Vehicle control system and method, electronic equipment and medium

Abstract

The invention provides a vehicle control system and method, electronic equipment and a medium, and relates to the technical field of vehicles. The vehicle control system comprises a vehicle transverse control module and a vehicle longitudinal control module. Wherein the vehicle transverse control module comprises a first wheel steering angle control module, and the vehicle longitudinal control module comprises a speed tracking control module and an acceleration compensation module. The first wheel steering angle control module obtains a first wheel steering angle control amount of the first vehicle based on the path tracking control problem, wherein the first wheel is a front wheel or a rear wheel; the speed tracking control module obtains the expected acceleration of the first vehicle based on the speed tracking control problem; the acceleration compensation module uses a non-linear disturbance observer, estimates the value of a longitudinal control disturbance parameter according to the actual acceleration and the expected acceleration, and obtains the acceleration control quantity of the first vehicle accordingly. The control performance and robustness of vehicle control can be considered.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle control system, method, electronic equipment and medium. Background Art

[0002] The control performance and robustness of vehicle control are both important factors that affect the vehicle control effect. For example, the uncertainty of the vehicle's external environment affects the vehicle's longitudinal control performance. Therefore, it is necessary to take into account both control performance and robustness in the process of designing vehicle control. Summary of the invention

[0003] The embodiments of the present application provide a vehicle control system, method, electronic device and medium that can take into account both the control performance and robustness of vehicle control.

[0004] In a first aspect, an embodiment of the present application provides a vehicle control system, comprising: a vehicle lateral control module and a vehicle longitudinal control module; wherein the vehicle lateral control module comprises a first wheel steering angle control module, and the vehicle longitudinal control module comprises a speed tracking control module and an acceleration compensation module; the first wheel steering angle control module is used to solve a path tracking control problem for tracking a planned path, and obtain a first wheel steering angle control amount of a first vehicle, the first wheel being one of a front wheel and a rear wheel; wherein the planned path comprises a reference posture at a series of future time points, and the reference posture comprises at least one of a reference lateral position and a reference heading angle; the speed tracking control module , used to solve the speed tracking control problem for tracking the planned speed and obtain the expected acceleration of the first vehicle; wherein the planned speed includes the reference speed at a series of future time points; an acceleration compensation module, used to use a nonlinear disturbance observer, according to the actual acceleration of the first vehicle and the expected acceleration of the first vehicle, solve the first function, and obtain the value of the longitudinal control disturbance parameter; according to the value of the longitudinal control disturbance parameter and the expected acceleration of the first vehicle, obtain the acceleration control amount of the first vehicle; wherein the first function includes the expected acceleration of the vehicle, the actual acceleration of the vehicle, the longitudinal control disturbance parameter and the correlation relationship between the calibration parameters of the nonlinear disturbance observer.

[0005] In the embodiment of the present application, the first wheel steering angle control module and the speed tracking control module are independent of the vehicle chassis interface, and the control performance requirements are met by the designed high-performance control law to achieve precise control of path tracking and speed tracking, while the acceleration compensation module depends on the vehicle chassis interface, and the requirements for resisting unknown interference are met by the designed strong robustness control law to ensure the robustness of vehicle control, so that the vehicle control system can take into account both control performance and robustness.

[0006] By using a nonlinear disturbance observer to perform real-time estimation and feed-forward compensation of the longitudinal control disturbance term, the vehicle control can still exhibit high performance of "fast convergence, high accuracy and strong robustness" even when there is uncertainty in the vehicle's external environment and the modeling mechanism of the vehicle control nominal model.

[0007] Optionally, the vehicle lateral control module also includes a second wheel steering angle control module; the second wheel steering angle control module is used to obtain the second wheel steering angle control amount of the first vehicle based on the correlation relationship between the front wheel steering angle and the rear wheel steering angle of the first vehicle, and the first wheel steering angle control amount of the first vehicle, the second wheel being the other of the front wheel and the rear wheel; wherein the correlation relationship is obtained based on the maximum value of the front wheel steering angle of the first vehicle and the maximum value of the rear wheel steering angle of the first vehicle.

[0008] The second wheel steering angle control module relies on the vehicle chassis interface and meets the requirements of resisting unknown interference through the designed strong robust control law to ensure the robustness of the vehicle's lateral control.

[0009] Optionally, the first function is obtained according to a longitudinal control model, where the longitudinal control model includes a desired acceleration of the vehicle, an actual acceleration of the vehicle, and a correlation relationship between a longitudinal control disturbance parameter and a first-order inertia link parameter.

[0010] The burden of the speed tracking control module can be reduced by using a nonlinear disturbance observer to perform real-time estimation and feedforward compensation of the longitudinal control disturbance term.

[0011] Optionally, the acceleration compensation module is used to use a tracking differentiator to solve a second function according to the actual speed of the first vehicle to obtain the actual acceleration of the first vehicle; wherein the second function includes a correlation relationship between the actual speed of the vehicle, the actual acceleration of the vehicle and calibration parameters of the tracking differentiator.

[0012] By using a tracking differentiator to estimate the actual acceleration of the vehicle based on the actual speed of the vehicle, accurate acquisition of the actual acceleration of the vehicle can be achieved.

[0013] Optionally, solving the speed tracking control problem for tracking the planned speed includes: solving a third function using a fast terminal sliding mode control law; wherein the third function is obtained based on a fast terminal sliding mode surface including a speed tracking error, and the speed tracking error is used to describe the error between a reference speed and a vehicle speed predicted based on the expected acceleration.

[0014] The fast terminal sliding mode control law can make the speed tracking error converge to zero within a finite time, making the vehicle longitudinal control present high performance of "fast convergence, high accuracy and strong robustness".

[0015] Optionally, solving a path tracking control problem for tracking a planned path includes: solving a quadratic programming problem, wherein the quadratic programming problem is obtained by transforming the path tracking control problem, and constraints of the quadratic programming problem are obtained based on vehicle kinematic equations and Lagrangian functions.

[0016] The path tracking control problem can be transformed from a nonlinear optimization problem into a quadratic programming problem with linear optimization, and the first wheel steering angle control value can be obtained by solving the quadratic programming problem.

[0017] Optionally, any solution result includes state quantities reflecting the vehicle posture and the first wheel steering angle at a series of future time points, control quantities reflecting the first wheel steering angular velocity, and values ​​of Lagrange multipliers; solving the quadratic programming problem includes: if there is a solution result of the previous cycle, solving the quadratic programming problem based on the solution result of the previous cycle to obtain a state quantity increment; obtaining the solution result of the current cycle based on the obtained state quantity increment and the solution result of the previous cycle; if the set condition is met, the first wheel steering angle control quantity of the first vehicle is the first wheel steering angle at the next moment obtained in the current cycle; the set condition includes that the absolute value of the obtained state quantity increment is not greater than the set tolerance; if the set condition is not met, executing the steps of solving the quadratic programming problem again.

[0018] The quadratic programming problem is solved cyclically based on the increment of the solution results obtained from two adjacent loops, and the increment of the state quantity at the end of the loop is limited to be small enough, so as to support the accurate acquisition of the steering angle control quantity of the first vehicle.

