Heterogeneous fleet preset time uniform sliding mode fault-tolerant control method for complex working conditions

Abstract

This invention provides a unified sliding mode fault-tolerant control method for heterogeneous vehicle fleets under complex operating conditions, belonging to the field of traffic control systems and intelligent transportation technology. To adapt to complex traffic scenarios such as multi-vehicle merging, platooning, lane changing, and lane restoration, this invention first establishes a third-order longitudinal and lateral coupled dynamic model of a two-dimensional planar heterogeneous vehicle fleet. Secondly, it designs two sets of preset time performance functions to ensure the transient and steady-state control performance of the fleet, enabling the tracking error to converge to a specified steady-state interval within a preset time and reducing the impact of initial conditions on tracking accuracy. Furthermore, this invention proposes a unified sliding mode fault-tolerant control strategy based on Nussbaum functions, which can suppress the adverse effects of complete actuator failure in unknown directions and asymmetric actuator saturation, ensuring stable and safe operation of the fleet under complex conditions.

Description

Technical Field

[0001] This invention relates to the fields of traffic control systems and intelligent transportation technology, and in particular to a unified sliding mode fault-tolerant control method for heterogeneous vehicle fleets under complex operating conditions with preset time. Background Technology

[0002] With the rapid development of intelligent transportation systems, vehicle platooning technology has become a core means to improve traffic efficiency, reduce energy consumption, and ensure driving safety in the field of intelligent transportation. Vehicles actually exhibit longitudinal and lateral coupled motion, requiring adaptation to complex conditions such as multi-vehicle merging, platooning, lane changing, and lane restoration. Two-dimensional planar platooning control is particularly crucial. Existing research often employs simplified second-order dynamic models, which struggle to accurately characterize the longitudinal and lateral coupling characteristics of vehicles and generally neglect actuator failure issues. Conventional actuator failure models only cover failure and bias faults, with fault coefficients limited to the (0,1) range. However, in actual engineering, actuator failures exhibit unknown directions and time-varying characteristics. High-temperature wear, motor reversal, and high-frequency component damage can cause fault coefficients to be negative or greater than 1, severely deteriorating vehicle dynamic performance and leading to platoon instability and increased collision risk. Furthermore, actuator saturation can cause dynamic response lag, weakening the longitudinal and lateral coordinated control performance of the platoon. Therefore, it is urgent to construct a longitudinally and laterally coupled heterogeneous platoon dynamic model that considers both unknown-direction complete actuator failures and asymmetric actuator saturation.

[0003] Meanwhile, platooning operations place stringent demands on transient response characteristics and trajectory tracking accuracy, making performance control methods a research hotspot in platooning control. Existing performance control based on traditional performance functions can only achieve basic trajectory tracking of two-dimensional platoons under ideal conditions; however, platoons often need to complete platoon tracking and cooperative driving tasks within a preset time. Existing research has not fully considered convergence time performance, and conventional performance control methods are difficult to adapt to time-limited task scenarios. To this end, control strategies based on finite-time and fixed-time performance functions have been gradually applied to two-dimensional platooning systems. Although these strategies have improved transient tracking performance and achieved bounded convergence to some extent, they still have two major drawbacks: the error convergence time cannot be preset according to task requirements; and both use symmetrical performance boundaries, making it difficult to adapt to complex traffic conditions and meet the high-precision cooperative tracking requirements of two-dimensional platoons. Therefore, designing a novel asymmetric preset time performance function is key to achieving high-precision cooperative tracking of two-dimensional planar platoons.

[0004] Furthermore, platooning operations are susceptible to disturbances such as road bumps, gusts of wind, and actuator aging, requiring the control system to possess strong robustness and fault tolerance. Sliding mode control, with its strong robustness and inherent fault tolerance potential, has been widely used in platooning control research. To improve convergence performance, finite-time and fixed-time sliding mode control methods have been proposed, enabling rapid convergence of tracking errors. However, existing results are mostly aimed at one-dimensional platoons and cannot be directly applied to two-dimensional planar platoons; a few two-dimensional studies use second-order models, which are difficult to accurately reflect the actual dynamic characteristics of vehicles. Although recent research has proposed adaptive fixed-time sliding mode control to solve the cooperative control problem under lane and distance constraints, it cannot flexibly preset the convergence time and has not constructed an active fault-tolerant framework. Under faults and disturbances, it is prone to platoon instability and low tracking accuracy, making it difficult to meet actual operational requirements. Therefore, it is necessary to propose a unified preset-time sliding mode fault-tolerant control scheme to fill the above research gaps. Summary of the Invention

