CN113655718B - Automatic driving vehicle distance self-adaptive control method based on sliding mode control - Google Patents
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Abstract
The invention discloses an automatic driving vehicle distance self-adaptive control method based on sliding mode control, which is characterized in that a sliding mode surface is established by establishing a vehicle dynamics control equation based on an exponential approach law, and acquiring acceleration output, and finally acquiring ideal acceleration output by combining a model reference self-adaptive control algorithm for longitudinally adjusting the distance between the automatic driving vehicle and the front vehicle. The invention can improve the control precision, and can effectively solve the problems of system buffeting, external disturbance and interference caused by nonlinear factors in the process of controlling the longitudinal distance of the automatic driving, thereby obviously improving the performance of a control system and improving the stability and the accuracy of controlling the longitudinal distance. Meanwhile, the problems of uncertainty of vehicle control and time-varying parameter characteristics can be effectively solved, and the control law can be adjusted according to the self-adaptive parameters, so that the controlled performance of the vehicle reaches the expected target.
Description
Technical Field
The invention relates to an intelligent vehicle control method, in particular to an automatic driving vehicle distance control algorithm combining sliding mode control and model reference self-adaptive control.
Background
Intelligent driving is an important field of development of future automobile industry, and is widely focused by domestic and foreign scientific research institutions, and longitudinal distance control plays an important role in driving safety and comfort, so that strict algorithm model selection and simulation verification are required in the process of design and development. Because the whole automobile modules have pure delay, time lag and coupling characteristics in mutual communication, and meanwhile, the automobile dynamics and kinematics models have complex parameters and nonlinear characteristics, the interference caused by various external environments needs to be comprehensively considered in the control design process.
Various control algorithms have been used in the art for controlling autonomous vehicles, such as PID control, MPC control, LQR control, slip-form control, and the like. Patent CN201810765512.5 discloses a method for controlling a second-order sliding mode of an automatic driving vehicle based on visual dynamics, which solves a series of problems of discontinuous traditional sliding mode control, buffeting and the like, has stronger robustness, but is mainly aimed at transverse control of the vehicle; patent CN201610527920.8 discloses a learning method-based intelligent automobile longitudinal neural sliding mode control method, but the control output is accelerator opening or brake pressure, which is not suitable for a framework with acceleration as the control output; patent CN201510278571.6 discloses a method for unmanned vehicle side longitudinal coupling tracking control based on a fast sliding mode principle, which utilizes a fast terminal sliding mode principle to finally calculate a desired throttle opening or braking torque, but the output of the final torque of the scheme is required to be arbitrated by an ESP and finally determined to be given to a power system or a braking system, so the method is not suitable for the development architecture of an actual intelligent driving system.
Disclosure of Invention
The invention aims to: the invention aims to provide a control method capable of keeping a safe following distance of a vehicle during automatic driving.
The technical scheme is as follows: the self-adaptive control method for the distance between the automatic driving vehicles based on the sliding mode control comprises the following steps:
(1) Establishing a dynamic model for describing longitudinal movement characteristics of the automobile;
(2) Determining a sliding mode surface equation and an index approach rate,
(3) Solving a control law equation according to the model obtained in the steps (1) - (3) and smoothing the control law equation;
(4) Adding a feedforward item representing dynamic movement of the front vehicle, and primarily acquiring acceleration output;
(5) And establishing a model reference self-adaptive controller to obtain the final ideal acceleration output.
In step (1), the kinetic model is expressed as:
Wherein R act represents the actual distance between the own vehicle and the front vehicle; r des represents the ideal distance between the vehicle and the front vehicle; t Gap represents a safety time interval kept with the front vehicle; v lead represents the front vehicle speed; x 1 represents the difference between the actual inter-vehicle distance and the ideal inter-vehicle distance; x 2 represents the relative speed of the own vehicle and the preceding vehicle; u represents an ideal following acceleration.
The slip plane equation is expressed as:
s＝k1x1+k2x2+k3∫x1dt
the exponential approach law is expressed as:
Wherein the parameters of k1, k2 and k3 are set according to actual conditions, epsilon is the approach speed, and k is an exponential approach term coefficient set according to the actual sliding mode surface approach conditions.
The control law equation is expressed as:
smoothing the control law equation to smooth the control output
In the above formula, u is the output of the sliding mode control.
In the step (4), the acceleration of the front vehicle is taken as a feedforward term and is corrected, and the obtained control law is as follows:
In the above formula, k 4 is a correction parameter.
Step (5) comprises the following steps:
(51) Establishing a reference vehicle model and a real vehicle model comprising an ESP model;
(52) Defining an output error between the reference model and the real model;
(53) Establishing an adaptive control law of the adjustable parameters by combining the error influence and the control law;
(54) And establishing an automobile acceleration control law equation based on the self-adaptive control rate of the adjustable parameters.