[0019] In a second aspect, an embodiment of the present application provides a vehicle control method, including: solving a path tracking control problem for tracking a planned path, obtaining a first wheel steering angle control amount of a first vehicle, the first wheel being one of a front wheel and a rear wheel; wherein the planned path includes a reference posture at a series of future time points, and the reference posture includes at least one of a reference lateral position and a reference heading angle; solving a speed tracking control problem for tracking a planned speed, obtaining an expected acceleration of the first vehicle; wherein the planned speed includes a reference speed at a series of future time points; using a nonlinear disturbance observer, solving a first function according to an actual acceleration of the first vehicle and an expected acceleration of the first vehicle, obtaining a value of a longitudinal control disturbance parameter; obtaining an acceleration control amount of the first vehicle according to the value of the longitudinal control disturbance parameter and the expected acceleration of the first vehicle; wherein the first function includes an association relationship between the expected acceleration of the vehicle, the actual acceleration of the vehicle, the longitudinal control disturbance parameter and a calibration parameter of the nonlinear disturbance observer.

[0020] In a third aspect, an embodiment of the present application provides an electronic chip, comprising: a processor, which is used to execute computer program instructions stored in a memory, wherein when the computer program instructions are executed by the processor, the electronic chip is triggered to execute any method as in the first aspect.

[0021] In a fourth aspect, an embodiment of the present application provides an electronic device, comprising at least one processor, wherein the processor and a memory are coupled, the memory is used to store computer program instructions, and the processor is used to execute the computer program instructions, wherein when the computer program instructions are executed by the processor, the electronic device is triggered to execute a method as described in any one of the first aspects.

[0022] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program runs on a computer, the computer executes any method in the first aspect.

[0023] In a sixth aspect, an embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is run on a computer, the computer executes any method in the first aspect.

[0024] The technical effects of the aforementioned aspects can be referenced to each other and will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments are briefly introduced below.

[0026] Figure 1 A block diagram of a vehicle control system provided in an embodiment of the present application;

[0027] Figure 2 A block diagram of another vehicle control system provided in an embodiment of the present application;

[0028] Figure 3 A schematic diagram reflecting a vehicle kinematic model provided in an embodiment of the present application;

[0029] Figure 4 A schematic diagram reflecting the path tracking control problem provided in an embodiment of the present application;

[0030] Figure 5 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to better understand the technical solution of the present application, the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0032] It should be clear that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0033] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0034] It should be understood that the term "at least one" used in this article refers to one or more, and "plurality" refers to two or more. The term "and / or" used in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. Among them, A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b and c can be represented by: a, b, c, ab, ac, bc, or abc, wherein a, b, c can be single or multiple.

[0035] It should be understood that, although the terms first, second, etc. may be used to describe the set thresholds in the embodiments of the present application, these set thresholds should not be limited to these terms. These terms are only used to distinguish the set thresholds from each other. For example, without departing from the scope of the embodiments of the present application, the first set threshold may also be referred to as the second set threshold, and similarly, the second set threshold may also be referred to as the first set threshold.

[0036] refer to Figure 1 An embodiment of the present application provides a vehicle control system for controlling a vehicle 100, in which lateral control and longitudinal control are decoupled, and the longitudinal control module includes a fast terminal sliding mode control law 101, a tracking differentiator 1021 and a nonlinear disturbance observer 1022, and the lateral control module includes a top-level lateral control module 103 and a bottom-level lateral allocation module 104.

[0037] Exemplarily, the vehicle 100 may be a four-wheel steering vehicle, a front-wheel steering vehicle, a rear-wheel steering vehicle, a steer-by-wire vehicle, or a non-steer-by-wire vehicle. Taking a front-wheel steering vehicle as an example, compared to a front-wheel steering vehicle (with the front wheels as driving wheels), a four-wheel steering vehicle can synchronously control the front and rear wheels to achieve steering action by adding rear wheel steering angle control, thereby improving the maneuverability of the vehicle during parking and driving. For example, a four-wheel steering vehicle can more easily complete parking operations in narrow environments.

[0038] Figure 1 The vehicle control system shown is designed based on a layered architecture, so that the lateral and longitudinal controls are decoupled, the front and rear wheel controls in the lateral control are decoupled, and the control performance and robustness indicators in the longitudinal control are decoupled.

[0039] Figure 1 In the vehicle control system shown, the top-level lateral control module 103 solves the front wheel steering angle control quantity that can realize path tracking control based on the planned path; the bottom-level lateral allocation module 104 solves the rear wheel steering angle control quantity based on the front wheel steering angle control quantity output by the top-level lateral control module 103 and the correlation between the front and rear wheel steering angles.

[0040] The planned path can include the reference lateral position y of the vehicle at a series of future time points ref and the reference heading angle By controlling the steering angles of the front and rear wheels of the vehicle, lateral control of the vehicle can be achieved.

[0041] In one implementation, the top-level lateral control module 103 may calculate and output a desired front wheel steering angle based on a tracking error (such as a lateral position error and a heading angle error) of the planned path.

[0042] The top-level lateral control module 103 is independent of the vehicle chassis interface and meets the control performance requirements by designing high-performance control laws to ensure the lateral control performance of the vehicle. The bottom-level lateral distribution module 104 depends on the vehicle chassis interface and meets the requirements of resisting unknown interference by designing strong robustness control laws to ensure the robustness of the vehicle lateral control.

[0043] By limiting the vehicle's lateral control strategy to a decoupled calculation process of the desired front wheel steering angle and the desired rear wheel steering angle based on a hierarchical architecture, the closed-loop control effect of the front and rear wheel steering angles of a four-wheel steering vehicle during parking can be made more human-like, safer and more comfortable.

[0044] Figure 1 In the vehicle control system shown in FIG. 1 , the fast terminal sliding mode control law 101 solves the expected acceleration a that can achieve speed tracking control based on the planned speed. cThat is, the fast terminal sliding mode control law 101 is used to achieve the purpose of planning speed tracking to ensure the longitudinal control performance of the vehicle.

[0045] The planned speed may include the reference speed v of the vehicle at a series of future time points. ref By controlling the acceleration of the vehicle, longitudinal control of the vehicle can be achieved.

[0046] In one implementation, the fast terminal sliding mode control law 101 may calculate and output a desired vehicle acceleration based on a tracking error of the planned speed.

[0047] Figure 1 In the vehicle control system shown in FIG. 1 , the tracking differentiator 1021 estimates the actual acceleration of the vehicle (i.e., the estimated value of the actual acceleration of the vehicle) according to the actual speed of the vehicle. ); The nonlinear disturbance observer 1022 estimates the longitudinal control disturbance term d in real time according to the actual vehicle acceleration estimated by the tracking differentiator 1021 and the reference acceleration obtained by solving the fast terminal sliding mode control law 101 to obtain the disturbance estimation Then, the desired acceleration is feedforward compensated according to the disturbance estimation d to obtain the acceleration control amount. That is, the tracking differentiator 1021 and the nonlinear disturbance observer 1022 are combined to realize the estimation and feedforward compensation of the vehicle control disturbance to ensure the robustness of the vehicle longitudinal control.

[0048] For example, the longitudinal control disturbance term may include the uncertainty of the external environment of the vehicle, the uncertainty of the nominal model modeling mechanism used to design the vehicle controller, etc. The nonlinear disturbance observer 1022 can reduce the burden of the fast terminal sliding mode control law and improve the longitudinal control performance of the vehicle by performing real-time estimation and feedforward compensation on the longitudinal control disturbance term.

