Vehicle fleet tracking control method, system, computer device, and storage medium

Abstract

The present application belongs to the technical field of vehicle platoon tracking control, and specifically discloses a vehicle platoon tracking control method, system, computer device and storage medium. The method uses adaptive neural network sliding mode technology to provide a scheme for the prescribed performance multi-lane fusion tracking control of a two-dimensional three-order nonlinear vehicle platoon with actuator faults and actuator saturation. A new performance function is designed to ensure that the tracking error under asymmetric constraints reaches the preset performance, and a new three-order preset performance sliding surface is proposed for the vehicle platoon to complete multi-lane fusion tracking. The designed sliding mode fault-tolerant steering controller and saturated throttle / braking controller can ensure that the multi-lane fusion tracking error converges to the predefined area within the preset finite time under the asymmetric constraints of collision avoidance and communication maintenance. The method solves the problem of vehicle platoon tracking control with actuator faults and saturation.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of vehicle platoon tracking control, and particularly relates to a vehicle platoon tracking control method, system, computer device and storage medium, to solve the problem of vehicle platoon tracking control with actuator faults and saturation. BACKGROUND

[0002] The gradual increase in the number of vehicles has led to rapid development of intelligent transportation technology. In the face of road congestion, environmental pollution and traffic accidents, vehicle platoon tracking control has become one of the important measures to solve these problems. Vehicle platoon control technology has good performance in improving highway utilization, reducing road congestion and avoiding traffic accidents. Vehicle platoon control defined in one-dimensional plane can complete the performance control of vehicles running in the same lane. However, in practice, the number of vehicle lanes decreases during driving, which makes vehicles have to complete multi-lane fusion.

[0003] Therefore, scholars have begun to study the multi-lane fusion control problem of vehicle platoon defined in two-dimensional plane. Secondly, vehicles are affected by disturbances such as wind speed, parameter uncertainty, air resistance during driving, and are limited by the physical characteristics of vehicles. The actuators and sensors will inevitably fail due to aging, damage and other problems in engineering practical applications. These interference factors will make the system modeling inaccurate, and thus reduce the accuracy of fault diagnosis. Especially for small faults, the existence of disturbances makes it difficult to detect small faults. For vehicle platoon, due to structural limitations, control input is affected by saturation nonlinearity, and actuators often fail, which reduces system performance and even leads to system instability. The above factors bring certain challenges to vehicle platoon tracking control.

[0004] Therefore, in order to maximize the accuracy and reliability of the vehicle platoon control system, a more perfect tracking control strategy for vehicle platoon with actuator faults and saturation needs to be proposed. In addition, due to the limitations of sensor capabilities, information transmission between adjacent vehicles cannot be guaranteed. At the same time, convergence time is one of the indicators for evaluating vehicle platoon control strategies.

[0005] In order to ensure that the closed-loop system can achieve stability in a limited time, scholars have begun to study the design of finite-time vehicle platoon controller. For this purpose, barrier Lyapunov function (BLF) is applied to avoid collision and maintain communication of vehicle platoon. The BLF method can achieve specified performance control, and ensures that the convergence time and / or convergence region can be arbitrarily preset. At the same time, considering the nonlinear relationship between variables in the system, in order to obtain a more accurate system model, for a system with completely unknown nonlinear function, the BLF method can also ensure that the system approaches the predetermined region within a predetermined time. SUMMARY

[0006] The application aims to provide a preset performance multi-channel fusion tracking control method for a two-dimensional vehicle platoon with actuator faults and saturation.

[0007] In order to achieve the above-mentioned purpose, the application adopts the following technical scheme:

[0008] The vehicle platoon tracking control method comprises the following steps:

[0009] Step 1: establishing a dynamic model of a two-dimensional three-order vehicle platoon;

[0010] Step 2: based on the dynamic model of the two-dimensional three-order vehicle platoon established in step 1, establishing a detailed vehicle attitude kinematic model and describing saturation nonlinearity;

[0011] Step 3: defining the distance between vehicles based on the detailed vehicle attitude kinematic model established in step 2, and then calculating the tracking error of each vehicle in the vehicle platoon and the tracking error of the speed direction deflection angle;