In the step (51), the reference vehicle model is a second-order system model, and the transfer function expression is as follows:
Wherein k m is the second-order system gain, ζ is the damping ratio, and w n is the undamped natural frequency;
Is provided with am1＝2ξwn，So that xi is determined according to the requirement for the overshoot σ%, and a proper w n is selected to meet the requirement for the adjustment time t s.
The transfer function expression of the real vehicle model in step (51) is as follows:
Wherein P(s) is a transfer function of the controlled object, Y p(s) is an actual output, U(s) is an actual input, k p>0,ap1>0,ap0 >0 is a system structural parameter of the actual vehicle model, and the value is obtained through parameter identification.
The time domain description of the reference vehicle model and the real vehicle model is as follows:
The control action u (t) is:
e 0 is the output error, which is represented as follows:
e0(t)＝yp(t)-ym(t)
substituting the formulas (12), (13) and (14) into the formula (16) to obtain:
when c 0(t)、d0(t)、d1(t)、d2 (t) are respectively equal to the nominal parameters When, i.e
When the four formulas are satisfied, the output response curve of the adjustable system completely follows the output response curve of the reference model, and the self-adaptive law is set, however, due to the dynamic response characteristic of the control system, the self-adaptive law of the adjustable parameters in the following form is adopted:
the adjustable adaptive law may be expressed as
Wherein g 1、g2、g3、g4 is a parameter that is adjusted according to the actual condition of the system output response.
The final ideal acceleration output is calculated as follows:
The beneficial effects are that: compared with the prior art, the invention has the following remarkable advantages: the control precision can be improved through a sliding mode control algorithm based on an index approach law, and the system buffeting, external disturbance and interference caused by nonlinear factors in the automatic driving longitudinal spacing control process can be effectively solved, so that the performance of a control system is obviously improved, and the stability and the accuracy of longitudinal spacing control are improved. Meanwhile, the model reference self-adaptive control is combined, the problems of vehicle control uncertainty and parameter characteristic time variation can be effectively solved, the control law can be adjusted according to the self-adaptive parameters, and the parameters or the structure of the controller can be adjusted in a self-adaptive mode, so that the controlled performance of the vehicle can reach the expected target.
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FIG. 1 is a control schematic of the present invention;
FIG. 2 is a schematic diagram of the model reference adaptive control of the present invention;
FIG. 3 is a schematic diagram of a smart car longitudinal spacing slip form control of the present invention;
fig. 4 is a diagram of a second order system model reference adaptive control system of the present invention.
Detailed Description
The technical scheme of the invention is further described below with reference to the accompanying drawings.
The sliding mode control is one of nonlinear control methods, and the control principle is shown in fig. 3; if in the control process, the system structure changes purposefully along with the change of deviation, so that the system is ensured to finally enable the system track to reach and be kept on a preset sliding surface in a limited time under the action of a controller, and the closed-loop system is enabled to stably run on the sliding surface; the sliding mode design has no relation with the object parameters and external disturbance thereof, is insensitive to the object parameter change and disturbance, does not need system identification and physical realization, and has the advantage of quick control response.
The model reference self-adaptive control can select a proper reference model according to the performance index requirement of the system, the structure of the controlled object model and known parameter information, and can ensure that the output or state of the controlled object can reach the expected performance index requirement of the system under the condition of ensuring the stability of the system by designing a proper self-adaptive parameter adjustment control law, thereby achieving the self-adaptive tracking control purpose of the output or state of the controlled object.
Therefore, the invention provides a vehicle distance control method combining sliding mode control and model reference self-adaptive control, wherein the control principle is shown in figure 1, the model reference self-adaptive control principle is shown in figure 2, a control system consists of a sliding mode controller, a model self-adaptive controller and a vehicle body electronic stability system (ESP), the speed of a front vehicle, the speed of a self-vehicle, an ideal distance, an actual distance and the acceleration of the front vehicle are used as inputs of the sliding mode controller, and the initial longitudinal acceleration of the vehicle is used as outputs of the sliding mode controller; the method comprises the steps of establishing a reference vehicle model and a real vehicle model, taking initial longitudinal acceleration as reference acceleration of a desired vehicle, forming input of an adaptive regulator together with acceleration of the real vehicle, taking the initial longitudinal acceleration of the reference vehicle model, the acceleration of the real vehicle and output of the adaptive regulator as input of a model reference controller (MRAC), regulating parameters of the model reference controller by the adaptive regulator, taking output of the model reference controller as final longitudinal acceleration, and converting the output of the model reference controller into a torque request by a vehicle body electronic stabilizing system to regulate the acceleration of the vehicle, so that the control of the distance between the vehicle and a front vehicle is realized. The control method specifically comprises the following steps:
(1) Establishing a dynamic model for describing longitudinal movement characteristics of the automobile;
(2) Establishing a sliding mode surface equation and an index approach rate,
(3) Solving a control law equation according to the model obtained in the steps (1) - (3) and smoothing the control law equation;
(4) Adding a feedforward item representing dynamic movement of the front vehicle, and primarily acquiring acceleration output;
(5) And establishing a model reference self-adaptive controller to obtain the final ideal acceleration output.