[0049] By limiting the vehicle's longitudinal control strategy to use a nonlinear disturbance observer to perform real-time estimation and feed-forward compensation of the longitudinal control disturbance term, the vehicle control can still exhibit high performance of "fast convergence, high accuracy and strong robustness" even when there is uncertainty in the vehicle's external environment and the modeling mechanism of the vehicle control nominal model.

[0050] The fast terminal sliding mode control law 101 is independent of the vehicle chassis interface. The control performance requirements are met by designing a high-performance control law to ensure the longitudinal control performance of the vehicle. The acceleration compensation module composed of the tracking differentiator 1021 and the nonlinear disturbance observer 1022 depends on the vehicle chassis interface. The requirements for resisting unknown interference are met by designing a strong robustness control law to ensure the robustness of the longitudinal control of the vehicle.

[0051] The vehicle control system can achieve driving control of the vehicle by decoupling the vehicle's lateral and longitudinal directions.

[0052] in this way, Figure 1 The vehicle control system shown may have at least the following features:

[0053] (1) The fast terminal sliding mode control law and the top-level lateral control module are independent of the vehicle chassis interface. The high-performance control law is designed to meet the control performance requirements to achieve precise control of path tracking and speed tracking. The acceleration compensation module and the bottom-level lateral distribution module rely on the vehicle chassis interface. The strong robustness control law is designed to meet the requirements of anti-unknown interference to ensure the robustness of vehicle control. In this way, the vehicle control system can take into account both control performance and robustness.

[0054] (2) By decoupling lateral control and longitudinal control through a hierarchical architecture, and decoupling the two control variables of the front wheel steering angle and the rear wheel steering angle in the vehicle lateral control, and decoupling the control performance and robustness indicators in the vehicle longitudinal control, the vehicle control presents a high performance of "fast convergence, high accuracy and strong robustness".

[0055] (3) When a four-wheel steering vehicle is driving, the front wheel steering angle and rear wheel steering angle control commands and the vehicle's yaw motion present a complex nonlinear relationship, which affects the vehicle's dynamic response characteristics. Figure 1 The illustrated embodiment can cope with the influence of the complex nonlinear relationship on the dynamic response characteristics of the vehicle by decoupling the front and rear wheel controls and by designing a strong robust control law, which is beneficial to the robustness of the vehicle's lateral control.

[0056] During the driving process, the driving and braking control commands and the longitudinal motion of the vehicle also present a complex nonlinear relationship. The uncertainty of the external environment in which the vehicle is located and the uncertainty of the nominal model modeling mechanism used in the design of the vehicle controller will also affect the dynamic response characteristics of the vehicle. Figure 1 The illustrated embodiment can cope with the influence of the complex nonlinear relationship and uncertainty on the dynamic response characteristics of the vehicle by decoupling the control performance and robustness indicators in the longitudinal control of the vehicle and performing real-time estimation and feedforward compensation of the longitudinal control disturbance term through a nonlinear disturbance observer, which is beneficial to the robustness of the longitudinal control of the vehicle.

[0057] Thus, the vehicle is based on Figure 1 The vehicle control system shown is capable of performing nonlinear robust vehicle control, thereby achieving precise tracking control of the planned trajectory and planned speed.

[0058] (4) Through layered architecture design, the vehicle control requirements of “easy to implement, easy to maintain, easy to expand and easy to upgrade” are met.

[0059] (5) The vehicle control system has the characteristic of backward compatibility, that is, it can be applied not only to the vehicle control of four-wheel steering vehicles, but also to the vehicle control of front-wheel steering vehicles. Therefore, it can serve as the basis for creating a "high-performance, platform-based, and vehicle-type decoupled" general vehicle control architecture.

[0060] (6) Figure 1 When the vehicle control system shown is applied to the parking scenario of a four-wheel steering vehicle, the four-wheel steering vehicle can synchronously control the front and rear wheels to achieve steering action based on the vehicle control system, and can achieve precise tracking and control of the parking planning path, so that the four-wheel steering vehicle has better maneuverability and flexibility during parking, and it is easier to complete parking operations in narrow spaces.

[0061] refer to Figure 2 An embodiment of the present application provides a vehicle control system 200, which includes: a vehicle lateral control module 210 and a vehicle longitudinal control module 220; wherein the vehicle lateral control module 210 includes a first wheel steering angle control module 211, and the vehicle longitudinal control module 220 includes a speed tracking control module 221 and an acceleration compensation module 222.

[0062] The vehicle control system 200 is applicable to vehicle control scenarios such as parking scenarios and driving scenarios. During the parking process, the vehicle is in a low-speed and large-angle motion state, and the vehicle control system 200 supports the vehicle to achieve accurate and stable parking in the parking scenario.

[0063] The vehicle control system 200 is applicable to vehicles such as front-wheel steering vehicles, rear-wheel steering vehicles, and four-wheel steering vehicles. When the vehicle control system 200 is used to control a front-wheel steering vehicle, the first wheel is the front wheel, and when the vehicle control system 200 is used to control a rear-wheel steering vehicle, the first wheel is the rear wheel. When the vehicle control system 200 is used to control a four-wheel steering vehicle, the first wheel may be the front wheel.

[0064] In the vehicle control system 200, the first wheel steering angle control module 211 solves a path tracking control problem for tracking a planned path, and obtains a first wheel steering angle control value of a first vehicle, where the first wheel is one of a front wheel and a rear wheel. The planned path includes a reference posture at a series of future time points, and the reference posture includes at least one of a reference lateral position and a reference heading angle.

[0065] In one embodiment, the first wheel steering angle control module 211 may be the top-level lateral control module 103 .

[0066] The path tracking control problem is preferably used to track the planned path by controlling the first wheel steering angle of the first vehicle. The first wheel steering angle of the first vehicle may be controlled according to the first wheel steering angle control amount obtained by solving the path tracking control problem.

[0067] In one embodiment, a path tracking control problem including a first wheel steering angle control amount and a speed tracking control problem including a reference acceleration can be established based on a vehicle coordinate system. The lateral and longitudinal directions described in this embodiment can be lateral and longitudinal directions based on the vehicle coordinate system.

[0068] In one embodiment, the constraint conditions of the path tracking control problem can be obtained based on the vehicle control dynamics model, the maximum / minimum value of the wheel steering angle, etc.

[0069] Taking the first wheel as the front wheel as an example, in one embodiment, the path tracking control problem can be solved repeatedly to obtain the front wheel steering angle control amount that meets the path tracking requirement. The path tracking requirement can be that the difference between the predicted trajectory and the planned path meets the requirement (i.e., the vehicle is controlled to travel along the planned path in the lateral direction), and the predicted trajectory is the predicted vehicle travel trajectory in the future when the vehicle is controlled by the solved front wheel steering angle control amount.

[0070] If the front wheel steering angle obtained in the current cycle does not meet the path tracking requirement, the next loop solution of the path tracking control problem can be performed based on the front wheel steering angle obtained in the current cycle, so that as the number of loop solutions increases, the front wheel steering angle control amount obtained by the solution can be more likely to meet the path tracking requirement. In this way, the path tracking control problem can be solved repeatedly until the front wheel steering angle that meets the path tracking requirement is solved, and this is used as the front wheel steering angle control amount to control the front wheel steering angle of the vehicle to perform lateral control on the vehicle.