[0005] To address the shortcomings of existing vehicle platoon control technologies, such as low dynamic model coupling accuracy, failure to account for actuator failures in unknown directions and asymmetric saturation constraints, poor adaptability to various operating conditions, limited tracking convergence performance, and control singularities, this invention provides a unified sliding mode fault-tolerant control method for heterogeneous platoons with preset time for complex operating conditions. This method is applicable to two-dimensional heterogeneous platooning systems with actuator failures in unknown directions and nonlinear input saturation constraints. It adapts to complex traffic conditions such as multi-vehicle merging, platooning, platooning lane changes, and lane restoration, effectively solving the problems of weak fault tolerance, poor convergence performance, and limited applicability to various operating conditions inherent in traditional control strategies.

[0006] To achieve the above objectives, this invention provides a unified sliding mode fault-tolerant control method for heterogeneous vehicle fleets under complex operating conditions, comprising the following steps:

[0007] First, we constructed a complex traffic scenario for a two-dimensional vehicle platoon, covering typical driving conditions of various vehicle platoons.

[0008] Secondly, a longitudinally and laterally coupled heterogeneous vehicle dynamics model with unknown direction fully actuator failure and asymmetric saturation constraints is constructed to match the heterogeneous characteristics of leader and follower vehicles.

[0009] Furthermore, we designed queue obstacle avoidance and communication topology preservation rules, constructed a new preset time performance function, optimized the system tracking error constraint characteristics, and took into account both the transient and steady-state control performance of the system.

[0010] Finally, a unified sliding surface was built and a new preset time sliding mode fault-tolerant control strategy was designed to achieve preset time convergence of the queuing system, effectively resist external disturbances and actuator performance degradation, eliminate control singularities, and improve the stability and robustness of queuing cooperative driving under complex constraints.

[0011] The beneficial effects of this invention are as follows:

[0012] 1) This invention constructs a three-order longitudinally and laterally coupled two-dimensional planar queue dynamic model. Compared with the existing two-dimensional planar queue control scheme, it can achieve safe and stable operation of the convoy under various traffic conditions such as multi-vehicle merging, queue driving, queue lane changing and original lane restoration under the constraints of complete actuator failure in unknown directions and asymmetric actuator saturation, thus broadening the applicable range of vehicle queue control conditions.

[0013] 2) This invention designs two sets of novel preset time performance functions. Compared with traditional performance control strategies and finite / fixed time performance control methods, these functions not only enable the tracking error to converge quickly to the preset steady-state range within a preset time, but also relax the stringent initial error constraints, introduce asymmetric error boundaries, effectively adapt to complex and ever-changing vehicle driving conditions, and take into account both the transient and steady-state control performance of the system.

[0014] 3) This invention proposes a novel preset-time unified sliding mode fault-tolerant control strategy. Compared with existing sliding mode control technology, it can flexibly preset the convergence time of the queue system and has active fault tolerance capability to resist complex disturbances and actuator performance degradation for two-dimensional planar queues. At the same time, it can eliminate control singularity problems, significantly improve the convergence efficiency of the queue control system, and ensure the reliability and stability of the convoy during operation.

[0015] Additional advantages of the present invention will be presented in such a way that some will be directly stated in the following description, some will be gradually revealed in the process of description, and others will be known through specific practice of the invention. Attached Figure Description

[0016] The accompanying drawings, which constitute a part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0017] Figure 1 This is the overall flowchart of the pre-set time unified sliding mode fault-tolerant control method for heterogeneous vehicle fleets under complex working conditions according to the present invention.

[0018] Figure 2 This invention presents a complex traffic scenario involving two-dimensional planar vehicle queuing, including multi-vehicle merging, queuing driving, queuing lane changing, and restoration of the original lane.

