CN116430847A - Double-unmanned-vehicle dynamic track tracking and obstacle avoidance self-adaptive robust control method - Google Patents

Double-unmanned-vehicle dynamic track tracking and obstacle avoidance self-adaptive robust control method Download PDF

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CN116430847A
CN116430847A CN202310196288.3A CN202310196288A CN116430847A CN 116430847 A CN116430847 A CN 116430847A CN 202310196288 A CN202310196288 A CN 202310196288A CN 116430847 A CN116430847 A CN 116430847A
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constraint
obstacle avoidance
vehicle
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tracking
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孙芹芹
王修业
吴子潇
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Nanjing University of Science and Technology
Nanjing University of Aeronautics and Astronautics
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Nanjing University of Science and Technology
Nanjing University of Aeronautics and Astronautics
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    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
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Abstract

The invention discloses a double unmanned vehicle track tracking and obstacle avoidance self-adaptive robust control method, which comprises the following steps: step 1), establishing a unified unmanned vehicle dynamics model of a reconnaissance vehicle and a rescue vehicle; step 2), establishing a mathematical model of target arrival constraint required by the reconnaissance vehicle, track tracking constraint required by the rescue vehicle and obstacle avoidance constraint according to the control target; step 3), analyzing the mathematical model of the arrival constraint, the track constraint and the obstacle avoidance constraint established in the step 2) based on the constraint following theory, and constructing a constraint following error as a control object of the controller design; step 4), determining a function for comprehensively describing an uncertainty limit value of the system based on the unmanned vehicle dynamics model established in the step 1), and constructing an adaptive law and adaptive robust controller by combining a mathematical model and constraint tracking errors. The invention can solve the problems of target arrival of the reconnaissance vehicle, track tracking of the rescue vehicle and obstacle avoidance in the double-unmanned-vehicle system and has excellent control performance.

Description

Double-unmanned-vehicle dynamic track tracking and obstacle avoidance self-adaptive robust control method
Technical Field
The invention relates to the field of mechanical system dynamics and control, in particular to a dynamic track tracking and obstacle avoidance self-adaptive robust control method for double unmanned vehicles.
Background
Along with the intelligent development of unmanned platform technology, the unmanned platform plays a very important role in the process of executing various tasks. In the existing researches, most researches on a mobile control algorithm are relatively one-sided, and only the problems of tracking a route, planning the route and the like or the problem of avoiding obstacle targets are considered. However, in actual situations, the unmanned vehicle arrives at a specified target, the control targets of track tracking and obstacle avoidance may be time-varying and simultaneous, and many conventional control methods at present cannot meet the performance requirements due to the existence of model errors, measurement errors, friction and other interference factors, which are interfered by various uncertainty factors in the unmanned vehicle control process. The self-adaptive robust control method for the dynamic track tracking and obstacle avoidance of the double unmanned vehicles is designed by introducing constraint following theory, the reconnaissance vehicle is responsible for detecting the path and the obstacle, and the rescue vehicle performs track tracking and obstacle avoidance behaviors, so that the self-adaptive robust control method has higher flexibility, higher control precision and excellent robustness under the interference of time-varying uncertainty.
Disclosure of Invention
The invention aims to provide a self-adaptive robust control method for tracking dynamic tracks and avoiding barriers of double unmanned vehicles.
