design is carried out on the slow subsystem in the same way,
Figure BDA0002269010040000042
wherein the content of the first and second substances,
Figure BDA0002269010040000043
is an estimate of the state variable in the disturbance model outside the slow subsystem,
Figure BDA0002269010040000044
to representThe first derivative with respect to time is,
Figure BDA0002269010040000046
is an estimate of the external interference of the slow subsystem, LsIs the observer gain. Is provided with
Figure BDA0002269010040000047
Indicating the estimation error.
And fourthly, compensating the interference according to the interference observer designed in the third step, and designing a state feedback controller to realize accurate and quick control of the system.
The fast subsystem control law is designed as
Figure BDA0002269010040000048
Wherein KfRepresenting a state feedback controller gain array. The law of control of the slow subsystem is designed by the same theoryWherein KsPresentation formAnd a state feedback controller gain array.
Fifthly, solving the gain matrix
For the fast subsystem, the controller gain matrix KfAnd observer gain matrix LfThe following conditions should be satisfied:
wherein the symbol sym (X) denotes the matrix X with its own transpose XTSum, Qf,Pf2,Rf1,Rf2Is a positively determined symmetric matrix, then
Figure BDA00022690100400000411
The gain conditions of the slow subsystem obtained by the same method are as follows:
Figure BDA00022690100400000412
wherein Q iss,Ps2,Rs1,Rs2Is a positively determined symmetric matrix, then
Figure BDA00022690100400000413
Compared with the prior art, the invention has the advantages that:
according to the anti-interference control method of the singular perturbation system, the singular perturbation theory is adopted to carry out singular perturbation decomposition on the system aiming at the problem that the state variables of the system have inconsistent change speeds, so that the accuracy and the rapidity of the control system are improved; meanwhile, aiming at the problem that the fast state variable and the slow state variable respectively have fast-varying interference and slow-varying interference, interference observers are respectively designed to estimate and compensate the interference, and the robustness and the reliability of the system are improved, so that the high-precision and fast control of the system is realized.
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FIG. 1 is a design flow chart of an anti-interference control method of a singular perturbation system.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. As shown in fig. 1, the specific implementation steps of the present invention are as follows (taking a certain attitude pilot system as an example):
1. establishing a system model containing external interference, and writing a state space expression as follows:
Figure BDA0002269010040000051
wherein x ═ γ v θ q]TIn order to be in the state of the system,
Figure BDA0002269010040000055
denotes the first derivative of x with respect to time, gamma denotes the displacement in the direction of the velocity, and V denotes the normalized velocity increment V ═ V (V-V)0)/V0Theta represents pitch angle increment, q represents pitch angle rate, u is system control input, d is system external interference, and y represents system output. Coefficient matrix
Figure BDA0002269010040000052
C＝[0 0 0 1]Initial value of x
Figure BDA0002269010040000053
2. And (3) converting the system model to obtain a standard singular perturbation system model as follows:
wherein x is1A slow state variable representing the system is shown,
Figure BDA0002269010040000061
representing the first derivative of the slow state variable with respect to time, x2A fast state variable representing the system is shown,representing fast state variables versus timeAnd y represents the system output. Perturbation parameter mu is 0.1, coefficient matrix
Figure BDA0002269010040000063
Figure BDA0002269010040000064
C1＝[01]，C2＝[1 1]。
Singular perturbation decomposition is carried out on the system, and the obtained slow subsystem is as follows:
wherein the content of the first and second substances,
