Path tracking control method and device considering side slip angle, equipment, medium and product

Abstract

The invention discloses a path tracking control method, device, equipment, medium and product considering a side slip angle, and relates to the field of path tracking, and the method comprises the steps: taking a path curvature as feedforward control compensation, employing the final value theorem of a frequency domain control system, carrying out the stable error analysis of a path according to the vehicle state information, and obtaining a path curve; obtaining a steady-state error of the system containing feed-forward control compensation; determining a course relation according to the steady-state error of the system comprising the feedforward control compensation; the course relation is the relation among the expected direction of automobile path tracking, the course angle of the automobile and the side slip angle of the mass center; constructing a cost function based on a controller according to the vehicle dynamics model; performing linear constraint integration on the cost function to obtain a quadratic programming problem; and solving the quadratic programming problem by using the course relation to obtain a front wheel steering angle. The path tracking precision and stability can be improved.

Description

Technical Field

[0001] The present application relates to the field of path tracking, and in particular to a path tracking control method, device, equipment, medium and product that takes into account the sideslip angle of the center of mass. Background Art

[0002] In the path-following problem of autonomous vehicles, the traditional goal of path-following control is to align the vehicle's heading with the tangent of the target path. However, when the vehicle is following a path with high curvature or at high speed, traditional methods are prone to deviations when aligning the vehicle's heading angle with the path tangent. This deviation is primarily due to the side slip effect of the vehicle when turning, namely the side slip angle of the center of mass. This side slip angle causes the vehicle's actual direction of motion to be inconsistent with the path tangent. Therefore, a method is needed to overcome the side slip effect and improve path-following accuracy and stability. Summary of the Invention

[0003] The purpose of this application is to provide a path tracking control method, device, equipment, medium and product that takes into account the sideslip angle of the center of mass, which can improve the path tracking accuracy and stability.

[0004] To achieve the above objectives, this application provides the following solutions.

[0005] In a first aspect, the present application provides a path tracking control method taking into account the sideslip angle of the center of mass, including: obtaining vehicle state information and a vehicle dynamics model; the vehicle state information includes vehicle positioning coordinates, vehicle speed, vehicle head orientation angle, center of mass sideslip angle and steady-state error vector.

[0006] The path curvature is used as feedforward control compensation. The terminal value theorem of frequency domain control system is used to analyze the path stability error according to the vehicle state information, and the steady-state error of the system including feedforward control compensation is obtained.

[0007] A heading relationship is determined based on the steady-state error of the system including feedforward control compensation; the heading relationship is the relationship between the desired direction of vehicle path tracking, the vehicle's heading angle and the center of mass sideslip angle.

[0008] A cost function is constructed based on the controller according to the vehicle dynamics model.

[0009] Performing linear constraint integration on the cost function, a quadratic programming problem is obtained.

[0010] The quadratic programming problem is solved using the heading relationship to obtain the front wheel turning angle.

[0011] In the second aspect, the present application provides a path tracking control device that takes into account the sideslip angle of the center of mass, including: an acquisition module for acquiring vehicle status information and a vehicle dynamics model; the vehicle status information includes vehicle positioning coordinates, vehicle speed, vehicle head orientation angle, center of mass sideslip angle and steady-state error vector.

[0012] The stable error analysis module is used to use the path curvature as feedforward control compensation. It uses the terminal value theorem of the frequency domain control system and the vehicle state information to perform stable error analysis on the path to obtain the steady-state error of the system including feedforward control compensation.

[0013] A heading relationship determination module is used to determine a heading relationship based on the steady-state error of the system including feedforward control compensation; the heading relationship is the relationship between the desired direction of vehicle path tracking, the vehicle's heading angle and the center of mass sideslip angle.

[0014] The cost function construction module is used to construct a cost function based on the controller according to the vehicle dynamics model.

[0015] The linear constraint integration module is used to perform linear constraint integration on the cost function to obtain a quadratic programming problem.

[0016] A solving module is used to solve the quadratic programming problem using the heading relationship to obtain a front wheel turning angle.

[0017] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any one of the above-described path tracking control methods considering the sideslip angle of the center of mass.