[0019] Figure 3 This is a diagram showing the three-dimensional vehicle position trajectory results in an embodiment of the present invention;

[0020] Figure 4 This is a graph showing the speed trajectory results of all vehicles in this embodiment of the invention;

[0021] Figure 5This is a diagram showing the heading angle trajectory results for all vehicles in this embodiment of the invention;

[0022] Figure 6 This is a diagram showing the angular rate trajectory results of all vehicles in this embodiment of the invention;

[0023] Figure 7 This is a diagram showing the trajectory results of the longitudinal composite sliding surface in an embodiment of the present invention;

[0024] Figure 8 This is a diagram showing the trajectory results of the transverse composite sliding surface in an embodiment of the present invention;

[0025] Figure 9 This is a diagram showing the longitudinal control input trajectory results in an embodiment of the present invention;

[0026] Figure 10 This is a diagram showing the lateral control input trajectory results in an embodiment of the present invention;

[0027] Figure 11 This is a diagram showing the tracking error trajectory results in an embodiment of the present invention;

[0028] Figure 12 This is a diagram showing the trajectory results of lane changing and original lane restoration in an embodiment of the present invention; Detailed Implementation

[0029] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0030] This invention provides a unified sliding mode fault-tolerant control method for heterogeneous vehicle fleets under complex operating conditions, with preset time, such as... Figure 1 As shown, the specific steps include:

[0031] S1: Construct a complex traffic scenario for two-dimensional planar vehicle queuing, including multi-vehicle merging, queuing driving, queuing lane changing, and restoration of the original lane;

[0032] S2: Establish heterogeneous dynamics models of longitudinally and laterally coupled third-order follower vehicles and second-order leader vehicles, considering the failure of fully actuators in unknown directions and the saturation constraints of asymmetric actuators.

[0033] S3: Formulate rules for queue obstacle avoidance and communication topology maintenance, design two sets of new preset time performance functions, construct asymmetric error boundaries, relax the initial tracking error constraints of the system, and take into account the transient and steady-state control performance of vehicle queue driving.

[0034] S4: Construct a unified sliding surface with preset time, design a fault-tolerant control strategy with preset time unified sliding surface, realize flexible preset convergence time, actively resist complex disturbances and actuator performance degradation, and ensure the robustness and stability of the fleet under complex working conditions.

[0035] In practical implementation, the first step is to build a two-dimensional planar vehicle queuing scenario for complex traffic conditions such as multi-vehicle merging, queuing driving, queuing lane changing, and original lane restoration (e.g., Figure 2 As shown), this heterogeneous convoy mainly consists of one leader vehicle. and A following vehicle.

[0036] Establish follower vehicles The third-order dynamic model with longitudinal and transverse coupling:

[0037] ,

[0038] and

[0039] ,

[0040] in, , , , These represent the vehicle's longitudinal position, lateral position, velocity, and acceleration, respectively. , , These represent the vehicle's heading angle, angular rate, and angular acceleration, respectively. and These represent the throttle / brake input and steering wheel input in the event of an actuator malfunction, respectively. and Represent the unknown disturbances of the accelerator / brake and the steering wheel, respectively; unknown nonlinear functions. It can be decomposed into two components: In this formula Represents a known nonlinear term. Indicates unknown or uncertain terms; Indicates the mass of the vehicle; Indicates the engine time constant; Indicates air mass density; Indicates the cross-sectional area facing the wind; Indicates the air drag coefficient; Indicates the road slope angle; Represents gravitational acceleration; This represents the road resistance coefficient.

[0041] Establish a second-order dynamic model of the leader vehicle with longitudinal and lateral coupling:

[0042] ,

[0043] in, , , , These represent the longitudinal position, lateral position, velocity, and acceleration of the leader's vehicle, respectively. , , These represent the leader's vehicle's heading angle, angular rate, and angular acceleration, respectively.

[0044] Constructing a complete actuator failure model with unknown direction and an asymmetric actuator saturation model:

[0045] ,

[0046] in, , ; Denotes the unknown actuator failure efficiency factor and satisfies ; Represents an unknown bounded bias signal that satisfies .according to and Depending on the value of , complete actuator failures can be classified into 8 types: 1. Actuator is normal: , 2. Partial failure: , 3. Bias fault: , 4. Partial failure—bias compound fault: , 5. Excessive failure: , 6. Over-bias compound fault: , 7. Reverse fault: , 8. Reverse-bias combined fault: , .

[0047] Asymmetric actuator saturation The structure is as follows:

[0048] ,

[0049] in, , These represent the actual control inputs. The upper / lower bound; , These represent the saturation amplitude, respectively. , These represent two different unknown nonlinear terms. For ease of control design later, the saturation function can be rewritten as: ,in It is a time-varying saturation coefficient and satisfies , .