Figure BDA0002269010040000066
Cs＝[0 1]，Ds＝0.001，xsrepresenting the state variable of the slow subsystem, ysRepresents the slow subsystem output, usRepresenting slow subsystem control inputs, dsRepresents slow subsystem interference, represented by the following model:
Figure BDA0002269010040000067
wherein, wsFor the state variables of the slow subsystem external disturbance model,denotes wsFirst derivative with respect to time, coefficient matrix V1＝[0 1]，
Figure BDA0002269010040000069
The express subsystem is as follows:
Figure BDA00022690100400000610
wherein x isfRepresenting the state variable of the fast subsystem, ufIndicating a fast subsystem control input, yfExpress the fast subsystem to outputAnd then the mixture is discharged out of the furnace,
Figure BDA00022690100400000611
dfexpress the fast subsystem interference, expressed by the following model:
Figure BDA0002269010040000071
wherein, wfFor the state variables of the external disturbance model of the fast subsystem,
Figure BDA0002269010040000072
denotes wfFirst derivative with respect to time, coefficient matrix V2＝[0 5]，
Figure BDA0002269010040000073
3. Constructing a fast subsystem interference observer as follows:
wherein the content of the first and second substances,in order to estimate the interference of the fast sub-system,
Figure BDA0002269010040000076
is wfIs determined by the estimated value of (c),
Figure BDA0002269010040000077
to represent
Figure BDA0002269010040000078
For time first derivative, fast subsystem interference estimation error
Figure BDA0002269010040000079
LfIs the observer gain. The slow subsystem disturbance observer is designed as follows:
Figure BDA00022690100400000710
wherein the content of the first and second substances,is wsIs determined by the estimated value of (c),
Figure BDA00022690100400000712
to represent
Figure BDA00022690100400000713
The first derivative with respect to time is,
Figure BDA00022690100400000714
is an estimate of the external interference of the slow subsystem, LsIn order to obtain the gain of the slowest system observer,indicating the estimation error.
4. Separately designing state feedback control law compensation interference
The fast subsystem control law is
Figure BDA00022690100400000716
The slow subsystem control law is
Figure BDA00022690100400000717
Wherein Kf，KsIs the controller gain.
5. Solving the gain matrix, we can obtain:
Kf＝[999.9749 6.9975]，
Figure BDA00022690100400000718
Ks＝[7242.4 -24.5]，
Figure BDA00022690100400000719
those skilled in the art will appreciate that the invention may be practiced without these specific details.

Claims (6)

1. An anti-interference control method of a singular perturbation system is characterized by comprising the following steps:
step 1: establishing a system model containing external interference for the external interference of a system under a complex environment condition;
step 2: converting the system model into a singular perturbation system model according to a singular perturbation theory, and performing singular perturbation decomposition on the singular perturbation system model to obtain a fast subsystem and a slow subsystem in the singular perturbation system;
and step 3: respectively designing an interference observer to estimate and compensate the interference of the fast subsystem and the slow subsystem;
and 4, step 4: and designing a state feedback controller to realize accurate and rapid control on the fast subsystem and the slow subsystem, thereby finishing the anti-interference control of the singular perturbation system.
2. The singular perturbation system anti-interference control method according to claim 1, wherein: the step 1 is specifically realized as follows:
establishing a system model containing external interference, and writing a state space expression as follows:
Figure FDA0002269010030000011
wherein x is a system state variable and x is a system state variable,
Figure FDA0002269010030000012
the first derivative of the state variable x with respect to time is represented, u is the control input, d is the external disturbance, and a, B are the system coefficient matrices of known dimensions.