[0012] Step 4: according to the tracking error of each vehicle in the vehicle platoon and the tracking error of the speed direction deflection angle calculated in step 3, constructing a performance function to realize preset performance multi-lane fusion tracking control;

[0013] Step 5: based on the vehicle attitude kinematic model described in step 2 and the distance and error defined in step 3, designing a new sliding mode surface, which is used for stability analysis in step 7;

[0014] Step 6: constructing a preset performance multi-lane fusion tracking controller according to the performance function constructed in step 4;

[0015] Step 7: based on the preset performance multi-lane fusion tracking controller designed in step 6, selecting a suitable barrier Lyapunov function to analyze the stability of the entire multi-channel vehicle platoon system, and completing multi-channel fusion control of the vehicle platoon.

[0016] In addition, on the basis of the vehicle platoon tracking control method described above, the application further provides a vehicle platoon tracking control system adapted to the vehicle platoon tracking control method, and the vehicle platoon tracking control system adopts the following technical scheme:

[0017] The vehicle platoon tracking control system comprises:

[0018] A dynamic model construction module is configured to establish a dynamic model of a two-dimensional three-order vehicle platoon;

[0019] A vehicle attitude kinematic model construction module is configured to establish a detailed vehicle attitude kinematic model based on the established dynamic model of the two-dimensional three-order vehicle platoon, and describe saturation nonlinearity.

[0020] a distance and tracking error module for defining the distance between vehicles according to the established detailed vehicle posture kinematic model, and then calculating the tracking error of each platoon and the speed direction deflection angle tracking error;

[0021] a performance function construction module for constructing a performance function according to the calculated platoon tracking error and speed direction deflection angle tracking error to achieve the preset performance of the multi-lane fusion tracking control;

[0022] a sliding mode surface module for designing a new sliding mode surface based on the vehicle posture kinematic model and the defined distance and error, and the sliding mode surface is applied to the fusion control module for stability analysis;

[0023] a tracking controller construction module for constructing a preset performance multi-lane fusion tracking controller according to the performance function;

[0024] and a fusion control module for selecting a suitable barrier Lyapunov function to analyze the stability of the entire multi-lane platoon system according to the designed preset performance multi-lane fusion tracking controller, and completing the multi-lane fusion control of the platoon.

[0025] In addition, on the basis of the above-mentioned platoon tracking control method, the present application further proposes a computer device, which comprises a memory and one or more processors.

[0026] The memory stores executable code, and the processor executes the executable code to implement the steps of the above-mentioned platoon tracking control method.

[0027] In addition, on the basis of the above-mentioned platoon tracking control method, the present application further proposes a computer readable storage medium having a program stored thereon.

[0028] The program is executed by the processor to implement the steps of the above-mentioned platoon tracking control method.

[0029] Compared with the prior art, the present application has the following advantages:

[0030] 1. The one-dimensional platoon considered in part of the research cannot complete multi-lane fusion tracking, and ignoring the engine dynamics of the two-dimensional platoon will lead to lack of practicability.

[0031] In contrast, the present application establishes a more general three-order platoon model in a two-dimensional plane, which is a prerequisite for achieving the goal of multi-lane fusion tracking.

[0032] 2. In order to avoid collisions and maintain communication between adjacent vehicles, the present invention uses a more flexible asymmetric spacing to constrain tracking errors, which also means that the symmetric performance function designed in existing research is not applicable to the present invention.

[0033] To overcome these obstacles, this invention proposes a new class of asymmetric performance functions as a key technology for achieving specified performance in multichannel fusion tracking targets under asymmetric constraints.

[0034] 3. The second-order sliding surfaces designed in some existing studies cannot be directly applied to the vehicle fleet considered in this invention because the first derivative of the sliding surface does not clearly contain the control input signal of the third-order vehicle fleet, making it impossible to complete the controller design.

[0035] Based on this, the present invention proposes a novel third-order sliding surface with asymmetric performance characteristics, and develops a multi-lane fusion tracking controller based on this. Furthermore, it can ensure that follower vehicles in different lanes track the lead vehicle with predetermined accuracy within a predetermined finite time, while avoiding collisions and maintaining communication. Attached Figure Description

[0036] Fig. 1 This is a flowchart of the vehicle tracking control method in an embodiment of the present invention.