[0071] The reference posture in the planned path may include a reference lateral position and / or a reference heading angle. By solving the front wheel steering angle based on the reference lateral position and / or the reference heading angle, and using the solved front wheel steering angle to control the vehicle, the lateral control effect of the vehicle tracking the planned path can be achieved.

[0072] The planned path may include reference postures at a series of future time points, such as reference postures at steps 0 to N. The state of the vehicle at the next moment can be predicted based on the state of the vehicle at the current moment (such as posture) and control quantity (such as front wheel steering angle). In this way, the state and control quantity at steps 0 to N can be predicted in sequence through iterative solution in any loop solution process, and the predicted series of state quantities can reflect the above-mentioned predicted trajectory.

[0073] In the vehicle control system 200, the speed tracking control module 221 solves the speed tracking control problem for tracking the planned speed to obtain the expected acceleration of the first vehicle; wherein the planned speed includes reference speeds at a series of future time points.

[0074] In one embodiment, the speed tracking control module 221 may be the above-mentioned fast terminal sliding mode control law 101 .

[0075] The speed tracking control problem is preferably used to track the planned speed by controlling the acceleration of the first vehicle. The acceleration of the first vehicle can be controlled according to the desired acceleration obtained by solving the speed tracking control problem after acceleration disturbance compensation.

[0076] In the vehicle control system 200, the acceleration compensation module 222 uses a nonlinear disturbance observer to solve a first function according to the actual acceleration of the first vehicle and the expected acceleration of the first vehicle to obtain the value of the longitudinal control disturbance parameter; according to the value of the longitudinal control disturbance parameter and the expected acceleration of the first vehicle, the acceleration control amount of the first vehicle is obtained; wherein the first function includes the expected acceleration of the vehicle, the actual acceleration of the vehicle, the longitudinal control disturbance parameter and the correlation relationship between the calibration parameters of the nonlinear disturbance observer.

[0077] The vehicle longitudinal control module may control the acceleration of the first vehicle according to the acquired acceleration control amount.

[0078] In one embodiment, the value of the longitudinal control disturbance parameter and the desired acceleration of the first vehicle may be added to obtain the acceleration control amount of the first vehicle.

[0079] In one embodiment, the speed of the vehicle, that is, the actual speed of the vehicle, can be collected according to the on-board sensor, and the actual acceleration of the vehicle can be estimated according to the actual speed of the vehicle.

[0080] In one feasible implementation, the longitudinal control disturbance term can represent the combination of disturbance factors such as the uncertainty of the external environment in which the vehicle is located, the uncertainty of the nominal model modeling mechanism used to design the vehicle controller, and the complex nonlinear relationship between the drive and brake control commands and the longitudinal motion of the vehicle.

[0081] By using a nonlinear disturbance observer to estimate the value of the longitudinal control disturbance parameter in real time based on the actual acceleration and the expected acceleration, and then performing feedforward compensation of the acceleration, an acceleration control amount that meets the speed tracking requirement can be obtained. The speed tracking requirement can be that the difference between the predicted speed and the planned speed meets the requirement (i.e., the vehicle is controlled to travel at the planned speed in the longitudinal direction), and the predicted speed is the predicted vehicle speed in the future when the vehicle is controlled by the obtained acceleration control amount.

[0082] Since the acceleration control amount obtained after compensation eliminates the influence of the longitudinal control interference term on the longitudinal control of the vehicle, compared with the reference acceleration, the acceleration control amount can better meet the speed tracking requirements and ensure the longitudinal control effect of the vehicle.

[0083] In order to make the vehicle control system 200 not only applicable to four-wheel steering vehicles, but also backward compatible to be applicable to front-wheel or rear-wheel steering vehicles, in one embodiment of the present application, reference Figure 2 The vehicle lateral control module 210 also includes a second wheel steering angle control module 212; the second wheel steering angle control module 212 obtains the second wheel steering angle control amount of the first vehicle according to the correlation between the front wheel steering angle and the rear wheel steering angle of the first vehicle, and the first wheel steering angle control amount of the first vehicle, and the second wheel is the other of the front wheel and the rear wheel; wherein the correlation is obtained according to the maximum value of the front wheel steering angle of the first vehicle and the maximum value of the rear wheel steering angle of the first vehicle.

[0084] The second wheel steering angle of the first vehicle may be controlled according to the obtained second wheel steering angle control amount.

[0085] In one embodiment, the second wheel steering angle control module 212 may be the bottom-level lateral distribution module 104 .

[0086] After the top-level lateral control module obtains the front wheel steering angle control value, the bottom-level lateral distribution module can calculate and output the rear wheel steering angle control value based on it, thereby realizing the perfect decoupling control of the front wheel steering angle and the rear wheel steering angle of the four-wheel steering vehicle.

[0087] The second wheel steering angle control module relies on the vehicle chassis interface and meets the requirements of resisting unknown interference through the designed strong robust control law to ensure the robustness of the vehicle's lateral control.

[0088] The vehicle control system 200 can achieve a reasonable distribution of the front and rear wheel steering angle control amounts and improve lateral control accuracy by decoupling the front and rear wheel steering angles and combining the correlation between the front and rear wheel steering angles.

[0089] refer to Figure 3 The schematic diagram of the vehicle kinematic model reflecting the four-wheel steering vehicle 301 is shown. In one embodiment, the rear wheel steering angle δ of the vehicle can be determined. r With the front wheel steering angle δ f The following formula (1) is satisfied.

[0090] L f tanδ r =L r tanδ f (1)

[0091] In formula (1), L f and L r They are the distances from point A on a four-wheel steering vehicle to the front axle and rear axle of the vehicle respectively.

[0092] In formula (1),

[0093] Among them, the maximum values ​​of the front and rear wheel steering angles of the four-wheel steering vehicle are δ fmax and δ rmax , L is the wheelbase of the four-wheel steering vehicle.

[0094] It can be seen from formula (1) that the bottom-level lateral distribution module can calculate and output the rear wheel steering angle control amount based on the front wheel steering angle control amount output by the top-level lateral control module by comprehensively considering the maximum value constraints of the front and rear wheel steering angles of the four-wheel steering vehicle.

[0095] Exemplarily, the correlation between the front and rear wheel steering angles of the first vehicle can be expressed as formula (1). By substituting the first wheel steering angle control value output by the first wheel steering angle control module 211 into formula (1), the second wheel steering angle control value of the first vehicle can be obtained.

[0096] In one embodiment of the present application, solving a path tracking control problem for tracking a planned path includes: solving a quadratic programming problem, wherein the quadratic programming problem is obtained by transforming the path tracking control problem, and the constraints of the quadratic programming problem are obtained based on the vehicle kinematic equations and the Lagrangian function.

[0097] The path tracking control problem is used to solve the first wheel steering angle control quantity that meets the path tracking requirements. The path tracking control problem can be converted into a quadratic programming problem based on the vehicle kinematic equation and the Lagrangian function, and the first wheel steering angle control quantity can be obtained by cyclically solving the quadratic programming problem. That is, the path tracking control problem can be converted from a nonlinear optimization problem to a linear band optimized quadratic programming problem, and the first wheel steering angle control quantity can be obtained by solving the quadratic programming problem.