[0050] Based on the above analysis, the vehicle dynamics with unknown-direction full actuator failure and nonlinear saturation can be rewritten as follows:

[0051] ,

[0052] in, and Defined as total disturbance of two types.

[0053] Then, formulate the rules for queue obstacle avoidance and communication topology preservation:

[0054] vehicle Adjacent vehicles Distance between and relative azimuth Defined as:

[0055] ,

[0056] Among them, when the vehicle With vehicles When the longitudinal position difference is zero, in order to eliminate the singularity in the calculation of the arctangent function, the azimuth angle is defined. To simultaneously meet the requirements of collision avoidance and uninterrupted communication links, the distance constraint is defined as follows: ,in and These represent the minimum permissible safe distance and the maximum effective communication range, respectively. The range of velocity angle variation is set as follows: .definition Then the angle constraint satisfies the inequality: .

[0057] Therefore, the spacing tracking error and azimuth tracking error are constructed:

[0058] ,

[0059] in, This indicates that the desired spacing satisfies ; This indicates that the desired azimuth angle satisfies Furthermore, the spacing tracking error and azimuth tracking error must comply with the following constraints: and .

[0060] For simplicity, auxiliary variables are defined here. The subscript satisfies Specifically, and Set as follows and The simplified form. This notation simplification also applies to all other state variables.

[0061] Then, two new sets of preset time performance functions are designed:

[0062] ,

[0063] and

[0064] ,

[0065] in, , , , , , These are all positive parameters of the design.

[0066] To relax the strict performance constraints on the initial tracking error, a time-varying offset function is introduced. Used to redefine tracking error

[0067]

[0068] and

[0069]

[0070] in, It is a given time constant. When Sometimes, Established, and .

[0071] To ensure that performance constraints are satisfied throughout the entire control process, the following initial inequalities must hold:

[0072]

[0073] Therefore, in order to achieve tracking error Small overshoot will affect the preset time performance function. and Build as

[0074] ,

[0075] in, It is an offset function and satisfies , and This indicates the positive design parameters.

[0076] To facilitate subsequent controller design, an error transformation method is proposed, which converts bounded tracking error into unconstrained error. The specific form of this transformation is defined as follows:

[0077]

[0078] Then, to ensure vehicle platoon stability, coupled error variables are designed. for:

[0079] ,

[0080] in, , and They have equivalent convergence.

[0081] The preset time sliding surface is designed as follows:

[0082] ,

[0083] and

[0084] ,

[0085] in, , , , , , , , . , , , , , It is a design constant.

[0086] Based on the above formula, a new time-unified sliding surface is constructed, with the specific expression as follows:

[0087] ,

[0088] and

[0089] ,

[0090] in, , , , , It is a design constant. , , , , , .

[0091] Due to the total longitudinal disturbance With total lateral disturbance Since direct measurement is not possible, this application employs a radial basis function neural network approximation method to further obtain: and in, It is an ideal weight vector. Represents a basis function vector. The bounded approximation error is expressed as: .

[0092] Furthermore, the longitudinal and transverse controllers are designed as follows:

[0093]

[0094] and

[0095] ,

[0096] ,

[0097] in, , , , , , , It is a design constant. Let... ,and yes The estimate, and This indicates the estimation error. It is an offsetting term. It is a Nussbaum function designed that satisfies .

[0098] Meanwhile, the adaptive law is constructed as follows:

[0099]

[0100] Based on the above design, the following steps will be used to perform a stability analysis:

[0101] Step 1 (Proving the boundedness of tracking error): Establish the Lyapunov function:

[0102] Based on the designed preset time performance function, preset time unified sliding surface, preset time unified sliding fault-tolerant controller, and adaptive law, the derivative of the Lyapunov function can be obtained:

[0103] ,

[0104] in, , , .

[0105] Therefore, the queue satisfies the actual preset time stability, that is... At the preset time Stable region near the origin of inward convergence There exists a positive constant. (in ), and satisfy

[0106] ,

[0107] in, .

[0108] Furthermore, it can be deduced that and It converges within the following bounds.

[0109]

[0110] when When approaching a small neighborhood near zero, it can be approximated as Given and The equivalence of the preset time for the unified sliding surface It can be re-represented as Therefore, a Lyapunov function is established. Its derivative is calculated as Next, according to and The relationship between them should be analyzed separately for the following two situations. The convergence behavior.