[0018] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned path tracking control methods considering the sideslip angle of the center of mass.

[0019] In a fifth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-mentioned path tracking control methods considering the sideslip angle of the center of mass.

[0020] According to the specific embodiments provided in this application, this application has the following technical effects.

[0021] The present application provides a path tracking control method, apparatus, equipment, medium and product that considers the sideslip angle of the center of mass. First, a stability error analysis is performed, and then a heading relationship is determined based on the stability error, wherein the heading relationship considers the sideslip angle of the center of mass of the vehicle. By considering the influence of the changes in the curvature of the path against the sideslip angle of the center of mass on the error state of the system, the smoothness of the vehicle when passing through sharp turns is improved. Finally, the cost function is linearly constrained and integrated to obtain a quadratic programming problem. The heading relationship is solved using quadratic programming stability to achieve vehicle control, thereby improving the path tracking accuracy and stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 This is a diagram of the application environment of a path tracking control method considering the sideslip angle of the center of mass in one embodiment of the present application.

[0024] Figure 2 A flow chart of a path tracking control method taking into account the sideslip angle of the center of mass provided in one embodiment of the present application.

[0025] Figure 3 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0027] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0028] The path tracking control method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send vehicle state information and vehicle dynamics model to the server 104. After the server 104 receives the vehicle state information and vehicle dynamics model, the server 104 uses the path curvature as feedforward control compensation for the vehicle state information and the vehicle dynamics model, and uses the terminal value theorem of the frequency domain control system to perform a stable error analysis on the path according to the vehicle state information to obtain the steady-state error of the system including feedforward control compensation; the heading relationship is determined based on the steady-state error of the system including feedforward control compensation; the heading relationship is the relationship between the desired direction of the vehicle path tracking, the heading angle of the vehicle and the sideslip angle of the center of mass; a cost function is constructed based on the controller according to the vehicle dynamics model; the cost function is linearly constrained and integrated to obtain a quadratic programming problem; the quadratic programming problem is solved using the heading relationship to obtain the front wheel steering angle. The server 104 can feed back the obtained front wheel steering angle to the terminal 102. In addition, in some embodiments, the path tracking control method can also be implemented independently by the server 104 or the terminal 102. For example, the terminal 102 can directly perform path tracking control based on the vehicle state information and the vehicle dynamics model, or the server 104 can obtain the vehicle state information and the vehicle dynamics model from a data storage system and perform path tracking control based on the vehicle state information and the vehicle dynamics model.

[0029] Terminal 102 may include, but is not limited to, various desktop computers, laptops, smartphones, tablet computers, IoT devices, and portable wearable devices. IoT devices may include smart speakers, smart TVs, smart air conditioners, and smart car devices. Portable wearable devices may include smart watches, smart bracelets, and head-mounted devices. Server 104 may be implemented as a standalone server or a server cluster consisting of multiple servers, or may be a cloud server.

[0030] In an exemplary embodiment, Figure 2 As shown, a path tracking control method considering the sideslip angle of the center of mass is provided. The method is executed by a computer device, specifically, it can be executed by a computer device such as a terminal or a server alone, or it can be executed by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used for explanation, including the following steps 201 to 206.

[0031] Step 201: Acquire vehicle state information and a vehicle dynamics model; the vehicle state information includes vehicle positioning coordinates, vehicle speed, vehicle head angle, center of mass sideslip angle, and steady-state error vector.

[0032] Step 202: Using the path curvature as feedforward control compensation, using the terminal value theorem of the frequency domain control system, and performing a stable error analysis on the path according to the vehicle state information, the steady-state error of the system including the feedforward control compensation is obtained.

[0033] Step 203: Determine a heading relationship based on the steady-state error of the system including the feedforward control compensation; the heading relationship is the relationship between the desired direction of the vehicle path tracking, the heading angle of the vehicle, and the sideslip angle of the center of mass.

[0034] Step 204: Construct a cost function based on the controller according to the vehicle dynamics model.

[0035] Step 205: Perform linear constraint integration on the cost function to obtain a quadratic programming problem.

[0036] Step 206: Solve the quadratic programming problem using the heading relationship to obtain the front wheel turning angle.