3. The singular perturbation system anti-interference control method according to claim 1, wherein: the step 2 is specifically realized as follows:
converting the system model, and establishing a singular perturbation system model as follows:
Figure FDA0002269010030000013
wherein x is1A slow state variable is represented which is,
Figure FDA0002269010030000014
representing the first derivative of the slow state variable with respect to time, x2A fast state variable is represented that is,representing the first derivative of the fast state variable with respect to time, 0<μ<1 denotes the perturbation parameter, y denotes the output, A11,A12,A21,A22,B1,B2,C1,C2Obtaining a singular perturbation system coefficient matrix according to the system coefficient matrix, wherein the dimensionality is known;
singular perturbation decomposition is carried out to obtain a slowness subsystem as follows:
Figure FDA0002269010030000021
wherein the content of the first and second substances,
Figure FDA0002269010030000022
Figure FDA0002269010030000023
xsrepresenting the state variable of the slow subsystem, ysRepresents the slow subsystem output, usRepresenting slow subsystem control inputs, dsIndicating slow subsystem interference, dsRepresented by the following model:
Figure FDA0002269010030000024
wherein, wsFor the state variables of the slow subsystem external disturbance model,
Figure FDA0002269010030000025
denotes wsFirst derivative with respect to time, V1，W1Is a known coefficient matrix;
the express subsystem is as follows:
Figure FDA0002269010030000026
wherein x isfRepresenting the state variable of the fast subsystem, ufIndicating a fast subsystem control input, yfThe output of the fast subsystem is represented,
Figure FDA0002269010030000027
dfexpress the fast subsystem interference, expressed by the following model:
Figure FDA0002269010030000028
wherein, wfFor the state variables of the external disturbance model of the fast subsystem,
Figure FDA0002269010030000029
denotes wfFirst derivative with respect to time, V2，W2Is a matrix of known coefficients.
4. The singular perturbation system anti-interference control method according to claim 1, wherein: in the step 3, interference observers are respectively designed for the interference in the fast and slow subsystems obtained in the step 2, and the interference of the fast and slow subsystems is estimated and compensated;
aiming at external interference in the fast subsystem, designing an interference observer to estimate the external interference in real time and obtaining an estimated value
Figure FDA00022690100300000210
Further obtaining interference estimation error of the fast subsystem
Figure FDA00022690100300000211
Figure FDA00022690100300000212
Is wfIs determined by the estimated value of (c),to represent
Figure FDA0002269010030000032
First derivative with respect to time, LfFor observer gain, the fast subsystem disturbance observer is of the form:
Figure FDA0002269010030000033
the derivative of the fast subsystem interference estimation error is:
Figure FDA0002269010030000034
the observer design is carried out on the slow subsystem in the same way,
Figure FDA0002269010030000035
wherein the content of the first and second substances,
Figure FDA0002269010030000036
is an estimate of the state variable in the disturbance model outside the slow subsystem,to represent
Figure FDA0002269010030000038
The first derivative with respect to time is,
Figure FDA0002269010030000039
is an estimate of the external interference of the slow subsystem, LsThe gain of the observer to be determined. Is provided with
Figure FDA00022690100300000310
Representing the interference estimation error of the slow subsystem, the derivative of the interference estimation error of the slow subsystem is:
Figure FDA00022690100300000311
5. the singular perturbation system anti-interference control method according to claim 1, wherein: in the step 4, the state feedback controller is designed to realize the following accurate and rapid control of the system:
the fast subsystem control law is designed as
Figure FDA00022690100300000312
Wherein KfRepresenting a gain array of a feedback controller in a pending state; the slow subsystem control law is designed as
Figure FDA00022690100300000313
Wherein KsRepresenting the gain array of the feedback controller in a pending state.