[0098] In one embodiment of the present application, any solution result includes a state quantity reflecting the vehicle posture and the first wheel steering angle at a series of future time points, a control quantity reflecting the first wheel steering angular velocity, and a value of the Lagrange multiplier. Based on this, the step of solving the quadratic programming problem may include:

[0099] If there is a solution result of the previous cycle, the quadratic programming problem is solved based on the solution result of the previous cycle to obtain the state quantity increment; the solution result of the current cycle is obtained according to the obtained state quantity increment and the solution result of the previous cycle; if the set condition is met, the first wheel steering angle control amount of the first vehicle is the first wheel steering angle at the next moment obtained in the current cycle; the set condition includes that the absolute value of the obtained state quantity increment is not greater than the set tolerance.

[0100] In the process of cyclically solving the quadratic programming problem, the actual lateral position of the vehicle at the future time may be the predicted result of the lateral position of the vehicle, and the actual heading angle of the vehicle at the future time may be the predicted result of the heading angle of the vehicle.

[0101] Since there is no solution result of the previous cycle in the first loop solution process, the first loop solution process can be performed based on the preset initial information, and then another loop solution is performed based on the solution result of the previous cycle (that is, the k+1th loop solution is performed based on the solution result of the kth cycle).

[0102] The state increment is the difference between the state quantities obtained by solving the quadratic programming problem in two consecutive cycles. By always performing a cycle solution based on the result of the previous cycle solution, the solution result can better meet the path tracking requirements as the number of cycle solutions increases.

[0103] If the absolute value of the state quantity increment is not greater than the set tolerance, it can be said that the difference between the state quantities obtained by two adjacent loop solutions is small, that is, the state quantities obtained by two adjacent loop solutions are similar, so there is no need to continue the loop, and the loop solution process can be ended.

[0104] On the contrary, if the absolute value of the state quantity increment is greater than the set tolerance, it means that the state quantities obtained by two adjacent loops are quite different, so it is necessary to continue looping until the tolerance requirement is met. Thus, in one embodiment of the present application, if the set condition is not met, the step of solving the quadratic programming problem is executed again.

[0105] The quadratic programming problem is solved cyclically based on the increment of the solution results obtained from two adjacent loops, and the increment of the state quantity at the end of the loop is limited to be small enough, so as to support the accurate acquisition of the steering angle control quantity of the first vehicle.

[0106] The following takes the case where the first wheel is the front wheel, the vehicle is a wire-controlled four-wheel steering vehicle, and the planned path is a planned parking path as an example to illustrate a feasible implementation process of the first wheel steering angle control module 211 solving the front wheel steering angle control value. The relevant technical implementation is also applicable to embodiments in which the first wheel is a rear wheel, a front-wheel or rear-wheel steering vehicle, an on-the-spot steering vehicle, and the planned path is a planned driving path.

[0107] refer to Figure 3 , using x a ,y a and The position and posture of point A on the steer-by-wire vehicle (i.e., the lateral position and longitudinal position of point A in the OXY coordinate system and the heading angle of the steer-by-wire vehicle) are expressed using v a The speed of point A on the 4WD vehicle is expressed in ω f represents the steering angular velocity of the front wheels of the wire-controlled four-wheel steering vehicle. Based on the instantaneous center of velocity theorem, the kinematic equation of the wire-controlled four-wheel steering vehicle described by equation (2) can be established.

[0108]

[0109] Based on formula (2), the system state vector is defined as The control vector is u=[ω f ] T Therefore, equation (2) can be rewritten as equation (3).

[0110]

[0111] The fourth-order Runge-Kutta integration method is used to discretize equation (3), and equation (4) can be obtained.

[0112]

[0113] In formula (4), x(k) represents the state vector at the kth step (or the state vector at the kth time point in the future), and x(k+1) represents the state vector at the k+1th step.

[0114] The calculation of step size h, coefficient K1, coefficient K2, coefficient K3 and coefficient K4 in formula (4) is shown in formula (5).

[0115]

[0116] In formula (5), t f and N are the prediction duration and number of discrete points of model predictive control, respectively.

[0117] Combining equations (4) and (5), it can be seen that the state vector at the k+1 step can be predicted based on the state vector and control vector at the k-th step.

[0118] refer to Figure 4 By considering the maximum / minimum constraints of the front wheel steering angle and the maximum / minimum constraints of the front wheel steering angular velocity of the wire-controlled four-wheel steering vehicle, and in the vehicle coordinate system Ax v y vThe following represents the planned path 401 to be tracked. Based on equation (4), the top-level lateral control problem (i.e., path tracking control problem) of the wire-controlled four-wheel steering vehicle can be transformed into a nonlinear optimization problem described by equation (6).

[0119]

[0120] In formula (6), ω fmax is the maximum value of the front wheel steering angular velocity of the wire-controlled four-wheel steering vehicle; Q and R are weight coefficients; x0 is the initial state vector of the system.

[0121] The nonlinear optimization problem described by equation (6) is abstracted into the nonlinear optimization problem described by equation (7).

[0122]

[0123] The constraint condition of the nonlinear optimization problem described by equation (7) is equation (8).

[0124]

[0125] In formula (8), L(x, λ, μ) is the Lagrangian function of the nonlinear optimization problem and can be expressed as formula (9).

[0126]

[0127] Using {x k ,λ k ,μ k} represents the k-th loop solution result of the nonlinear optimization problem to be solved, and {x k+1 ,λ k+1 ,μ k+1} represents the k+1th loop solution result of the nonlinear optimization problem to be solved, and the loop increment δ is shown in formula (10).

[0128]

[0129] Using Taylor's formula in {x k ,λ k ,μ k}, we make a second-order approximation to the Lagrangian function described by equation (9), and we get equation (11).

[0130]

[0131] In formula (11), and They can be expressed as formula (12) and formula (13) respectively.

[0132]

[0133]

[0134] Among them, g k , A ek , A ik 、a k 、c k and Z k They can be expressed as equations (14) to (19) respectively.

[0135]

[0136]

[0137]

[0138] a k =[a1(x k ) a2(x k ) … a p (x k )] T (17)

[0139] c k =[c1(x k ) c2(x k ) … c q (x k )] T (18)

[0140]

[0141] By taking the derivative of equation (11) with respect to the cycle increment δ, we can obtain equation (20).

[0142]

[0143] make Then, by combining equation (20), equation (10), equation (12) and equation (13), we can get equation (21).

[0144]

[0145] Based on equation (21), a first-order linear approximation is performed on the constraints of the original optimization problem described by equation (8), and equation (22) is obtained.

[0146]

[0147] Using formula (21) And equation (22), the constraints of the original optimization problem described by equation (8) are approximated as equation (23).

[0148]

[0149] Formula (23) can be transformed into an equivalent quadratic programming problem, see formula (24).

[0150]

[0151] The quadratic programming problem described by formula (24) can be expressed as a linear belt constraint problem. By cyclically solving the linear belt constraint problem, the optimal solution of the front wheel steering angle control value can be obtained.

[0152] In one embodiment, the quadratic programming problem solved by the first wheel steering angle control module 211 may be equation (24), and the constraints of the quadratic programming problem are obtained according to the vehicle kinematic equation described by equation (2) and the Lagrangian function described by equation (9).

[0153] Based on the above content, the steps for solving the nonlinear optimization problem may include the following steps 1.1 to 1.6.

[0154] Step 1.1, initialize the initial loop result of the nonlinear optimization problem to be solved as {x0, λ0, μ0}, and initialize Z0 = I n , initialization tolerance ε. I n is the identity matrix.