[0037] Implementing the above steps 201 to 206 can improve the path tracking accuracy and stability.

[0038] The present invention aims to improve the path tracking control method to take into account the vehicle's center of mass sideslip angle, thereby enhancing path tracking accuracy and stability, so that the vehicle can smoothly and safely track the target path even under extreme driving conditions.

[0039] In practical applications, path tracking error analysis is first performed, and then the controller is designed based on the error analysis results.

[0040] In the error analysis of step 202, the error state adjustment system is considered as shown below.

[0041] e(k+1)=A e e(k)+B e u(k)+C e κ(k) (1)

[0042] Where, e(k+1) represents the error at time k+1, represents the error state vector, e y Indicates lateral deviation, is the time derivative of the lateral deviation, represents the time derivative of the heading error. κ(k) represents the road curvature at time k. The yaw angle error of the car relative to the reference path is e ψ =ψ-θ des ,θdes Indicates the target heading angle, A e 、B e and C e is the regulation matrix, which is obtained from the system model. The closed-loop control system is designed based on the full-state feedback control law as follows.

[0043] e(k+1)=(A e -B e K)e(k)+C e κ(k) (2)

[0044] Feedforward control compensation related to the path curvature is introduced, and assuming that the vehicle travels at a constant speed on a road with a constant curvature, the steady-state error of the system including feedforward compensation can be obtained by using the terminal value theorem of the frequency domain control system.

[0045] In an exemplary embodiment, the steady-state error of the system including feedforward control compensation is expressed as:

[0046]

[0047] Among them, e ss is the steady-state error of the system including feedforward control compensation, z is the complex variable in the discrete-time system, I is the identity matrix, and A e is the first adjustment matrix, B e is the second adjustment matrix, C e is the third adjustment matrix, K is the feedback gain matrix, K ff is the feedforward control gain, k is the road curvature, k1 is the element of the feedback gain, k ff,1 is the feedforward gain, l f is the distance from the rear axle to the center of mass, m is the mass of the car, v is the speed of the car, k3 is the adjustment feedback gain, c αr is the front and rear cornering stiffness, c αf is the rear axle cornering stiffness, l r is the distance from the front axle to the center of mass, and σ is the vehicle configuration coefficient.

[0048] By adjusting the feedback gain k3 and the feedforward gain k ff,1 , the lateral displacement error can be guaranteed to converge to zero.

[0049] It can be concluded that the lateral yaw error will converge to the sideslip angle of the center of mass.

[0050] β=-e ψ =-(ψ-θ des )(4)

[0051] e ψis the heading angle deviation. By shifting the terms in the above equation, it can be deduced that the center of mass sideslip angle and the vehicle body heading angle will eventually converge to the tangent direction of the reference path, that is, the heading relationship in step 203.

[0052] In an exemplary embodiment, the heading relationship is expressed as:

[0053] (β+ψ)=θ des (5)

[0054] Among them, β is the sideslip angle of the center of mass, ψ is the body direction angle, θ des is the target heading angle.

[0055] When designing the controller, a dynamic model is used. The controller is a single-input single-output system. In an exemplary embodiment, the expression of the controller is:

[0056]

[0057] y i =Cx i (7)

[0058]

[0059]

[0060] C=[1 0 1] (12)

[0061] in, is the time derivative of the state vector of the inner control loop, A is the first Jacobian matrix, B is the second Jacobian matrix, C is the output matrix, x i is the state space, u i is the control quantity, B comp is the output matrix, y i is the controlled output, where the controlled output is p1, p2, p3, p4, p1 is the first coefficient matrix, v is the car speed, p2 is the second coefficient matrix, p3 is the third coefficient matrix, p4 is the fourth coefficient matrix, c αf is the rear axle cornering stiffness, l f is the distance from the rear axle to the center of mass, I z is the yaw moment of inertia, m is the mass of the car, g is the acceleration of gravity, ψ is the vehicle body orientation angle, c αr is the front and rear lateral stiffness, l r is the distance from the front axle to the center of mass.

[0062] The discrete form of the above formula is .