[0037] Fig. 2 This is a schematic diagram of a convoy considered in an embodiment of the present invention, showing the initial state of the convoy under consideration.

[0038] Fig. 3 This is a schematic diagram of a convoy considered in an embodiment of the present invention, showing the final state of the convoy under consideration. Detailed Implementation

[0039] Example 1

[0040] This embodiment addresses the multi-lane fusion tracking control problem of a two-dimensional third-order nonlinear platoon, proposing a platoon tracking control method. This method utilizes adaptive neural network (NN) sliding mode technology to provide a solution for multi-lane fusion tracking control with specified performance for two-dimensional third-order nonlinear platoons exhibiting actuator failure and saturation. The invention designs a new class of performance functions to ensure that the tracking error reaches the specified performance under asymmetric constraints. A new third-order specified performance sliding surface is proposed for the considered platoon to achieve multi-lane fusion tracking. The designed fault-tolerant multi-lane fusion tracking controller, under the asymmetric constraints of avoiding collisions and maintaining communication, simultaneously ensures that the multi-lane fusion tracking error converges to a predefined region within a preset finite time.

[0041] like Figs. 1 to 3 As shown, the vehicle tracking control method in this embodiment includes the following steps:

[0042] Step 1. Establish a two-dimensional third-order dynamic model of the vehicle fleet.

[0043] In step 1, the dynamic model of the two-dimensional third-order vehicle convoy is expressed as follows:

[0044] (1a)

[0045] (1b)

[0046] (1c)

[0047] (1d)

[0048] Where i = 0, 1, ..., N, vehicle 0 is the leader, vehicle i is the follower, and N represents the number of followers; It is the vertical position. It refers to the horizontal position; It is the direction of velocity and The deflection angle between the positive directions of the axis and ; It's speed. It is acceleration. It's about quality. It is the engine time constant; It is aerodynamic drag. It is air density; among which It is air density; It is the cross-sectional area of ​​the vehicle. It is the air drag coefficient; It is rolling resistance; among which It is the rolling resistance coefficient. It is gravitational acceleration. It refers to the road slope; It is gravity; It has Unknown smooth nonlinear function; It has Saturated throttle / brake input, Indicates the control input of the follower. This indicates that the leader controls the input.

[0049] Step 2. Based on the two-dimensional third-order vehicle dynamics model established in Step 1, a detailed vehicle attitude kinematics model is established, and saturation nonlinearity is described.

[0050] In step 2, the detailed vehicle attitude kinematics model and saturated nonlinear description are as follows:

[0051] (2)

[0052] (3)

[0053] in Angular velocity, Angular acceleration; To meet Steering wheel input under actuator failure of the form; where Input for steering wheel To meet Fault efficiency coefficient; For positive integers, This is a deviation fault. and Indicates the instantaneous state of an unknown fault; in saturated nonlinearity and It is a control input The upper and lower boundaries are defined as follows:

[0054] (4)

[0055] Represented as ;in It is a satisfaction A bounded function, It is a positive constant; applying the mean value theorem... get: ;in Represent a constant. It is to satisfy The constant; Represents a piecewise smooth function with 0 as the variable, when At that time, by order middle That is, .

[0056] The acceleration dynamics of the i-th vehicle attitude kinematics model are:

[0057] (5)

[0058] in .

[0059] Step 3. Based on the detailed vehicle attitude kinematics model established in Step 2, define the distance between vehicles, and then calculate the tracking error of the convoy and the tracking error of the velocity direction deflection angle.

[0060] In step 3, the distance d between the vehicles avoiding collisions and maintaining communication is... i It is expressed as follows:

[0061] (6)

[0062] in , They represent the first , The location of each vehicle; if Then the velocity direction deflection angle Represented as ,otherwise .

[0063] To avoid collisions and maintain communication, the spacing constraint is defined as follows: ;in For minimum safe distance, This represents the maximum effective communication distance.

[0064] Vehicle i's tracking error and velocity direction deflection angle tracking error They are represented as follows:

[0065] (7a)

[0066] (7b)

[0067] in To satisfy the inequality The expected distance between adjacent vehicles.