[0155] Step 1.2, use equations (14) to (19) to calculate g k , A ek , A ik 、a k 、c k and Z k .

[0156] Step 1.3: Based on the calculation results of step 1.2, solve equation (24) to obtain δ x δ x is the state quantity increment in the loop increment δ.

[0157] According to the calculation results of step 1.2, calculate the equality constraint A in equation (24): ek δ x =-a k , we can get multiple δ that meet the equality constraints. x , and then the multiple δ x Substitute the functions into equation (24) respectively Get multiple values, and take the δ used to calculate the minimum value among the multiple values x As the solution of equation (24), δ x .

[0158] Step 1.4, calculate the scaling factor α using the line search method k. Scaling factor α k It may show a gradually downward trend.

[0159] Step 1.5, calculate x k+1 =x k +α k δ x .

[0160] The δ obtained in step 1.3 x , α obtained in step 1.4 k , and the state vector obtained from the last cycle solution of the vehicle (i.e., the kth cycle solution) is substituted into x k+1 =x k +α k δ x , the state vector of the vehicle obtained by the current cycle solution (i.e., the k+1th cycle solution) can be calculated.

[0161] When step 1.5 is executed for the first time, x0 represents the state vector of the vehicle obtained by solving the previous cycle.

[0162] Step 1.6, if ||δ x ||≤ε, output x calculated in step 1.5 k+1 and stop the loop solution; otherwise, set k = k + 1 and jump to step 1.2 to perform another loop solution. This cycle continues until the solution is δ that meets the tolerance requirements. x .

[0163] The state vector obtained by each loop solution can include the front wheel steering angle at a series of future time points, so the state vector x obtained by the output of the k+1th loop solution can be taken k+1 The front wheel steering angle at the next time point in is used as the solved front wheel steering angle control value.

[0164] In one feasible implementation, the activation set method can be used in step 1.3 to solve equation (24) to obtain δ x .

[0165] Comparing the constraints described by equation (8) and equation (23), we can see that equation (23) is a first-order approximation of the constraints described by equation (8). Therefore, solving the problem described by equation (24) in the k+1th cycle is equivalent to solving the optimal solution of the approximate problem of equation (7). Using the activation set method to solve the problem described by equation (24), equation (24) can be rewritten as equation (25).

[0166]

[0167] Based on the above content, the calculation process of the activation set method can include the following steps 2.1 to 2.6.

[0168] Step 2.1, initialize the loop starting point and working set to δ x,0 and W0, so that i∈W0, we have Make have

[0169] Step 2.2, assume that the working set of the mth loop is W m , solve the equality constraint optimization problem described by equation (30) to obtain s m .

[0170] The following formula (26) exists.

[0171]

[0172] Formula (26) is further simplified into formula (27).

[0173]

[0174] In formula (27), Y m =Z k δ x,m +g k .

[0175] The optimality condition for optimizing equation (27) is equation (28).

[0176]

[0177] In formula (28), λ i ,i∈W m is the Lagrange multiplier, L(s,λ) is the Lagrange function and can be expressed as formula (29).

[0178]

[0179] Further rearrangement of formula (29) gives formula (30).

[0180]

[0181] Solving equation (30) yields s m .

[0182] Step 2.3, based on the s calculated in step 2.2 m , if s m =0, execute step 2.4, if s m ≠0, proceed to step 2.5.

[0183] Step 2.4, calculate the Lagrange multiplier λ i ,i∈W m ; If λ i≥0,i∈W m ∩I, then output the optimal solution δ x,m And stop the loop solution, otherwise, update the working set W m+1 =W m / {i|arg(λ i <0,i∈W m ∩I)},δ x,m+1 =δ x,m , and jump to step 2.2.

[0184] Step 2.5, calculate the step length And calculate δ x,m+1 =δ x,m +β m s m ; if exists Update working set W m+1 =W m ∪{i}, and execute step 2.6; otherwise, W k+1 =W k , and execute step 2.6;

[0185] Step 2.6, set m=m+1 and jump to step 2.2.

[0186] Steps 2.2 to 2.6 can be executed repeatedly until the loop end condition described in step 2.4 is met. At this time, the loop solution can be terminated and the δ solved in the current loop can be output. x,m .

[0187] In one embodiment of the present application, the first function is obtained according to a longitudinal control model, where the longitudinal control model includes a desired acceleration of the vehicle, an actual acceleration of the vehicle, and a correlation relationship between longitudinal control disturbance parameters and first-order inertia link parameters.

[0188] The longitudinal response characteristics of the vehicle can be approximated as a first-order inertia link to design the vehicle longitudinal control model, and then the value of the longitudinal control disturbance parameter can be estimated using a nonlinear disturbance observer.

[0189] The burden of the speed tracking control module can be reduced by using a nonlinear disturbance observer to perform real-time estimation and feedforward compensation for the uncertainty of the parking external environment and the control nominal model modeling mechanism.

[0190] In one embodiment, the acceleration compensation module 222 may use the above-mentioned nonlinear disturbance observer to estimate the uncertainty of the parking external environment and the control nominal model modeling mechanism.

[0191] The following takes the case where the vehicle is a wire-controlled four-wheel steering vehicle and the planned path is a planned parking path as an example to illustrate a feasible implementation process of the acceleration compensation module 222 solving the longitudinal control interference parameters. The relevant technical implementation is also applicable to embodiments where the vehicle is a front-wheel or rear-wheel steering vehicle and the planned path is a planned driving path.

[0192] The longitudinal control disturbance parameter d is used to represent the uncertainty of the parking external environment and the control nominal model modeling mechanism, and The longitudinal response characteristics of the wire-controlled four-wheel steering vehicle are approximated as a first-order inertia link, and the nominal model of the longitudinal control of the wire-controlled four-wheel steering vehicle parking can be expressed as formula (31).

[0193]

[0194] In formula (31), v and a are the actual speed and actual acceleration of the wire-controlled four-wheel steering vehicle, respectively; a c is the expected acceleration of the wire-controlled four-wheel steering vehicle; τ is the first-order inertia link parameter.

[0195] For the longitudinal control model described by equation (31), a nonlinear disturbance observer described by equation (32) can be designed to estimate the uncertainty of the parking external environment and the control nominal model modeling mechanism.

[0196]

[0197] In the formula, is the calibration parameter of the nonlinear disturbance observer, and z is the intermediate variable.

[0198] When , the nonlinear disturbance observer described by equation (32) is stable, and (That is, the error between the actual value of the interference and the estimated value of the interference is small enough), so that the longitudinal control interference parameters can be accurately estimated to support the accurate acquisition of the acceleration control amount, which is beneficial to improving the accuracy of the vehicle's longitudinal tracking.

[0199] In one embodiment, the first function may be a function shown in formula (32) obtained according to the longitudinal control model described in formula (31). In order to accurately obtain the acceleration control amount, the first function may be limited to include calibration parameters of the nonlinear disturbance observer, and the value thereof is a value that can stabilize the nonlinear disturbance observer.

[0200] Next, based on equations (33) to (36), When , the stability of the nonlinear disturbance observer described by equation (32) is verified.

[0201] For the nonlinear disturbance observer of equation (32), the Lyapunov function is defined as equation (33).

[0202]

[0203] By differentiating the Lyapunov function described by equation (33), we can obtain equation (34).