[0111] when hour, ,in Further obtained .therefore It can converge within a preset time. When It can be calculated and , At this point, the convergence rate is higher than... This results in a shorter convergence duration during this phase. Considering both scenarios, Achieve convergence within the preset time. A conservative upper limit for the convergence time can be derived as follows: Similarly, when It converges to zero within a preset time (i.e.) When ), there exists . The convergence time can be expressed as In summary, the error signal It has preset time stability, which means that within time constraints Inside, due to Equivalence and They will all converge to a small area near the origin.

[0112] Step 2 (Verifying vehicle queue stability at preset time): Since Step 1 has already proven that all errors meet the preset time stability, for all... All have Further, we can obtain .pass and There is an equivalence relation between them, which can be used to deduce ,because Furthermore, based on the definition of vehicle queue stability, the fleet successfully achieved queue stability for the preset time.

[0113] Step 3 (verifying the feasibility of the preset time performance): Calculate the exponential form of the error transformation function as follows: Further simplification yields its algebraic form. Based on the inherent boundedness of the sigmoid function, the following constraints are obtained. This ensures the preset time performance constraints of the two-dimensional planar vehicle queue.

[0114] To verify the feasibility and superiority of this invention, the following simulation experiments were conducted:

[0115] The simulation employs a two-dimensional heterogeneous vehicle platoon consisting of one leader vehicle and four follower vehicles. A series of simulation experiments were conducted to simulate real-world highway driving scenarios, including multi-vehicle merging, platoon driving, platoon lane changing, and lane re-entry.

[0116] The time-varying reference speed of the leader vehicle is set to Therefore, its reference acceleration can be calculated as follows: The unknown and uncertain term is defined as follows: The interference signals for the accelerator / brake and steering wheel are described as follows: and The complete actuator failure model for the four follower vehicles is considered as follows:

[0117] Throttle / brake actuator malfunction:

[0118]

[0119] Steering wheel actuator malfunction:

[0120]

[0121] Furthermore, the saturation input selection for longitudinal and lateral asymmetric actuators is as follows:

[0122] Longitudinal actuator saturation:

[0123]

[0124] Lateral actuator saturation:

[0125]

[0126] The parameters for the vehicle queue are selected as follows: , , , , , , , , , , , , , , , , , , , , , , , , , , , Other design parameters are provided below: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , .

[0127] The initial values ​​are set as follows: , , , , , , , , .

[0128] The effectiveness of the simulation in this embodiment is further illustrated by referring to the accompanying drawings:

[0129] Based on the above analysis, the simulation results of multi-vehicle merging and platooning are as follows: Figure 3 — Figure 11 As shown. Figure 3 The diagram illustrates the three-dimensional positional trajectories during the multi-vehicle merging process. The four following vehicles adjust their lateral positions in the initial phase to complete the lane merging, then form a stable convoy along the leader vehicle's path, maintaining a safe following distance. Figure 4 For the speed trajectories of all vehicles, you can see that each follower vehicle is able to track the speed of the leader vehicle; Figure 5 and Figure 6 The trajectories for the vehicle's heading angle and angular velocity are shown respectively. It can be observed that there are slight fluctuations in the initial stage, which then quickly converge to zero without any continuous oscillations. Figure 7 and Figure 8 The longitudinal and transverse composite sliding surfaces, respectively, converged to the equilibrium point within a preset time, which confirms the accessibility and preset time convergence capability of the proposed sliding mode control scheme. Figure 9 and Figure 10 The longitudinal and lateral control inputs demonstrate that the proposed control strategy can achieve stable convergence within a preset time even in the presence of unknown direction full actuator failure and asymmetric actuator saturation; Figure 11 shows the simulation results of the tracking error. Whether it is the spacing tracking error ( Figure 11 a) Or is it angle tracking error? Figure 11 (b) All of them exhibit consistent convergence characteristics: after small initial fluctuations, all errors converge rapidly to near zero within the specified preset time range and strictly remain within the preset time performance range, verifying the effectiveness of the proposed preset time performance constraint scheme.

[0130] Figure 12 It demonstrates the evolution of the two-dimensional trajectory of the queue during the coordinated lane changing and original lane restoration process after multiple vehicles merge. Figure 12 a demonstrates the entire operation process, with a time frame of [time range]. This includes queuing lane changes, queuing movement, and returning to the original lane. Figure 12 b— Figure 12 d respectively shows the lane change phase ( ), queue driving phase ( ) and lane return phase ( Throughout the process, all following vehicles accurately tracked the leader vehicle's trajectory, maintaining a tight and stable convoy without lane departures or abnormal following distances. Therefore, these results validate the effectiveness of the proposed control scheme in complex traffic scenarios.