[0068] right The asymmetric error constraints are as follows: ,in , .

[0069] Step 4. Based on the vehicle tracking error and speed direction deflection angle tracking error calculated in Step 3, construct a performance function to achieve the preset performance multi-lane fusion tracking control.

[0070] In step 4, the performance function is constructed. and as follows:

[0071] (8a)

[0072] (8b)

[0073] in It is a pre-given finite time. , and These are design parameters, and they have... and Based on the constructed performance function, the transformed tracking error is defined as follows:

[0074] ;in This represents the transformed vehicle tracking error.

[0075] Step 5. Based on the vehicle attitude kinematic model described in Step 2 and the distance and error defined in Step 3, design a new sliding surface, which will be applied in the subsequent design in Step 7. The new sliding surface designed in Step 5 is as follows:

[0076] (9a)

[0077] (9b)

[0078] in and This indicates the design of a new type of sliding surface. , , and These are the positive parameters of the design.

[0079] Step 6. Based on the performance function constructed in Step 4, construct a multi-lane fusion tracking controller with preset performance.

[0080] In step 6, the saturated throttle / brake control law is designed as follows:

[0081] (10)

[0082] in These are design parameters; To meet A known constant that is greater than zero; The parameter represents the adaptive control law.

[0083] (11)

[0084] (12)

[0085] (13)

[0086] The basis vector function representing the neural network; , .

[0087] .

[0088] and

[0089] (14)

[0090] In addition, the following fault-tolerant multi-lane fusion tracking controller was designed. :

[0091] (15)

[0092] in These are design parameters; ; The basis vector function representing the neural network; The number of neurons in a neural network; Representing unknown parameters Ordered estimation.

[0093] parameter and The adaptive law is designed as follows:

[0094] (16a)

[0095] (16b)

[0096] in and These are the design parameters.

[0097] Step 7. Based on the preset performance multi-lane fusion tracking controller designed in Step 6, select an appropriate obstacle Lyapunov function to analyze the stability of the entire multi-channel convoy system. Here, the sliding surface designed in Step 5 is used to calculate the derivative of the obstacle Lyapunov function, and finally the multi-channel fusion control of the convoy is completed.

[0098] In step 7, the barrier Lyapunov function The candidates are as follows:

[0099] (17)

[0100] in and It is the approximation error, and , Substituting the derivative of the sliding surface designed in step 5, we obtain... The derivative is as follows:

[0101] (18)

[0102] in Firstly, according to The following formula is obtained:

[0103] (19)

[0104] in:

[0105] (20)

[0106] Through derivation, we obtain:

[0107] (twenty one)

[0108] Furthermore, according to (2) and (7b), the first and second derivatives of the velocity direction deflection angle tracking error can also be obtained:

[0109] (twenty two)

[0110] The derivative of the synovial surface is then obtained as follows:

[0111] (twenty three)

[0112] Simultaneously, combining the detailed vehicle attitude kinematics model from step 2, we obtain:

[0113] (twenty four)

[0114] Using neural networks and Approximation capability and It is approximated as follows:

[0115] (25)

[0116] (26)

[0117] in and The approximation errors are, in order. and Represents two positive constants; and They represent and The weight matrix of the approximated neural network.

[0118] According to formulas (24), (25), and (26), the Lyapunov function is transformed into the following form:

[0119] (27)

[0120] Using Young's inequality and the steps in step 2... With bounded constraints, the following inequalities hold:

[0121] (28)

[0122] (29)

[0123] (30)

[0124] in , ; express norm, express The norm. Based on steps 2 and 3 mentioned... The determination and failure efficiency coefficient From the properties, we obtain:

[0125] (31)

[0126] Based on formulas (10), (15), and (31), we obtain:

[0127] (32)

[0128] Substituting formulas (16a) and (16b) into formula (32), we get:

[0129] (33)

[0130] According to Young's inequality, we obtain the following inequalities:

[0131] (34a)

[0132] (34b)

[0133] Combining formulas (34a), (34b), and (33), it can be expressed as:

[0134] (35)

[0135] in .