[0063]

[0064] is the discrete form of A, representing the A matrix at time k, is the discrete form of B, representing the B matrix at time K, u i (k) represents the control quantity at time k. The system output is:

[0065] y i =Cx i (14)

[0066] Where: The calculation method of the discrete matrix is ​​as follows.

[0067]

[0068] Δt represents the discretization step size, and They are all block matrices.

[0069] In an exemplary embodiment, the cost function expression is:

[0070]

[0071]

[0072] Where u is the upper bound N of the constraint i is the control time domain of the inner loop, k is the kth moment, y i,k is the output at time k, y r,k is the target value at time k, T is the matrix transpose, Q is the first optimization weight value, is the transpose of the deviation between the control value and the target value at time k, R is the second optimization weight value, x i (k+1) is the state space at time k+1, is the first Jacobian matrix at time k, is the second Jacobian matrix at time k, x i (k) is the state space at time k, u i (k) is the inner loop control input vector, B comp (k) is the output matrix at time k, y i is the controlled output, C is the output matrix, y min is the minimum output value set, x i is the state space, y max is the maximum output value set, u min is the minimum control quantity defined, u max is the maximum control quantity defined, Δu min is the minimum control deviation defined, Δu max is the maximum control deviation defined, x0 is the initial value of the state quantity of the prediction model, It is the feedback value of the inner loop state at the current moment. Defined as the initial state.

[0073] By transforming the cost function and integrating the linear constraints, the above optimal control problem is converted into a typical quadratic programming problem for solution. In an exemplary embodiment, the expression of the quadratic programming problem is:

[0074]

[0075] Among them, X is the vector to be optimized, P is the first equivalent optimization matrix, q T is the second equivalent optimization matrix, T is the matrix transpose, I is the constraint lower bound, is the constraint coefficient matrix, u is the constraint upper bound, y i (k) is the system output at time k, y i (k+N i |k) is the system output at time k+Ni predicted based on the system output at time k, Δu i (k) is the control increment at time K, Δu i (k+N i -1) is the control increment at time k+Ni based on the control increment at time k.

[0076] Finally, the sum of the sideslip angle and the yaw angle of the center of mass is output as the input of the controller, and the front wheel angle is finally output to control the rotational motion of the car.

[0077] This application first uses steady-state error analysis to derive the relationship between the desired direction of vehicle path tracking and the vehicle's heading angle and center of mass sideslip angle, namely (β+ψ) ss =θ des . Then, according to this relationship, an attitude regulator is designed, and the sum of the center of mass sideslip angle and the yaw angle is used as the input of the controller, and finally the front wheel angle is output to control the rotational motion of the car. At the same time, the feedback result of the car's rotational motion is input into the attitude regulator to realize a closed loop. When the smart car is tracking the trajectory, the path tracking accuracy can be improved, and the possibility of vehicle skidding can be reduced to a certain extent. At the same time, the front wheel angle can be used to resist the influence of the change in path curvature on the system error state, thereby improving the smoothness of the smart car when passing through sharp turns. The path tracking control method provided by the present application can have the following advantages.

[0078] 1. Higher Path Tracking Accuracy: The center of mass slip angle more accurately describes the vehicle's actual motion. Compared to traditional path tracking methods that only consider vehicle orientation, the center of mass slip angle method better reflects vehicle slip and steering deviation, thereby improving path tracking accuracy.

[0079] 2. Addressing Slippage: Vehicles are prone to sideways sliding when traveling at high speeds or on low-friction surfaces (such as wet, icy, or snowy roads). The center-of-mass angle path tracking method better accounts for the impact of sideways sliding on path tracking, helping to accurately track the path during slippage and improving vehicle stability and safety.

[0080] 3. Improved Dynamic Responsiveness: Path tracking that takes into account the center of mass deflection angle enables the controller to react more promptly to changes in vehicle posture and motion, particularly during high-speed cornering or emergency maneuvers. Faster dynamic response not only improves path tracking accuracy but also reduces vehicle oscillation, improving ride comfort.

[0081] 4. Reduce Path Tracking Error: During the path tracking process, the introduction of center of mass deviation can decompose the path tracking error into longitudinal and lateral errors, making them easier to control separately. This ensures longitudinal stability while minimizing lateral deviation, thus reducing overall path tracking error.