The technical scheme for realizing the purpose of the invention is as follows: a dynamic track tracking and obstacle avoidance self-adaptive robust control method for double unmanned vehicles comprises the following steps:
step 1), establishing a unified unmanned vehicle dynamics model of a reconnaissance vehicle and a rescue vehicle based on a Lagrange modeling method;
step 2), establishing a mathematical model of target arrival constraint required by the scout vehicle, track tracking constraint and obstacle avoidance constraint required by the rescue vehicle according to the control target, and expressing the mathematical model in a form of first-order constraint and second-order constraint;
step 3), analyzing the mathematical model of the arrival constraint, the track constraint and the obstacle avoidance constraint established in the step 2) based on the constraint following theory, and constructing a constraint following error as a control object of the controller design;
step 4), determining a function for comprehensively describing an uncertainty limit value of the system based on the unmanned vehicle dynamics model established in the step 1), and constructing an adaptive law and adaptive robust controller by combining the constraint matrix and the constraint vector obtained in the step 2) and the constraint tracking error constructed in the step 3);
further, based on the Lagrange modeling method, a unified unmanned vehicle dynamics model of the reconnaissance vehicle and the rescue vehicle is built, and the model specifically comprises the following steps:
Figure BDA0004107348500000021
wherein the method comprises the steps of
Figure BDA0004107348500000022
Is uncertainty, t represents time, q (t) ∈R n Representing coordinates, which are a function of time,
Figure BDA0004107348500000023
speed and acceleration, respectively, M (q, sigma, t) is the inertial matrix, +.>
Figure BDA0004107348500000024
Is the Coriolis centrifugal force, G (q, sigma, t) is gravity, +.>
Figure BDA0004107348500000025
Is friction and other external interference, τ∈R n Is the control input torque, for the sake of simplified writing, used hereinafter +.>
Figure BDA0004107348500000026
Can replace the representation +.>
Figure BDA0004107348500000027
For the uncertainty handling problem of the system, the model is decomposed, and the dynamics model is decomposed into a nominal part and an uncertainty part:
Figure BDA0004107348500000028
Figure BDA0004107348500000029
Figure BDA00041073485000000210
Figure BDA00041073485000000211
wherein the method comprises the steps of
Figure BDA00041073485000000212
Is a nominal moiety, ΔM (·), ΔC (·), ΔG (·), ΔF (·) is an uncertainty moiety.
Further, in step 2), according to the control target, a mathematical model of target arrival constraint required by the scout vehicle, track tracking constraint and obstacle avoidance constraint required by the rescue vehicle is established, and expressed in a form of first-order constraint and second-order constraint, specifically:
(1) Arrival constraints of the scout car:
defining a mathematical model of the arrival constraints:
e 1 (t):＝H 2 (q(t))-s 2 ，
wherein:
Figure BDA00041073485000000213
e 1 (t) is a mathematical model of the arrival constraints, q (t) is the scout coordinates,
Figure BDA00041073485000000214
for reaching the target reference point coordinates, s is the radius of the target reaching area;
derivative, get the mathematical model reaching the first order servo constraint:
Figure BDA0004107348500000031
wherein l is a constant and l > 0;
solving the second derivative to obtain a mathematical model reaching the second-order servo constraint:
Figure BDA0004107348500000032
thereby obtaining an arrival constraint matrix:
Figure BDA0004107348500000033
arrival constraint vector:
c 1 (q(t))＝ls 2 -lH(q(t))，
Figure BDA0004107348500000034
(2) Track tracking constraint of rescue vehicle:
mathematical models defining trajectory tracking constraints:
e 2 (t)＝q 2 (t)-q 1 (t)，
wherein e 2 (t) is a mathematical model of trajectory tracking constraints, q 1 (t) is the coordinate of the track of the scout car, q 2 (t) is the coordinates of the rescue vehicle;
deriving to obtain a mathematical model of the first-order constraint of the track tracking:
Figure BDA0004107348500000035
solving the second derivative to obtain a mathematical model of the track tracking second-order constraint:
Figure BDA0004107348500000036
thereby obtaining a track tracking constraint matrix:
A 2 (q(t))＝[1 1]；
trajectory tracking constraint vector:
Figure BDA0004107348500000037
Figure BDA0004107348500000038
(3) Obstacle avoidance constraint of rescue vehicle:
defining a mathematical model of obstacle avoidance constraints:
e 3 (t)＝ln(k-f)，
wherein:
f＝||q(t)-q 0 ||，
e 3 (t) is a mathematical model of obstacle avoidance constraint, q (t) is the coordinates of the rescue vehicle, q 0 Is the obstacle coordinates, k is the radius of the safety range;
deriving to obtain a mathematical model of obstacle avoidance first-order constraint:
Figure BDA0004107348500000041
obtaining a mathematical model of obstacle avoidance second-order constraint by solving the second derivative:
Figure BDA0004107348500000042
thereby obtaining an obstacle avoidance constraint matrix:
Figure BDA0004107348500000043