[0136] Choose the entire Lyapunov function as: Through equation (35), we can obtain The derivative:

[0137] (36)

[0138] in , Formula (36) means:

[0139] (37)

[0140] The results of the stability analysis using the candidate barrier Lyapunov function show that all closed-loop signals can remain bounded; obviously, It is bounded. It is also bounded; it depends on choice. and Initial value parameters and Prerequisites It can be guaranteed; furthermore, because It is bounded, from and Starting from the definition, there is Therefore, when At that time, tracking error Able to achieve preset performance targets, that is, meet ; and This is a pre-specified tracking precision. Furthermore, based on string stability, the entire convoy is string-stable, and further based on... and ,when When asymmetric spacing constraints This assurance indicates that the convoy can maintain an appropriate safe distance. Therefore, ultimately, under the saturation throttle / brake control law and fault-adjusting steering wheel control strategy, convoy tracking control under actuator failure and saturation conditions is achieved.

[0141] This invention achieves Fig. 3 In multi-lane fusion tracking, the convoy tracking error converges to the asymmetric constraints mentioned in step 4. For example... Fig. 2 and Fig. 3 The convoy under consideration achieved consistency by achieving convergence of tracking errors from the initial state to the final state.

[0142] Example 2

[0143] This embodiment 2 describes a fleet tracking control system, which is based on the same inventive concept as the fleet tracking control method described in embodiment 1. Specifically, the fleet tracking control system includes:

[0144] The dynamics model building module is used to build a two-dimensional third-order vehicle dynamics model;

[0145] The vehicle attitude kinematics model building module is used to build a detailed vehicle attitude kinematics model based on the established two-dimensional third-order vehicle convoy dynamics model, and to describe saturated nonlinearity.

[0146] The distance and tracking error module is used to define the distance between vehicles based on the established detailed vehicle attitude kinematic model, and then calculate the tracking error and velocity direction deflection angle tracking error for each vehicle.

[0147] The performance function construction module is used to construct performance functions based on the calculated vehicle tracking error and speed direction deflection angle tracking error to achieve multi-lane fusion tracking control with preset performance.

[0148] The sliding surface module is used to design a new sliding surface based on the vehicle attitude kinematics model and the distance and error defined in step 3, and apply it to the fusion control module for stability analysis.

[0149] The tracking controller building module is used to build a multi-lane fusion tracking controller with preset performance based on the performance function;

[0150] The system also includes a fusion control module, which is used to select an appropriate obstacle Lyapunov function to analyze the stability of the entire multi-channel convoy system based on the designed preset performance multi-lane fusion tracking controller. Here, the designed slip surface module is used to calculate the derivative of the obstacle Lyapunov function, and finally complete the multi-channel fusion control of the convoy.

[0151] It should be noted that the implementation process of the functions and roles of each functional module in the fleet tracking and control system is detailed in the implementation process of the corresponding steps in the method of the above embodiment 1, and will not be repeated here.

[0152] Example 3

[0153] This embodiment 3 describes a computer device used to implement the steps of the vehicle tracking control method described in embodiment 1 above.

[0154] The computer device includes a memory and one or more processors. Executable code is stored in the memory, which, when executed by the processor, implements the steps of the aforementioned fleet tracking control method.

[0155] In this embodiment, the computer device can be any device or apparatus with data processing capabilities, and will not be described in detail here.

[0156] Example 4

[0157] This embodiment 4 describes a computer-readable storage medium for implementing the steps of the fleet tracking control method described in embodiment 1 above.

[0158] The computer-readable storage medium in this embodiment 4 stores a program that, when executed by a processor, is used to implement the steps of the above-described vehicle tracking control method.

[0159] The computer-readable storage medium can be an internal storage unit of any device or apparatus with data processing capabilities, such as a hard disk or memory, or an external storage device of any device with data processing capabilities, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc.

[0160] Of course, the above description is only a preferred embodiment of the present invention. The present invention is not limited to the above-described embodiments. It should be noted that any equivalent substitutions or obvious modifications made by those skilled in the art under the guidance of this specification fall within the scope of this specification and should be protected by the present invention.