[0082] 5. Improved steering control smoothness: Traditional path-following methods are prone to large steering adjustments during sharp turns, affecting smoothness. By taking the slip angle into account, the controller can adjust the direction more smoothly during turns, reducing the discomfort caused by frequent steering corrections.

[0083] Based on the same inventive concept, embodiments of the present application further provide a path tracking control device for implementing the aforementioned path tracking control method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more of the path tracking control device embodiments provided below can be found in the aforementioned limitations of the path tracking control method and will not be further elaborated here.

[0084] In an exemplary embodiment, a path tracking control device considering a sideslip angle of a center of mass is provided, comprising:

[0085] The acquisition module is used to obtain vehicle status information and a vehicle dynamics model; the vehicle status information includes vehicle positioning coordinates, vehicle speed, vehicle head orientation angle, center of mass sideslip angle and steady-state error vector.

[0086] The stable error analysis module is used to use the path curvature as feedforward control compensation. It uses the terminal value theorem of the frequency domain control system and the vehicle state information to perform stable error analysis on the path to obtain the steady-state error of the system including feedforward control compensation.

[0087] A heading relationship determination module is used to determine a heading relationship based on the steady-state error of the system including feedforward control compensation; the heading relationship is the relationship between the desired direction of vehicle path tracking, the vehicle's heading angle and the center of mass sideslip angle.

[0088] The cost function construction module is used to construct a cost function based on the controller according to the vehicle dynamics model.

[0089] The linear constraint integration module is used to perform linear constraint integration on the cost function to obtain a quadratic programming problem.

[0090] A solving module is used to solve the quadratic programming problem using the heading relationship to obtain a front wheel turning angle.

[0091] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store front wheel angle data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a path tracking control method considering the sideslip angle of the center of mass is implemented.

[0092] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application and does not constitute a limitation on the computer device to which the solution of the present application is applied. A specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement. In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the above-mentioned method embodiments when executing the computer program.

[0093] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the above-mentioned method embodiments when executed by a processor.

[0094] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the above method embodiments are implemented.

[0095] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0096] In this application, all actions to obtain signals, information or data are carried out in compliance with the relevant data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0097] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0098] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0099] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0100] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A path tracking control method considering the sideslip angle of the center of mass, characterized in that: The path tracking control method comprises: Acquiring vehicle state information and a vehicle dynamics model; the vehicle state information includes vehicle positioning coordinates, vehicle speed, vehicle head orientation angle, center of mass sideslip angle, and steady-state error vector; Using path curvature as feedforward control compensation, the final value theorem of frequency domain control system is used to analyze the path stability error based on vehicle state information, and the steady-state error of the system including feedforward control compensation is obtained. Determining a heading relationship based on a steady-state error of the system including feedforward control compensation; the heading relationship being a relationship between a desired direction of vehicle path tracking, a heading angle of the vehicle, and a sideslip angle of the center of mass; constructing a cost function based on the controller according to the vehicle dynamics model; Performing linear constraint integration on the cost function to obtain a quadratic programming problem; The quadratic programming problem is solved using the heading relationship to obtain the front wheel turning angle.

2. The path tracking control method considering the sideslip angle of the center of mass according to claim 1, characterized in that: The steady-state error of the system including feedforward control compensation is expressed as: Among them, e ss is the steady-state error of the system including feedforward control compensation, z is the complex variable in the discrete-time system, I is the identity matrix, and A e is the first adjustment matrix, B e is the second adjustment matrix, C e is the third adjustment matrix, K is the feedback gain matrix, K ff is the feedforward control gain, κ is the road curvature, k1 is the element of the feedback gain, k ff,1 is the feedforward gain, l f is the distance from the rear axle to the center of mass, m is the mass of the car, v is the speed of the car, k3 is the adjustment feedback gain, c αr is the front and rear cornering stiffness, c αf is the rear axle cornering stiffness, l r is the distance from the front axle to the center of mass, and σ is the vehicle configuration coefficient.