obstacle avoidance constraint vector:
c 3 (q(t))＝0，
Figure BDA0004107348500000044
further, step 3), analyzing the mathematical model of the arrival constraint, the track constraint and the obstacle avoidance constraint established in step 2) based on the constraint following theory, and constructing a constraint following error as a control object of the controller design, wherein the specific method comprises the following steps:
constructing a constraint following error of the arrival constraint:
Figure BDA0004107348500000045
constructing a constraint following error of a track tracking constraint:
Figure BDA0004107348500000046
constructing a constraint following error of obstacle avoidance constraint:
Figure BDA0004107348500000047
follow-up error beta including arrival constraints 1 Constrained following error beta for trajectory tracking 2 And following error beta of obstacle avoidance constraint 3 Is:
β＝[β 1 ,β 2 ,β 3 ] T 。
further, in step 4), based on the unmanned vehicle dynamics model established in step 1), a function for comprehensively describing an uncertainty limit value of the system is determined, and an adaptive law and adaptive robust controller is constructed by combining the constraint matrix and the constraint vector obtained in step 2) and the constraint tracking error constructed in step 3), wherein the specific method comprises the following steps:
based on the unmanned vehicle dynamics model in the step 1), the uncertainty is analyzed, the general form of an uncertainty parameter sigma is determined, scaling transformation is carried out through the following inequality, and a function pi (°) for comprehensively describing the uncertainty limit value of the system is obtained:
Figure BDA0004107348500000051
wherein the method comprises the steps of
Figure BDA0004107348500000052
Where α is the uncertainty variable in the function pi (·), κ is the control gain, P is the transfer matrix, ρ E > -1 is a constant, A is the constraint matrix in the synthesis step 2), expressed as A= [ A ] 1 (q)，A 2 (q)，A 3 (q)] T C is a constraint vector combining the two constraints, denoted as c= [ c ] 1 (q)，c 2 (q),c 3 (q)] T ；
Figure BDA0004107348500000053
Figure BDA0004107348500000054
(·) -1 Representing the inverse of the matrix, (. Cndot.) T Representing a transpose of the matrix;
based on the constraint following error beta of the comprehensive three constraints constructed in the step 2) and the function pi (-) constructed in the step, constructing an adaptive law capable of self-evaluating the uncertainty variable alpha:
Figure BDA0004107348500000055
wherein the method comprises the steps of
Figure BDA0004107348500000056
Is an estimate of alpha, < >>
Figure BDA0004107348500000057
k 1 ，k 2 > 0 is a design parameter.
The following adaptive Lu Banglu stick controller was designed:
Figure BDA0004107348500000058
wherein the method comprises the steps of
Figure BDA0004107348500000061
Has been written out in this step, +.>
Figure BDA0004107348500000062
Is as follows
Figure BDA0004107348500000063
Wherein the method comprises the steps of
Figure BDA0004107348500000064
Figure BDA0004107348500000065
Wherein, xi > 0 is a constant.
The invention also provides computer equipment, which comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor realizes the method to carry out double-unmanned vehicle dynamic track tracking and obstacle avoidance self-adaptive robust control when executing the computer program.
Compared with the prior art, the invention has the remarkable characteristics that: 1) The method is characterized by providing a double unmanned vehicle task execution concept, wherein a reconnaissance vehicle is responsible for detection, and a rescue vehicle is used for dynamic track tracking and obstacle avoidance; 2) Converting the target arrival of the reconnaissance vehicle, the track tracking of the rescue vehicle and the obstacle avoidance control target into meeting of target arrival constraint, track tracking constraint and obstacle avoidance constraint, and taking constraint following error as a control object of the designed controller; 3) The unmanned vehicle dynamic model is divided into two parts for consideration, so that a plurality of uncertainty factors faced by the unmanned vehicle in work can be dealt with, a corresponding self-adaptive robust controller is designed, the capacity of the unmanned vehicle for resisting interference is enhanced, and the unmanned vehicle has excellent control performance.
Drawings
Fig. 1 is a constraint following error effect diagram of a scout vehicle arrival constraint of the double unmanned vehicle dynamic track tracking and obstacle avoidance adaptive robust control method.
Fig. 2 is a constraint following error effect diagram of a rescue vehicle track tracking constraint of the double unmanned vehicle dynamic track tracking and obstacle avoidance self-adaptive robust control method.
Fig. 3 is a constraint following error effect diagram of a rescue vehicle obstacle avoidance constraint of the double unmanned vehicle dynamic track tracking and obstacle avoidance self-adaptive robust control method.
Fig. 4 is a graph of the effect of coordinate errors of the adaptive robust control method for tracking and avoiding obstacle for the dynamic track of the double unmanned vehicles.