In step (1), the kinetic model is expressed as:
Wherein R act represents the actual distance between the own vehicle and the front vehicle; r des represents the ideal distance between the vehicle and the front vehicle; t Gap represents a safety time interval kept with the front vehicle; v lead represents the front vehicle speed; x 1 represents the difference between the actual inter-vehicle distance and the ideal inter-vehicle distance; x 2 represents the relative speed of the own vehicle and the preceding vehicle; u represents an ideal following acceleration.
The slip-form surface equation of the present invention is as follows, and its task is to enable a point located outside the slip-form surface to move onto the slip-form surface with certain conditions:
s＝k1x1+k2x2+k3∫x1dt (5)
Wherein the k 1,k2,k3 parameter is set according to the actual situation, epsilon is the approach speed.
The invention selects the index approach rate to carry out sliding mode control, and the task is to enable the initial point to approach to the sliding mode surface no matter where the initial point is; the approach speed is gradually reduced from a larger value to zero in the exponential approach, so that the approach time is shortened, the speed when the motion point reaches the switching surface is small, but the simple exponential approach, the motion point approaches the switching surface, a progressive process, the approach in a limited time can not be ensured, and no sliding mode exists on the switching surface, so that a constant-speed approach item is increasedSo that when s is close to zero, the approach speed is epsilon, instead of zero, and the finite time can be guaranteed to arrive, and in sum, the exponential approach law is expressed as:
Wherein k is an exponential approach term coefficient set according to the approach condition of an actual sliding mode surface.
According to the parameters and the equations, a control rate equation is preliminarily calculated, and the control law equation is as follows:
Smoothing the control law equation to smooth the control output:
Since the sliding mode control cannot consider the dynamic motion of the front vehicle, the acceleration a lead of the front vehicle is added as a feedforward term in a control equation, and in order to adjust the influence of the feedforward term on a control system, the feedforward term needs to be calibrated, so the feedforward term is corrected by a coefficient k 4, as follows:
In the above formula, u is the output of the sliding mode control, and is the input of the model reference adaptive controller.
Step (5) comprises the following steps:
(51) Establishing a reference vehicle model and a real vehicle model comprising an ESP model;
(52) Defining an output error between the reference model and the real model;
(53) Establishing an adaptive control law of the adjustable parameters by combining the error influence and the control law;
(54) And establishing an automobile acceleration control law equation based on the self-adaptive control rate of the adjustable parameters.
In the step (51), the reference vehicle model M(s) is a second-order system model, and the final ideal acceleration output is obtained, and the transfer function is as follows:
Wherein k m is the second-order system gain, ζ is the damping ratio, and w n is the undamped natural frequency;
Is provided with am1＝2ξwn，So that xi is determined according to the requirement for the overshoot σ%, and a proper w n is selected to meet the requirement for the adjustment time t s.
The real vehicle model in the step (51) comprises an ESP model, and the controlled object to be controlled is set to be a second-order linear time-invariant system, and the transfer function expression is as follows:
Wherein P(s) is a transfer function of the controlled object, Y p(s) is an actual output, U(s) is an actual input, k p>0,ap1>0,ap0 >0 is a system structural parameter of the actual vehicle model, and the value is obtained through parameter identification.
The time domain description of the reference vehicle model and the real vehicle model is as follows:
as shown in fig. 4, the control action u (t) is:
e 0 is the output error, which is represented as follows:
e0(t)＝yp(t)-ym(t) (15)
substituting the formulas (12), (13) and (14) into the formula (16) to obtain:
The invention combines the model reference self-adaptive control, utilizes the vehicle kinematic state equation to design the state self-adaptive tracking control system of the vehicle, and can adapt to the change of the vehicle characteristics and the influence caused by external interference by continuously correcting the characteristics of the system, so that the system can always obtain satisfactory performance indexes in the running process. When the adaptive mechanisms c 0(t)、d0(t)、d1(t)、d2 (t) are respectively equal to the nominal parameters When, i.e
The output response curve of the adjustable system can completely follow the output response curve of the reference model, and then the self-adaptive law is set. However, based on the dynamic response characteristics of the control system, an adaptive law of adjustable parameters of the following form is adopted:
the adjustable adaptive control law can be expressed as
In the above equation, g 1、g2、g3、g4 is a parameter that is adjusted according to the actual condition of the system output response. The adaptive control system is constructed as shown in fig. 4. Wherein r represents a given value, u represents a control function, y m、yp represents output responses of a reference model and a controlled object, e 0 represents a difference between outputs of the controlled object and the reference model, P(s) is a transfer function of the controlled object, M(s) is a transfer function of the reference model, c 0(t)、d0(t)、d1(t)、d2 (t) forms an adaptive mechanism, and dy p/dt represents derivation of y p.