Claims

1. A vehicle tracking and control method, characterized in that, Includes the following steps: Step 1. Establish a two-dimensional, third-order dynamic model of the vehicle fleet, represented as follows: (1a) (1b) (1c) (1d) Where i = 0, 1, ..., N, vehicle 0 is the leader, vehicle i is the follower, and N represents the number of followers; It is the vertical position. It refers to the horizontal position; It is the direction of velocity and The deflection angle between the positive directions of the axis and ; It's speed. It is acceleration. It's about quality. It is the engine time constant; It is aerodynamic drag. It is air density; in, It is air density. It is the cross-sectional area of ​​the vehicle. It is the air drag coefficient; It is rolling resistance; in, It is the rolling resistance coefficient. It is gravitational acceleration. It refers to the road slope; It is gravity. It has Unknown smooth nonlinear function, It has Saturated throttle / brake input; in, Indicates the control input of the follower. This represents the leader's control input; Step 2. Based on the two-dimensional third-order vehicle dynamics model established in Step 1, establish a detailed vehicle attitude kinematics model and describe the saturation nonlinearity; Step 3. Based on the detailed vehicle attitude kinematics model established in Step 2, define the distance between vehicles, and then calculate the tracking error and velocity direction deflection angle tracking error for each vehicle in the platoon; Step 4. Based on the tracking error and speed direction deflection angle tracking error of each vehicle in the platoon calculated in Step 3, construct a performance function to realize multi-lane fusion tracking control; Step 5. Based on the vehicle attitude kinematic model described in Step 2 and the distance and error defined in Step 3, design a new sliding surface, which is used for stability analysis in Step 7; Step 6. Based on the performance function constructed in Step 4, build a preset performance multi-lane fusion tracking controller; Step 7. Based on the preset performance multi-lane fusion tracking controller designed in Step 6, select an appropriate obstacle Lyapunov function to analyze the stability of the entire multi-channel convoy system and complete the multi-channel fusion control of the convoy.

2. The vehicle tracking and control method according to claim 1, characterized in that, The detailed vehicle attitude kinematics model and saturated nonlinearity description in step 2 are as follows: (2) (3) in, Angular velocity, Angular acceleration; To meet Steering wheel input under actuator failure; in, Input for steering wheel To meet Fault efficiency coefficient; For positive integers, This is a deviation fault. and Indicates the instant of an unknown failure; In saturated nonlinearity and It is a control input The upper and lower boundaries are defined as follows: (4) Represented as ;in It is a satisfaction A bounded function, It is a positive constant; Applying the mean value theorem get: ; in , ; It is to satisfy The constant; in Represent a constant. Represents a piecewise smooth function with 0 as the variable, when At that time, by order In That is, ; The acceleration dynamics of the i-th vehicle attitude kinematics model are: (5) in .

3. The vehicle tracking control method according to claim 2, characterized in that, In step 3, the distance d between the vehicles that avoid collisions and maintain communication is... i It is expressed as follows: (6) in , They represent the first , The location of each vehicle; if Then the velocity direction deflection angle Represented as ,otherwise ; To avoid collisions and maintain communication, the spacing constraint is defined as follows: ; in For minimum safe distance, The maximum effective communication distance; Vehicle i's tracking error and velocity direction deflection angle tracking error They are represented as follows: (7a) (7b) in To satisfy the inequality The expected distance between adjacent vehicles; for The asymmetric error constraints are as follows: ,in , .

4. The vehicle tracking control method according to claim 3, characterized in that, In step 4, the constructed performance function and as follows: (8a) (8b) in It is a pre-given finite time. , and These are design parameters, and they have... and Based on the constructed performance function, the transformed tracking error is defined as follows: ;in This represents the transformed vehicle tracking error.

5. The vehicle tracking control method according to claim 4, characterized in that, In step 5, a new sliding surface is designed, as shown below: (9a) (9b) in and This indicates the design of a new type of sliding surface. , , and These are the positive parameters of the design.