Fig. 5 is a motion track effect diagram of a scout vehicle and a rescue vehicle of the double unmanned vehicle motion track tracking and obstacle avoidance adaptive robust control method.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The invention provides a double-unmanned-vehicle dynamic track tracking and obstacle avoidance self-adaptive robust control method, which comprises the following steps:
step 1), establishing a unified unmanned vehicle dynamics model of a reconnaissance vehicle and a rescue vehicle based on a Lagrange modeling method:
Figure BDA0004107348500000071
wherein the method comprises the steps of
Figure BDA0004107348500000072
Is uncertainty, t represents time, q (t) ∈R n Representing coordinates, which are a function of time,
Figure BDA0004107348500000073
speed and acceleration, respectively, M (q, sigma, t) is the inertial matrix, +.>
Figure BDA0004107348500000074
Is the Coriolis centrifugal force, G (q, sigma, t) is gravity, +.>
Figure BDA0004107348500000075
Is friction and other external interference, τ∈R n Is a control input, for the sake of simplified writing, hereinafter +.>
Figure BDA0004107348500000076
Replace->
Figure BDA0004107348500000077
For the uncertainty handling problem of the system, the model is decomposed, and the dynamics model is decomposed into a nominal part and an uncertainty part:
Figure BDA0004107348500000078
Figure BDA0004107348500000079
Figure BDA00041073485000000710
Figure BDA00041073485000000711
wherein the method comprises the steps of
Figure BDA00041073485000000712
Is a nominal moiety, ΔM (·), ΔD (·), ΔG (·), ΔF (·) is an uncertainty moiety.
In order to facilitate the design of the subsequent controller, the following definitions are made:
Figure BDA00041073485000000713
Figure BDA00041073485000000714
wherein ( -1 Representing the inverse matrix.
Step 2), establishing a mathematical model of target arrival constraint required by the scout vehicle, track tracking constraint and obstacle avoidance constraint required by the rescue vehicle according to the control target, and expressing the mathematical model in a form of first-order constraint and second-order constraint;
based on the unmanned vehicle dynamics model established in the step 1), analyzing the moving target which needs to be completed, wherein the moving target comprises track tracking and obstacle avoidance actions in the way of the reconnaissance vehicle reaching the designated position and the rescue vehicle, and carrying out mathematic on the moving target.
First defining a mathematical model of the scout vehicle arrival constraint:
e 1 (t):＝H 2 (q(t))-s 2 ，
wherein:
Figure BDA0004107348500000081
e 1 (t) is a mathematical model of the arrival constraints of the scout vehicle, q (t) is the scout vehicle coordinates,
Figure BDA0004107348500000082
to reach the target reference point coordinates, s is the half of the target reach areaDiameter is as follows;
derivative, get the mathematical model reaching the first-order constraint:
Figure BDA0004107348500000083
wherein l is a constant and l > 0;
solving the second derivative to obtain a mathematical model reaching the second constraint:
Figure BDA0004107348500000084
thereby obtaining an arrival constraint matrix:
Figure BDA0004107348500000085
arrival constraint vector:
c 1 (q(t))＝ls 2 -lH(q(t))，
Figure BDA0004107348500000086
next, a mathematical model of the rescue vehicle trajectory tracking constraint is defined:
e 2 (t)＝q 2 (t)-q 1 (t)，
wherein e 2 (t) is a mathematical model of trajectory tracking constraints, q 1 (t) is the coordinate of the track of the scout car, q 2 (t) is the coordinates of the rescue vehicle;
deriving to obtain a mathematical model of the first-order constraint of the track tracking:
Figure BDA0004107348500000091
solving the second derivative to obtain a mathematical model of the track tracking second-order constraint:
Figure BDA0004107348500000092
thereby obtaining a track tracking constraint matrix:
A 2 (q(t))＝[1 1]；
trajectory tracking constraint vector:
Figure BDA0004107348500000093
Figure BDA0004107348500000094
and then defining a mathematical model of obstacle avoidance constraint of the rescue vehicle:
e 3 (t)＝ln(k-f)；
wherein:
f＝||q(t)-q 0 ||，
e 3 (t) is a mathematical model of obstacle avoidance constraint, q (t) is the coordinates of the rescue vehicle, q 0 Is the obstacle coordinates, k is the radius of the safety range;
deriving to obtain a mathematical model of obstacle avoidance first-order servo constraint:
Figure BDA0004107348500000096
obtaining a mathematical model of obstacle avoidance second-order servo constraint by solving the second derivative:
Figure BDA0004107348500000097
thereby obtaining an obstacle avoidance constraint matrix:
Figure BDA0004107348500000098
obstacle avoidance constraint vector:
c 3 (q(t))＝0，
Figure BDA0004107348500000099
and 3, analyzing the mathematical model of the arrival constraint, the track constraint and the obstacle avoidance constraint established in the step 2) based on the constraint following theory, and constructing a constraint following error as a control object of the controller design.