6. The anti-interference control method of the singular perturbation system according to claim 5, wherein: the method for selecting the gain matrix of the disturbance observer and the state feedback controller comprises the following steps:
for the fast subsystem, the controller gain matrix KfAnd observer gain matrix LfThe following conditions should be satisfied:
Figure FDA00022690100300000314
wherein the symbol sym (X) denotes the matrix X with its own transpose XTSum, Qf,Pf2,Rf1,Rf2Is a positively determined symmetric matrix, then
Figure FDA0002269010030000041
The slow subsystem gain matrix should satisfy the following conditions:
wherein Q iss,Ps2,Rs1,Rs2Is a positively determined symmetric matrix, then
Figure FDA0002269010030000043
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111855192A (en) * 2020-07-31 2020-10-30 北京航空航天大学 Singular value decomposition method for denoising encoder signal
CN114967457A (en) * 2022-05-27 2022-08-30 北京计算机技术及应用研究所 Model-based event trigger control stability method of singular perturbation system
CN116027809A (en) * 2023-02-07 2023-04-28 中国矿业大学 Multi-quad-rotor unmanned aerial vehicle formation control method under DoS attack

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102298390A (en) * 2011-06-24 2011-12-28 北京航空航天大学 Anti-disturbance flexible spacecraft attitude and vibration composite control method
CN103558857A (en) * 2013-11-14 2014-02-05 东南大学 Distributed composite anti-interference attitude control method of BTT flying machine
CN108303889A (en) * 2018-02-07 2018-07-20 中国航空工业集团公司西安飞机设计研究所 A kind of time-scale separation aircraft elasticity body controlling means based on nonlinear transformations
CN108333939A (en) * 2018-02-07 2018-07-27 中国航空工业集团公司西安飞机设计研究所 A kind of time-scale separation aircraft elastomer intelligent control method based on neural network
KR20180093331A (en) * 2017-02-13 2018-08-22 인하대학교 산학협력단 Method for stabilization of nonlinear system including singular perturbation
CN109514558A (en) * 2018-12-24 2019-03-26 中国航空工业集团公司西安飞机设计研究所 Flexible mechanical arm time-scale separation robust control method based on singular perturbation
CN110221539A (en) * 2019-05-17 2019-09-10 江苏理工学院 Quadrotor non-singular terminal sliding-mode control based on linear expansion observer
CN110361973A (en) * 2019-07-15 2019-10-22 南京信息工程大学 A kind of fault tolerant control method of time lag singular perturbation system

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102298390A (en) * 2011-06-24 2011-12-28 北京航空航天大学 Anti-disturbance flexible spacecraft attitude and vibration composite control method
CN103558857A (en) * 2013-11-14 2014-02-05 东南大学 Distributed composite anti-interference attitude control method of BTT flying machine
KR20180093331A (en) * 2017-02-13 2018-08-22 인하대학교 산학협력단 Method for stabilization of nonlinear system including singular perturbation
CN108303889A (en) * 2018-02-07 2018-07-20 中国航空工业集团公司西安飞机设计研究所 A kind of time-scale separation aircraft elasticity body controlling means based on nonlinear transformations
CN108333939A (en) * 2018-02-07 2018-07-27 中国航空工业集团公司西安飞机设计研究所 A kind of time-scale separation aircraft elastomer intelligent control method based on neural network
CN109514558A (en) * 2018-12-24 2019-03-26 中国航空工业集团公司西安飞机设计研究所 Flexible mechanical arm time-scale separation robust control method based on singular perturbation
CN110221539A (en) * 2019-05-17 2019-09-10 江苏理工学院 Quadrotor non-singular terminal sliding-mode control based on linear expansion observer
CN110361973A (en) * 2019-07-15 2019-10-22 南京信息工程大学 A kind of fault tolerant control method of time lag singular perturbation system

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
NIKOLAOS KAZANTZIS，ET AL.: "Nonlinear observer design for the slow states of a singularly perturbed system", 《COMPUTERS & CHEMICAL ENGINEERING》 *
刘蕾等: "基于PI观测器的奇异摄动系统故障诊断和最优容错控制", 《控制与决策》 *
张伟江等: "奇异摄动线性控制系统的能观性和能抗干扰性", 《数学研究与评论》 *
梅平: "奇异摄动系统的鲁棒控制", 《中国博士学位论文全文数据库信息科技辑》 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111855192A (en) * 2020-07-31 2020-10-30 北京航空航天大学 Singular value decomposition method for denoising encoder signal
CN111855192B (en) * 2020-07-31 2021-04-23 北京航空航天大学 Singular value decomposition method for denoising encoder signal
CN114967457A (en) * 2022-05-27 2022-08-30 北京计算机技术及应用研究所 Model-based event trigger control stability method of singular perturbation system
CN116027809A (en) * 2023-02-07 2023-04-28 中国矿业大学 Multi-quad-rotor unmanned aerial vehicle formation control method under DoS attack
CN116027809B (en) * 2023-02-07 2023-07-18 中国矿业大学 Multi-quad-rotor unmanned aerial vehicle formation control method under DoS attack

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