6. The vehicle tracking control method according to claim 5, characterized in that, In step 6, the saturated throttle / brake control law is designed as follows: (10) in These are design parameters; To meet A known constant that is greater than zero; Parameters representing the adaptive control law; (11) (12) (13) The basis vector function representing the neural network; , ; ； and (14) In addition, the following fault-tolerant multi-lane fusion tracking controller was designed. : (15) in These are design parameters; ; The basis vector function representing the neural network; The number of neurons in a neural network; Representing unknown parameters Ordered estimation; parameter and The adaptive law is designed as follows: (16a) (16b) in and These are design parameters; In step 7, a suitable obstacle Lyapunov function is selected to perform stability analysis on the entire multi-channel convoy system. The candidates are as follows: (17) in and It is the approximation error, and , Substituting the derivative of the new sliding surface designed in step 5 based on the vehicle attitude kinematics model and distance and error, we obtain... The derivative is as follows: (18) in Firstly, according to The following formula is obtained: (19) in: (20) Through derivation, we obtain: (21) Furthermore, according to formulas (2) and (7b), the first and second derivatives of the velocity direction deflection angle tracking error can be obtained: (22) The derivative of the synovial surface is then obtained as follows: (23) Simultaneously, combining the detailed vehicle attitude kinematics model from step 2, we obtain: (24) Using neural networks and Approximation capability and It is approximated as follows: (25) (26) in and The approximation errors are, in order. and Represents two positive constants; and They represent and The weight matrix of the approximated neural network; According to formulas (24), (25), and (26), the Lyapunov function is transformed into the following form: (27) Using Young's inequality and step 2, With bounded constraints, the following inequalities hold: (28) (29) (30) in , , express norm, express The norm; based on steps 2 and 3 Definition and failure efficiency coefficient From the properties, we obtain: (31) Based on formulas (10), (15), and (31), we obtain: (32) Substituting formulas (16a) and (16b) into formula (32), we get: (33) According to Young's inequalities, the following inequalities are obtained: (34a) (34b) Combining formulas (34a) and (34b), formula (33) can be expressed as: (35) in ; Choose the entire Lyapunov function as: ; Through equation (35), we obtain The derivative: (36) in, , Formula (36) means: (37) The results of the stability analysis using the candidate barrier Lyapunov function show that all closed-loop signals remain bounded; obviously, It is bounded. It is also bounded; it depends on choice. and Initial value parameters and Prerequisites It can be guaranteed; furthermore, because It is bounded, from and Starting from the definition, there is Therefore, when At that time, tracking error Able to achieve preset performance targets, that is, meet ; and It is a pre-specified tracking accuracy; furthermore, based on string stability, the entire convoy is string-stable, and further based on... and ,when When asymmetric spacing constraints This assurance means that the convoy can maintain an appropriate safe distance; therefore, under the control of the saturated throttle / brake control law and the fault-adjusting steering wheel control, it is possible to achieve convoy tracking control in case of actuator failure and saturation.

7. A fleet tracking control system for implementing the fleet tracking control method as described in claim 1, characterized in that, The fleet tracking and control system includes: The dynamics model building module is used to build a two-dimensional third-order vehicle dynamics model; The vehicle attitude kinematics model building module is used to build a detailed vehicle attitude kinematics model based on the established two-dimensional third-order vehicle convoy dynamics model, and to describe saturated nonlinearity. The distance and tracking error module is used to define the distance between vehicles based on the established detailed vehicle attitude kinematic model, and then calculate the row tracking error and velocity direction deflection angle tracking error for each vehicle. The performance function construction module is used to construct performance functions based on the calculated vehicle tracking error and speed direction deflection angle tracking error to achieve multi-lane fusion tracking control with preset performance. The sliding surface module is used to design a new sliding surface based on the vehicle attitude kinematics model and the distance and error defined in step 3. This sliding surface is used in the fusion control module for stability analysis. The tracking controller building module is used to build a multi-lane fusion tracking controller with preset performance based on the performance function; And a fusion control module, which is used to select an appropriate obstacle Lyapunov function to analyze the stability of the entire multi-channel convoy system based on the designed preset performance multi-lane fusion tracking controller, and finally complete the multi-channel fusion control of the convoy.

8. A computer device comprising a memory and one or more processors, wherein the memory stores executable code, characterized in that, When the processor executes the executable code The steps of implementing the vehicle tracking control method as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the fleet tracking control method as described in any one of claims 1 to 6.

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