Defining a constraint following error:
Figure BDA0004107348500000101
thereby deriving a constraint following error to reach the constraint:
Figure BDA0004107348500000102
constraint following error of trajectory tracking constraint:
Figure BDA0004107348500000103
constraint following error of obstacle avoidance constraint:
Figure BDA0004107348500000104
follow-up error beta including arrival constraints 1 Constrained following error beta for trajectory tracking 2 And following error beta of obstacle avoidance constraint 3 Is:
β＝[β 1 ,β 2 ,β 3 ] T 。
step 4, analyzing uncertainty (model uncertainty, external interference and the like) of the unmanned vehicle dynamics model established in the step 1) based on the unmanned vehicle dynamics model, determining a general form of an uncertainty parameter sigma, and performing scaling transformation through the following inequality to obtain a function pi (·) capable of comprehensively describing a system uncertainty limit value:
Figure BDA0004107348500000105
wherein:
Figure BDA0004107348500000106
where α is the uncertainty variable in the function pi (·), κ is the value of the control gain, P is the transfer matrix, ρ E > -1 is constant, A is A obtained in the synthesis step 2 1 (q)，A 2 (q) and A 3 (q) constraint matrix, denoted as a= [ a ] 1 (q)，A 2 (q)，A 3 (q)] T C is the c obtained in the synthesis step 2 1 (q)，c 2 (q) and c 3 Constraint vector of (q), denoted as c= [ c ] 1 (q)，c 2 (q)，c 3 (q)] T The method comprises the steps of carrying out a first treatment on the surface of the To facilitate the design of the controller, let
Figure BDA0004107348500000107
Figure BDA0004107348500000108
(·) -1 Representing the inverse of the matrix, (. Cndot.) T Representing a transpose of the matrix;
based on the constraint following error beta of the comprehensive three constraints constructed in the step 2) and the function pi (-) constructed in the step, constructing an adaptive law capable of self-evaluating the uncertainty variable alpha:
Figure BDA0004107348500000111
wherein the method comprises the steps of
Figure BDA0004107348500000112
Is an estimate of alpha, < >>
Figure BDA0004107348500000113
k 1 ,k 2 > 0 is a design parameter.
The following adaptive Lu Banglu stick controller was designed:
Figure BDA0004107348500000114
wherein the method comprises the steps of
Figure BDA0004107348500000115
Has been written out in this step, +.>
Figure BDA0004107348500000116
Is as follows
Figure BDA0004107348500000117
Wherein the method comprises the steps of
Figure BDA0004107348500000118
Figure BDA0004107348500000119
Wherein, xi > 0 is a constant.
The invention also provides a double-unmanned-vehicle dynamic track tracking and obstacle avoidance self-adaptive robust control system, which is used for carrying out double-unmanned-vehicle dynamic track tracking and obstacle avoidance self-adaptive robust control based on the method.
A computer device comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the method for double-unmanned vehicle dynamic track tracking and obstacle avoidance self-adaptive robust control when executing the computer program. The hardware structure of the device may include: a processor, a memory, an input/output interface, a communication interface, and a bus. Wherein the processor, the memory, the input/output interface and the communication interface are communicatively coupled to each other within the device via a bus. The processor may be implemented by using a general-purpose CPU, a microprocessor, an application-specific integrated circuit, or one or more integrated circuits, etc. to execute related programs to implement the technical solutions provided in the embodiments of the present disclosure.
The memory may be implemented in the form of ROM, RAM, static storage devices, dynamic storage devices, etc. The memory may store an operating system and other application programs, and when the technical solutions provided in the embodiments of the present specification are implemented by software or firmware, relevant program codes are stored in the memory and invoked by the processor to execute.