[0204]

[0205] The estimated value of the longitudinal control disturbance parameter d in equation (34) is (For example, it can be reflected as an estimate of the uncertainty of the parking external environment and the control nominal model modeling mechanism) Taking the derivative, we can get formula (35).

[0206]

[0207] Substituting equation (35) into equation (34), we can obtain equation (36).

[0208]

[0209] From formula (36), we can see that if Then the nonlinear disturbance observer described by equation (34) is stable, and there is

[0210] By using a stable nonlinear disturbance observer for disturbance estimation, it is helpful to accurately estimate the impact of disturbance on longitudinal control, and then control the vehicle acceleration after feedforward compensation of the reference acceleration according to the estimated disturbance, which can support the accurate tracking of the planned speed in the longitudinal direction of the vehicle.

[0211] In one embodiment of the present application, the acceleration compensation module uses a tracking differentiator to solve a second function according to the actual speed of the first vehicle to obtain the actual acceleration of the first vehicle; wherein the second function includes the correlation between the actual speed of the vehicle, the actual acceleration of the vehicle and the calibration parameters of the tracking differentiator.

[0212] The vehicle may be equipped with a sensor for sensing the vehicle speed, and the actual speed of the vehicle may be obtained based on the data collected by the sensor in real time, and the actual speed of the vehicle may be used as the input of the tracking differentiator. The tracking differentiator may estimate the actual acceleration of the vehicle using the actual speed of the vehicle. By using the tracking differentiator to estimate the actual acceleration of the vehicle based on the actual speed of the vehicle, the actual acceleration of the vehicle may be accurately obtained.

[0213] In one embodiment, the acceleration compensation module 222 may use the tracking differentiator 1021 described above to estimate the actual acceleration of the vehicle.

[0214] The actual vehicle acceleration estimated by the tracking differentiator can be used as the input of the nonlinear disturbance observer. The nonlinear disturbance observer then estimates the value of the longitudinal control disturbance parameter in real time based on the actual acceleration output by the tracking differentiator.

[0215] In one feasible implementation, a tracking differentiator as described in equation (37) can be designed.

[0216]

[0217] In formula (37), Q>0, b0>0, b1>0 and c>1 are the calibration parameters of the tracking differentiator. is an estimate of the actual acceleration of the vehicle.

[0218] In one embodiment of the present application, solving a speed tracking control problem for tracking a planned speed includes: solving a third function using a fast terminal sliding mode control law; wherein the third function is obtained based on a fast terminal sliding mode surface including a speed tracking error, and the speed tracking error is used to describe the error between a reference speed and a vehicle speed predicted based on an expected acceleration.

[0219] Based on the current actual speed and expected acceleration of the vehicle, the speed of the vehicle at a future moment can be predicted. If the error between the predicted speed and the reference speed (i.e., the speed tracking error) is small, it can be considered that the longitudinal tracking effect of the planned speed is better. In this way, a fast terminal sliding surface can be constructed based on the speed tracking error, and the fast terminal sliding surface constructed by the fast terminal sliding control law can be used to solve the expected acceleration that can meet the speed tracking requirements.

[0220] The fast terminal sliding mode control law can make the speed tracking error converge to zero within a finite time, making the vehicle longitudinal control present high performance of "fast convergence, high accuracy and strong robustness".

[0221] In one embodiment, the speed tracking control module 221 may use the above-mentioned fast terminal sliding mode control law 101 to solve the reference acceleration.

[0222] In one feasible implementation, the fast terminal sliding mode control law described by equation (39) can be designed based on the fast terminal sliding mode surface described by equation (38).

[0223] Using s=vv ref represents the velocity tracking error, and the fast terminal sliding surface described by equation (38) is defined based on the velocity tracking error.

[0224]

[0225] In formula (38), P>0, q>0, m and n are both positive odd numbers, and n>m.

[0226] Using the fast terminal sliding mode surface described by equation (38), a fast terminal sliding mode control law described by equation (39) is designed for the vehicle longitudinal control model described by equation (31), so that the closed-loop system composed of equations (31) and (39) is finite-time stable.

[0227]

[0228] In formula (39), k1>0, k2>0, k3>ξ and 0<η<1 are all parameters of the fast terminal sliding mode control law.

[0229] Next, through equations (40) to (49), it is proved that the closed-loop system formed by equations (31) and (39) is finite-time stable.

[0230] Define the Lyapunov function as equation (40).

[0231]

[0232] By differentiating equation (40), we can obtain equation (41).

[0233]

[0234] Substituting the fast terminal sliding mode control law of equation (39) into equation (41), we can obtain equation (42).

[0235]

[0236]

[0237] Further rearrangement of equation (43) yields equation (44).

[0238]

[0239] It can be seen from equation (44) that the closed-loop system composed of equation (31) and equation (39) converges to σ = 0 in a finite time.

[0240] Under the premise that the closed-loop system composed of equations (31) and (39) converges to σ = 0 in a finite time, the fast terminal sliding surface defined by equation (38) yields equation (45).

[0241]

[0242] By differentiating equation (45), we can obtain equation (46).

[0243]

[0244] Divide both ends of formula (46) by s m / n , and replace the variable y=s1-m / n , we can get formula (47).

[0245]

[0246] In formula (47),

[0247] Solving equation (47), we can obtain equation (48).

[0248]

[0249] Let y = 0, and we can obtain equation (49).

[0250]

[0251] When y = 0, s = 0. Therefore, the velocity tracking error converges to s = 0 in a finite time. In summary, the closed-loop system composed of equations (31) and (39) is finite-time stable.

[0252] It can be seen that since the fast terminal sliding mode control law can make the speed tracking error converge to zero within a finite time, by using the fast terminal sliding mode control law to solve the reference acceleration and controlling the acceleration of the vehicle based on the reference acceleration, the vehicle longitudinal control can present high performance of "fast convergence, high accuracy and strong robustness".

[0253] An embodiment of the present application provides a vehicle control method, including: solving a path tracking control problem for tracking a planned path, obtaining a first wheel steering angle control amount of a first vehicle, the first wheel being one of a front wheel and a rear wheel; wherein the planned path includes a reference posture at a series of future time points, and the reference posture includes at least one of a reference lateral position and a reference heading angle; solving a speed tracking control problem for tracking a planned speed, obtaining an expected acceleration of the first vehicle; wherein the planned speed includes a reference speed at a series of future time points; using a nonlinear disturbance observer, solving a first function according to an actual acceleration of the first vehicle and an expected acceleration of the first vehicle, obtaining a value of a longitudinal control disturbance parameter; obtaining an acceleration control amount of the first vehicle according to the value of the longitudinal control disturbance parameter and the expected acceleration of the first vehicle; wherein the first function includes an association relationship between the expected acceleration of the vehicle, the actual acceleration of the vehicle, the longitudinal control disturbance parameter and a calibration parameter of the nonlinear disturbance observer.

[0254] An embodiment of the present application provides an electronic chip, including: a processor, which is used to execute computer program instructions stored in a memory, wherein when the computer program instructions are executed by the processor, the electronic chip is triggered to execute the method described in any embodiment of the present application.

[0255] An embodiment of the present application provides an electronic device, which includes at least one processor, the processor and a memory are coupled, the memory is used to store computer program instructions, and the processor is used to execute the computer program instructions, wherein when the computer program instructions are executed by the processor, the electronic device is triggered to execute the method described in any embodiment of the present application.

[0256] An embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer executes the method described in any embodiment of the present application.