3. The path tracking control method considering the sideslip angle of the center of mass according to claim 1, characterized in that: The expression of the heading relationship is: (β+ψ)=θ des Among them, β is the sideslip angle of the center of mass, ψ is the body direction angle, θ des is the target heading angle.

4. The path tracking control method considering the sideslip angle of the center of mass according to claim 1, characterized in that: The expression of the controller is: y i =Cx i C＝[1 0 1] in, is the time derivative of the state vector of the inner control loop, A is the first Jacobian matrix, B is the second Jacobian matrix, C is the output matrix, x i is the state space, u i is the control quantity, B comp is the output matrix, y i is the controlled output, p1 is the first coefficient matrix, v is the vehicle speed, p2 is the second coefficient matrix, p3 is the third coefficient matrix, p4 is the fourth coefficient matrix, c αf is the rear axle cornering stiffness, l f is the distance from the rear axle to the center of mass, I z is the moment of inertia of the heading angle, m is the mass of the car, g is the acceleration of gravity, ψ is the vehicle body heading angle, c αr is the front and rear lateral stiffness, l r is the distance from the front axle to the center of mass.

5. The path tracking control method considering the sideslip angle of the center of mass according to claim 1, characterized in that: The cost function expression is: y i =Cx i , and min ≤y i,k ≤y max , in min in i,k in max , Δu min ≤Δu i,k ≤Δu max , Among them, u is the upper bound of the constraint, N i is the control time domain of the inner loop, k is the kth moment, y i,k is the output at time k, y r,k is the target value at time k, T is the matrix transpose, Q is the first optimization weight value, is the transpose of the deviation between the control value and the target value at time k, R is the second optimization weight value, x i (k+1) is the state space at time k+1, is the first Jacobian matrix at time k, is the second Jacobian matrix at time k, x i (k) is the state space at time k, u i (k) is the inner loop control input vector, B comp (k) is the output matrix at time k, y i is the controlled output, C is the output matrix, y min is the minimum output value set, x i is the state space, y max is the maximum output value set, u min is the minimum control quantity defined, u max is the maximum control quantity defined, Δu min is the minimum control deviation defined, Δu max is the maximum control deviation defined, x0 is the initial value of the state quantity of the prediction model, It is the feedback value of the inner loop state at the current moment.

6. The path tracking control method considering the sideslip angle of the center of mass according to claim 1, characterized in that: The expression of the quadratic programming problem is: minize X T PX+q T X Among them, X is the vector to be optimized, P is the first equivalent optimization matrix, q T is the second equivalent optimization matrix, T is the matrix transpose, I is the constraint lower bound, is the constraint coefficient matrix, u is the constraint upper bound, y i (k) is the system output at time k, y i (k+N i |k) is the system output at time k+Ni predicted based on the system output at time k, Δu i (k) is the control increment at time k, Δu i (k+N i -1) is the control increment at time k+Ni based on the control increment at time k.

7. A path tracking control device taking into account the sideslip angle of the center of mass, characterized in that: The path tracking control device comprises: An acquisition module is used to acquire vehicle status information and a vehicle dynamics model; the vehicle status information includes vehicle positioning coordinates, vehicle speed, vehicle head orientation angle, center of mass sideslip angle, and steady-state error vector; The stability error analysis module is used to analyze the path stability error based on the vehicle state information using the final value theorem of the frequency domain control system and the path curvature as feedforward control compensation, and obtains the steady-state error of the system including the feedforward control compensation. A heading relationship determination module, configured to determine a heading relationship based on a steady-state error of the system including feedforward control compensation; the heading relationship being the relationship between a desired direction of vehicle path tracking, a heading angle of the vehicle, and a sideslip angle of the center of mass; a cost function construction module, configured to construct a cost function based on a controller according to the vehicle dynamics model; A linear constraint integration module is used to perform linear constraint integration on the cost function to obtain a quadratic programming problem; A solving module is used to solve the quadratic programming problem using the heading relationship to obtain a front wheel turning angle.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the path tracking control method considering the sideslip angle of the center of mass according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the path tracking control method considering the sideslip angle of the center of mass according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the path tracking control method considering the sideslip angle of the center of mass according to any one of claims 1 to 6 is implemented.

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