The input/output interface is used for connecting with the input/output module to realize information input and output. The input/output module may be configured as a component in the device or may be external to the device to provide corresponding functionality. Wherein the input devices may include a keyboard, mouse, touch screen, microphone, various types of sensors, etc., and the output devices may include a display, speaker, vibrator, indicator lights, etc.
The communication interface is used for connecting the communication module so as to realize communication interaction between the device and other devices. The communication module may implement communication through a wired manner (such as USB, network cable, etc.), or may implement communication through a wireless manner (such as mobile network, WIFI, bluetooth, etc.).
A bus includes a path to transfer information between elements of the device (e.g., a processor, memory, input/output interfaces, and communication interfaces).
Examples
In order to verify the effectiveness of the scheme of the invention, the following double unmanned vehicle dynamic track tracking and obstacle avoidance problems are simulated and verified. The control object and the target are respectively:
(1) The control object is a reconnaissance vehicle and a rescue vehicle, and the unified unmanned vehicle motion equation of the reconnaissance vehicle and the rescue vehicle is as follows:
Figure BDA0004107348500000121
wherein x is 1 ,y 1 And x 2 ,y 2 Respectively the initial coordinates of the reconnaissance vehicle and the rescue vehicle, m 1 Is the mass of the scout car, m 2 For the quality of the rescue vehicle, Q 1x ,Q 1y And Q 2x ,Q 2y Input control of the reconnaissance vehicle and the rescue vehicle respectively, f 1x ,f 1y ,f 2x ,f 2y Is the external disturbance (including ground resistance, etc.) received by the system.
The system is written into a kinetic model established in the step 1, which comprises the following steps: q= [ x ] 1 ,y 1 ,x 2 ,y 2 ] T ，τ＝[Q 1x ,Q 1y ,Q 1y ,Q 2y ]，M＝diag(m 1 ,m 2 ,m 3 ,m 4 )，D＝0,G＝0，F＝[f x ,f y ] T
(2) Control target: the reconnaissance vehicle reaches the target point first and creates a track, and the rescue vehicle realizes track tracking and obstacle avoidance.
The detailed control parameters and data are as follows:
setting the initial position of the scout car as x 1 (0)＝1，y 1 (0) =3, the arrival position is obtained by
Figure BDA0004107348500000122
As a reference point, a circle with a radius of s=0.7 is used, and the initial position of the rescue vehicle is x 2 (0)＝1，y 2 (0) =3, obstacle avoidance point selection
Figure BDA0004107348500000123
The obstacle avoidance radius is set to r=0.5m, and the external disturbance is defined as +.>
Figure BDA0004107348500000124
ΔF＝[0.01sin(10t),0.01sin(10t),0.01sin(10t),0.01sin(10t)] T . Meanwhile, the mass of the reconnaissance vehicle and the rescue vehicle is m in the simulation process 1,2 ＝1kg，/>
Figure BDA0004107348500000125
Figure BDA0004107348500000131
The design parameters of the controller are l=0.1, k 1 ＝1，k 2 ＝0.3，κ＝50，ξ＝0.1，/>
Figure BDA0004107348500000132
Matlab is adopted for simulation, and simulation results are shown in figures 1,2,3,4 and 5. FIGS. 1,2 and 3 show the constraint following error beta, respectively, for applying the control method 1 ,β 2 ,β 3 It can be seen that the constraint following error of the scout vehicle reaching the constraint is in a very short time, the fluctuation range of the tracking error is very small after the system is stable, the track tracking constraint following error and the obstacle avoidance constraint following error fluctuate near the obstacle point, and then the scout vehicle returns to a stable state, accords with the reality, and has higher control precision. In fig. 4, two curves respectively represent the difference between the motion tracks of the scout car and the rescue car in the x and y directions, and it can be seen that the difference is larger near the obstacle avoidance area, and the motion tracks return to near the stable value 0 after obstacle avoidance is completed, so that the motion tracks meet the practical requirement and have higher control precision. Fig. 5 is a track diagram of the unmanned combat platform, and it can be seen that after the scout vehicle completes the arrival of the target, the rescue vehicle follows the track of the front vehicle, and avoids the obstacle appearing in the path, and the scout vehicle continues to return to the predetermined track after the obstacle avoidance is completed, so that the control performance is better. Therefore, the invention can well solve the problem of self-adaptive robust control of the dynamic track tracking and obstacle avoidance of the double unmanned vehicles.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.