[0257] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program runs on a computer, the computer executes the method described in any embodiment of the present application.

[0258] Figure 5 A schematic diagram of a computer device provided in one embodiment of the present application. Figure 5 As shown, the computer device 20 of this embodiment includes: a processor 21 and a memory 22, the memory 22 is used to store a computer program 23 that can be run on the processor 21, and the computer program 23 is executed by the processor 21 to implement the steps in the method embodiment of the present application. To avoid repetition, they are not described one by one here. Alternatively, when the computer program 23 is executed by the processor 21, the functions of each model / unit in the device embodiment of the present application are implemented. To avoid repetition, they are not described one by one here.

[0259] The computer device 20 includes but is not limited to a processor 21 and a memory 22. Those skilled in the art will appreciate that Figure 5 It is only an example of the computer device 20 and does not constitute a limitation of the computer device 20. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0260] The processor 21 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor may be any conventional processor, etc.

[0261] The memory 22 may be an internal storage unit of the computer device 20, such as a hard disk or memory of the computer device 20. The memory 22 may also be an external storage device of the computer device 20, such as a plug-in hard disk, a Smart Media (SM) card, a Secure Digital (SD) card, a Flash Card, etc. equipped on the computer device 20. Further, the memory 22 may also include both an internal storage unit of the computer device 20 and an external storage device. The memory 22 is used to store the computer program 23 and other programs and data required by the computer device. The memory 22 may also be used to temporarily store data that has been output or is to be output.

[0262] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0263] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0264] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0265] The integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (Processor) to perform some steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program code.

[0266] In the embodiments of the present application, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, method, commodity or device including the element.

[0267] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0268] Those skilled in the art will appreciate that the various units and algorithm steps described in the embodiments of the present application can be implemented by a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0269] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the same or similar parts between the various embodiments in this application can be referred to each other. For example, the specific working process of the system, device and unit described in the embodiments of this application can refer to the corresponding process in the method embodiment of this application, and will not be repeated here.

[0270] The above description is only a specific embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A vehicle control system, characterized in that: include: A vehicle lateral control module and a vehicle longitudinal control module; Wherein, the vehicle lateral control module includes a first wheel steering angle control module, and the vehicle longitudinal control module includes a speed tracking control module and an acceleration compensation module; The first wheel steering angle control module is used to solve a path tracking control problem for tracking a planned path, and obtain a first wheel steering angle control amount of a first vehicle, wherein the first wheel is one of a front wheel and a rear wheel; wherein the planned path includes a reference posture at a series of future time points, and the reference posture includes at least one of a reference lateral position and a reference heading angle; The speed tracking control module is used to solve the speed tracking control problem for tracking the planned speed to obtain the expected acceleration of the first vehicle; wherein the planned speed includes reference speeds at a series of future time points; The acceleration compensation module is used to use a nonlinear disturbance observer to solve a first function according to the actual acceleration of the first vehicle and the expected acceleration of the first vehicle to obtain a value of a longitudinal control disturbance parameter; and to obtain an acceleration control amount of the first vehicle according to the value of the longitudinal control disturbance parameter and the expected acceleration of the first vehicle; wherein the first function includes an association relationship between the expected acceleration of the vehicle, the actual acceleration of the vehicle, the longitudinal control disturbance parameter and a calibration parameter of the nonlinear disturbance observer.

2. The vehicle control system according to claim 1, characterized in that: The vehicle lateral control module also includes a second wheel steering angle control module; The second wheel steering angle control module is used to obtain a second wheel steering angle control amount of the first vehicle according to the correlation between the front wheel steering angle and the rear wheel steering angle of the first vehicle and the first wheel steering angle control amount of the first vehicle, wherein the second wheel is the other of the front wheel and the rear wheel; The association relationship is obtained according to a maximum value of a front wheel steering angle of the first vehicle and a maximum value of a rear wheel steering angle of the first vehicle.

3. The vehicle control system according to claim 1 or 2, characterized in that: The first function is obtained according to a longitudinal control model, wherein the longitudinal control model includes a desired acceleration of the vehicle, an actual acceleration of the vehicle, and a correlation relationship between the longitudinal control disturbance parameter and a first-order inertia link parameter.

4. The vehicle control system according to claim 1 or 2, characterized in that: The acceleration compensation module is used to solve a second function according to an actual speed of the first vehicle using a tracking differentiator to obtain an actual acceleration of the first vehicle; The second function includes the correlation between the actual speed of the vehicle, the actual acceleration of the vehicle and the calibration parameters of the tracking differentiator.

5. The vehicle control system according to claim 1 or 2, characterized in that: The solving of the speed tracking control problem for tracking the planned speed includes: solving the third function using a fast terminal sliding mode control law; The third function is obtained according to a fast terminal sliding surface including a speed tracking error, wherein the speed tracking error is used to describe an error between the reference speed and a vehicle speed predicted according to the expected acceleration.

6. The vehicle control system according to claim 1 or 2, characterized in that: The solution to the path tracking control problem for tracking the planned path includes: Solve a quadratic programming problem, wherein the quadratic programming problem is obtained by transforming the path tracking control problem, and the constraints of the quadratic programming problem are obtained according to the vehicle kinematic equation and the Lagrangian function.

7. The vehicle control system according to claim 6, characterized in that: Any solution result includes a state quantity reflecting the vehicle posture and the first wheel steering angle at a series of future time points, a control quantity reflecting the first wheel steering angular velocity, and a value of the Lagrange multiplier; The solving of the quadratic programming problem comprises: If there is a solution result of the previous cycle, then based on the solution result of the previous cycle, solve the quadratic programming problem to obtain a state quantity increment; According to the obtained state quantity increment and the solution result of the previous cycle, the solution result of the current cycle is obtained; If the setting condition is met, the first wheel steering angle control amount of the first vehicle is the first wheel steering angle at the next moment obtained in the current cycle; the setting condition includes that the absolute value of the obtained state quantity increment is not greater than the set tolerance; If the setting condition is not met, the step of solving the quadratic programming problem is performed again.

8. A vehicle control method, characterized in that: include: Solving a path tracking control problem for tracking a planned path, obtaining a first wheel steering angle control value of a first vehicle, wherein the first wheel is one of a front wheel and a rear wheel; wherein the planned path includes reference postures at a series of future time points, and the reference postures include at least one of a reference lateral position and a reference heading angle; Solving a speed tracking control problem for tracking a planned speed to obtain a desired acceleration of the first vehicle; wherein the planned speed includes reference speeds at a series of future time points; Using a nonlinear disturbance observer, a first function is solved according to the actual acceleration of the first vehicle and the expected acceleration of the first vehicle to obtain the value of the longitudinal control disturbance parameter; according to the value of the longitudinal control disturbance parameter and the expected acceleration of the first vehicle, the acceleration control amount of the first vehicle is obtained; wherein the first function includes the expected acceleration of the vehicle, the actual acceleration of the vehicle, the longitudinal control disturbance parameter and the correlation relationship between the calibration parameters of the nonlinear disturbance observer.

9. An electronic device, characterized in that: The electronic device comprises at least one processor, the processor is coupled to a memory, the memory is used to store computer program instructions, and the processor is used to execute the computer program instructions, wherein when the computer program instructions are executed by the processor, the electronic device is triggered to execute the method as claimed in claim 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is run on a computer, the computer is enabled to execute the method according to claim 8.

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