[0131] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A unified sliding mode fault-tolerant control method for heterogeneous vehicle fleets under complex operating conditions, characterized in that: Includes the following steps: S1: Construct a complex traffic scenario for two-dimensional planar vehicle queuing, including multi-vehicle merging, queuing driving, queuing lane changing, and restoration of the original lane; S2: Establish heterogeneous dynamics models of longitudinally and laterally coupled third-order follower vehicles and second-order leader vehicles, considering the failure of fully actuators in unknown directions and the saturation constraints of asymmetric actuators. S3: Formulate queue obstacle avoidance and communication topology preservation rules, design two sets of new preset time performance functions, construct asymmetric error boundaries, relax the initial tracking error constraints of the system, and take into account the transient and steady-state control performance of vehicle queue driving. S4: Construct a unified sliding surface with preset time, design a fault-tolerant control strategy with preset time unified sliding surface, realize flexible preset convergence time, actively resist complex disturbances and actuator performance degradation, and ensure the robustness and stability of the fleet under complex working conditions.

2. The method according to claim 1, characterized in that, In step S2, Establish a heterogeneous dynamics model for a longitudinally and laterally coupled third-order follower vehicle and a second-order leader vehicle, considering complete actuator failure in unknown directions and asymmetric actuator saturation constraints: ， in, , , , These represent the vehicle's longitudinal position, lateral position, velocity, and acceleration, respectively. , , These represent the vehicle's heading angle, angular rate, and angular acceleration, respectively. , These represent the failure efficiency factors for unknown actuators of the throttle / brake and steering wheel, respectively. , These represent the time-varying saturation coefficients; and Separate accelerator / brake inputs and steering wheel inputs; Represents a known nonlinear term; Represents an unknown nonlinear term; and Total disturbance of two types; Indicates the mass of the vehicle; Indicates the engine time constant; , This represents an unknown bounded bias signal.

3. The method according to claim 1, characterized in that, In step S3, Establish rules for queue obstacle avoidance and communication topology preservation: vehicle Adjacent vehicles Distance between and relative azimuth Defined as: ， Among them, when the vehicle With vehicles When the longitudinal position difference is zero, in order to eliminate the singularity in the calculation of the arctangent function, the azimuth angle is defined. To simultaneously meet the requirements of collision avoidance and uninterrupted communication links, the distance constraint is defined as follows: ,in and These represent the minimum permissible safe distance and the maximum effective communication range, respectively; and the range of velocity angle variation is set as follows: ;definition Then the angle constraint satisfies the inequality: ; Therefore, the spacing tracking error and azimuth tracking error are constructed: ， Design two new sets of preset time performance functions: ， and ， in, , , , , , All are positive parameters of the design; To achieve tracking error Small overshoot will affect the preset time performance function. and Build as ， in, It is an offset function and satisfies , and Indicates positive design parameters; To facilitate subsequent controller design, an error transformation method is proposed, which converts bounded tracking error into unconstrained error; the specific form of the transformation function is defined as follows: 。 4. The method according to claim 1, characterized in that, In step S4, Construct a new time-unified sliding surface, the specific expression of which is: ， and ， in, , , , , It is a design constant; , , , , , ; Furthermore, the longitudinal and transverse controllers are designed as follows: ， and ， ， in, , , , , , , It is a design constant; let ,and yes The estimate, and Indicates the estimation error; It is an offsetting term. It is a Nussbaum function designed that satisfies .

5. A heterogeneous vehicle fleet preset time unified sliding mode fault-tolerant control system, characterized in that, For performing the method according to any one of claims 1 to 4, comprising: Scene and model building module: Used to build multi-condition traffic scenarios, establish heterogeneous dynamics models, actuator failure models and saturation constraint models; Performance constraint module: used to formulate obstacle avoidance and communication topology rules, design preset time performance functions, construct asymmetric error boundaries and complete error transformation; Sliding mode fault-tolerant control module: used to construct a unified sliding surface for a preset time, generate a unified sliding mode fault-tolerant control signal for a preset time, and output it to the vehicle actuators of a heterogeneous vehicle fleet to achieve stable control under complex working conditions.

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