Claims (6)

1. The self-adaptive robust control method for tracking and obstacle avoidance of the dynamic track of the double unmanned vehicles comprises a reconnaissance vehicle and a rescue vehicle and is characterized by comprising the following steps:
step 1), establishing a unified unmanned vehicle dynamics model of a reconnaissance vehicle and a rescue vehicle based on a Lagrange modeling method;
step 2), establishing a mathematical model of target arrival constraint required by the reconnaissance vehicle, track tracking constraint required by the rescue vehicle and obstacle avoidance constraint according to the control target;
step 3), analyzing the mathematical model of the arrival constraint, the track constraint and the obstacle avoidance constraint established in the step 2) based on the constraint following theory, and constructing a constraint following error as a control object of the controller design;
step 4), determining a function for comprehensively describing an uncertainty limit value of the system based on the unmanned vehicle dynamics model established in the step 1), and constructing an adaptive law and adaptive robust controller by combining the mathematical model obtained in the step 2) and the constraint tracking error constructed in the step 3).
2. The method for self-adaptive robust control of double unmanned vehicles dynamic track tracking and obstacle avoidance according to claim 1, wherein in step 1), a unified unmanned vehicle dynamics model of a scout vehicle and a rescue vehicle is built based on a lagrangian modeling method, specifically comprising:
Figure FDA0004107348490000011
wherein the method comprises the steps of
Figure FDA0004107348490000012
Is uncertainty, t represents time, q (t) ∈R n Representing coordinates as a function of time, +.>
Figure FDA0004107348490000013
Speed and acceleration, respectively, M (q, sigma, t) is the inertial matrix, +.>
Figure FDA0004107348490000014
Is the Coriolis centrifugal force, G (q, sigma, t) is gravity, +.>
Figure FDA0004107348490000015
Is friction and other external interference, τ∈R n Is a control input;
for the uncertainty handling problem of the system, the model is decomposed, and the dynamics model is decomposed into a nominal part and an uncertainty part:
Figure FDA0004107348490000016
Figure FDA0004107348490000017
Figure FDA0004107348490000018
Figure FDA0004107348490000019
wherein the method comprises the steps of
Figure FDA00041073484900000110
Is a nominal moiety, ΔM (·), ΔC (·), ΔG (·), ΔF (·) is an uncertainty moiety.
3. The unmanned vehicle track tracking and obstacle avoidance adaptive robust control method according to claim 2, wherein in step 2), a mathematical model of a track tracking constraint and an obstacle avoidance constraint required by a rescue vehicle is established according to a control target, and expressed in the form of a first-order constraint and a second-order constraint, specifically:
(1) Arrival constraints of the scout car:
defining a mathematical model of the arrival constraints:
e 1 (t)：＝H 2 (q(t))-s 2 ，
wherein:
Figure FDA0004107348490000021
e 1 (t) is a mathematical model of the arrival constraint, q (t) is the coordinates of the scout car,
Figure FDA0004107348490000022
for reaching the target reference point coordinates, s is the radius of the target reaching area;
derivative, get the mathematical model reaching the first order servo constraint:
Figure FDA0004107348490000023
wherein l is a constant and l > 0;
solving the second derivative to obtain a mathematical model reaching the second-order servo constraint:
Figure FDA0004107348490000024
thereby obtaining an arrival constraint matrix:
Figure FDA0004107348490000025
arrival constraint vector:
c 1 (q(t))＝ls 2 -lH(q(t))，
Figure FDA0004107348490000026
(2) Track tracking constraint of rescue vehicle:
mathematical models defining trajectory tracking constraints:
e 2 (t)＝q 2 (t)-q 1 (t)，
wherein e 2 (t) is a mathematical model of trajectory tracking constraints, q 1 (t) is the coordinate of the track of the scout car, q 2 (t) is the coordinates of the rescue vehicle;
deriving to obtain a mathematical model of the first-order constraint of the track tracking:
Figure FDA0004107348490000031
solving the second derivative to obtain a mathematical model of the track tracking second-order constraint:
Figure FDA0004107348490000032
thereby obtaining a track tracking constraint matrix:
A 2 (q(t))＝[1 1]；
trajectory tracking constraint vector:
Figure FDA0004107348490000033
Figure FDA0004107348490000034
(3) Obstacle avoidance constraint of rescue vehicle:
defining a mathematical model of obstacle avoidance constraints:
e 3 (t)＝ln(k-f)，
wherein:
f＝||q(t)-q 0 ||，
e 3 (t) is a mathematical model of obstacle avoidance constraint, q (t) is the coordinates of the rescue vehicle, q 0 Is the obstacle coordinates, k is the radius of the safety range;
deriving to obtain a mathematical model of obstacle avoidance first-order constraint:
Figure FDA0004107348490000035
obtaining a mathematical model of obstacle avoidance second-order constraint by solving the second derivative:
Figure FDA0004107348490000036
thereby obtaining an obstacle avoidance constraint matrix:
Figure FDA0004107348490000037
obstacle avoidance constraint vector:
c 3 (q(t))＝0，
Figure FDA0004107348490000038
4. the self-adaptive robust control method for tracking and avoiding barriers of double unmanned vehicles according to claim 3, wherein the mathematical model of the arrival constraint, the track constraint and the obstacle avoidance constraint established in the step 2) is analyzed based on the constraint following theory, and a constraint following error is constructed as a control object of the controller design, and the specific method is as follows:
constructing a constraint following error of the arrival constraint:
Figure FDA0004107348490000041
constructing a constraint following error of a track tracking constraint:
Figure FDA0004107348490000042
constructing a constraint following error of obstacle avoidance constraint:
Figure FDA0004107348490000043
follow-up error beta including arrival constraints 1 Constrained following error beta for trajectory tracking 2 And following error beta of obstacle avoidance constraint 3 Is:
β＝[β 1 ，β 2 ，β 3 ] T ，
in order to simplify the writing, q is used hereinafter,
Figure FDA0004107348490000044
instead of q (t), a combination of two or more amino acids>
Figure FDA0004107348490000045
5. The method for self-adaptive robust control of double unmanned vehicle dynamic track tracking and obstacle avoidance according to claim 4, wherein in step 4), based on the unmanned vehicle dynamic model established in step 1), a function for comprehensively describing an uncertainty limit value of the system is determined, and in combination with the constraint matrix and the constraint vector obtained in step 2) and the constraint tracking error established in step 3), an adaptive law and self-adaptive robust controller is established, and the specific method is as follows:
based on the unmanned vehicle dynamics model in the step 1), the uncertainty is analyzed, the general form of an uncertainty parameter sigma is determined, scaling transformation is carried out through the following inequality, and a function pi (°) for comprehensively describing the uncertainty limit value of the system is obtained:
Figure FDA0004107348490000046
wherein the method comprises the steps of
Figure FDA0004107348490000047
Figure FDA0004107348490000048
Figure FDA0004107348490000049
Where α is the uncertainty variable in the function pi (·), κ is the control gain, P is the transfer matrix, ρ E > -1 is a constant, A is the constraint matrix in the synthesis step 2), expressed as A= [ A ] 1 (q)，A 2 (q)，A 3 (q)] T C is a constraint vector combining the two constraints, denoted as c= [ c ] 1 (q)，c 2 (q)，c 3 (q)] T ；
Figure FDA0004107348490000051
Figure FDA0004107348490000052
(·) -1 Representing the inverse of the matrix, (. Cndot.) T Representing a transpose of the matrix;
based on the constraint following error beta of the comprehensive three constraints constructed in the step 2) and the function pi (-) constructed in the step, constructing an adaptive law capable of self-evaluating the uncertainty variable alpha:
Figure FDA0004107348490000053
wherein the method comprises the steps of
Figure FDA0004107348490000054
Is an estimate of alpha, < >>
Figure FDA0004107348490000055
k 1 ，k 2 > 0 is a design parameter;
the following adaptive Lu Banglu stick controller was designed:
Figure FDA0004107348490000056
wherein the method comprises the steps of
Figure FDA0004107348490000057
Is as follows
Figure FDA0004107348490000058
Wherein the method comprises the steps of
Figure FDA0004107348490000059
Figure FDA00041073484900000510
Wherein, xi > 0 is a constant.
6. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method of any one of claims 1-5 for dual unmanned vehicle dynamic trajectory tracking and obstacle avoidance adaptive robust control.
CN202310196288.3A 2023-03-02 2023-03-02 Double-unmanned-vehicle dynamic track tracking and obstacle avoidance self-adaptive robust control method Pending CN116430847A (en)

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