Substituting the adaptive law equation (23) above, the control input r (i.e., the sliding mode control output), the actual output y p and its derivativesThe difference e 0 between the output of the controlled object and the reference model and the control law equation (14) are obtained as follows:
Claims (7)
1. An automatic driving vehicle distance self-adaptive control method based on sliding mode control is characterized by comprising the following steps:
(1) Establishing a dynamic model for describing longitudinal movement characteristics of the automobile;
(2) Determining a sliding mode surface equation and an index approach rate,
(3) Solving a control law equation according to the dynamics model and the sliding mode surface equation obtained in the step (2), and carrying out smoothing treatment on the control law equation;
(4) Adding a feedforward item representing dynamic movement of the front vehicle, and primarily acquiring acceleration output;
(5) Establishing a model reference self-adaptive controller to obtain final ideal acceleration output; the method comprises the following steps:
(51) Establishing a reference vehicle model and a real vehicle model comprising an ESP model;
(52) Defining an output error between a reference model and a real model, and establishing an adaptive control law of adjustable parameters by combining error influence and control law; the time domain description of the reference vehicle model and the real vehicle model is as follows:
The control action u (t) is:
e 0 is the output error, which is represented as follows:
e0(t)＝yp(t)-ym(t)
substituting the formulas (12), (13) and (14) into the formula (16) to obtain:
when c 0(t)、d0(t)、d1(t)、d2 (t) are respectively equal to the nominal parameters When, namely:
When the four formulas are satisfied, the output response curve of the adjustable system completely follows the output response curve of the reference model, and the self-adaptive law is set, however, due to the dynamic response characteristic of the control system, the self-adaptive law of the adjustable parameters in the following form is adopted:
The adjustable adaptation law is expressed as:
wherein g 1、g2、g3、g4 is a parameter adjusted according to the actual condition of the system output response;
the final ideal acceleration output is calculated as follows:
(53) And establishing an automobile acceleration control law equation based on the self-adaptive control rate of the adjustable parameters.
2. The method for adaptive control of distance between automatically driven vehicles based on sliding mode control according to claim 1, wherein in the step (1), the dynamics model is expressed as:
Wherein R act represents the actual distance between the own vehicle and the front vehicle; r des represents the ideal distance between the vehicle and the front vehicle; t Gap represents a safety time interval kept with the front vehicle; v lead represents the front vehicle speed; x 1 represents the difference between the actual inter-vehicle distance and the ideal inter-vehicle distance; x 2 represents the relative speed of the own vehicle and the preceding vehicle; u represents an ideal following acceleration.
3. The sliding mode control-based self-adaptive control method for distance between automatically driven vehicles according to claim 1, wherein the sliding mode surface equation is expressed as:
s＝k1x1+k2x2+k3∫x1dt
the exponential approach law is expressed as:
Wherein k 1,k2,k3 is a control parameter set according to actual conditions, epsilon is an approach speed, and k is an exponential approach term coefficient set according to actual sliding mode surface approach conditions.
4. The sliding mode control-based self-adaptive control method for distance between automatically driven vehicles according to claim 1, wherein the control law equation is expressed as:
smoothing the control law equation to smooth the control output
In the above formula, u is the output of the sliding mode control.
5. The method for adaptive control of distance between automatically driven vehicles based on sliding mode control according to claim 1, wherein the previous vehicle acceleration in step (4) is used as a feedforward term and is corrected, and the control law is as follows:
In the above formula, k 4 is a correction parameter.
6. The method for adaptive control of distance between automatically driven vehicles based on sliding mode control according to claim 1, wherein the reference vehicle model in the step (51) is a second order system model, and the transfer function expression is as follows:
Wherein k m is the second-order system gain, ζ is the damping ratio, and w n is the undamped natural frequency;
Is provided with So that xi is determined according to the requirement for the overshoot σ%, and a proper w n is selected to meet the requirement for the adjustment time t s.
7. The method for adaptive control of distance between automatically driven vehicles based on sliding mode control according to claim 6, wherein the expression of the transfer function of the real vehicle model in step (51) is as follows:
Wherein P(s) is a transfer function of the controlled object, Y p(s) is an actual output, U(s) is an actual input, k p>0,ap1>0,ap0 >0 is a system structural parameter of the actual vehicle model, and the value is obtained through parameter identification.
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