CN116679592A - Automatic driving vehicle control method and device based on MPC control - Google Patents

Automatic driving vehicle control method and device based on MPC control Download PDF

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Publication number
CN116679592A
CN116679592A CN202310466552.0A CN202310466552A CN116679592A CN 116679592 A CN116679592 A CN 116679592A CN 202310466552 A CN202310466552 A CN 202310466552A CN 116679592 A CN116679592 A CN 116679592A
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CN
China
Prior art keywords
steering wheel
control
wheel angle
automatic driving
change rate
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Pending
Application number
CN202310466552.0A
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Chinese (zh)
Inventor
严亮
董海涛
胡钱洋
付永卓
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Yutong Bus Co Ltd
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Yutong Bus Co Ltd
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Priority to CN202310466552.0A priority Critical patent/CN116679592A/en
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
    • G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
    • G05B19/0423—Input/output
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/25—Pc structure of the system
    • G05B2219/25257—Microcontroller
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

Abstract

The invention belongs to the technical field of automatic driving automatic control, and particularly relates to an automatic driving vehicle control method and device based on MPC control. According to the invention, the steering wheel angle change rate constraint is adaptively calculated in real time according to different working conditions, then an objective function is solved according to a dynamics error model under the constraint conditions of meeting the state, the control quantity and the control quantity change rate to obtain a control sequence in a control time domain, and the transverse comfort is improved while meeting the requirements of different working conditions on the control quantity change rate; in addition, when the steering wheel just enters automatic driving, the steering wheel is smoothly turned from the actual steering wheel to the target steering wheel, and the vehicle is controlled to slowly run in the smooth process, so that the tire is prevented from being worn during the in-situ return of the steering wheel, and the control comfort of the steering wheel is improved.

Description

Automatic driving vehicle control method and device based on MPC control
Technical Field
The invention belongs to the technical field of automatic driving automatic control, and particularly relates to an automatic driving vehicle control method and device based on MPC control.
Background
The track tracking control of the automatic driving vehicle is one of key technologies for realizing automatic driving of the vehicle, and the transverse control function in track tracking mainly reduces the transverse deviation between the current track and the target track of the vehicle by controlling the front wheel steering angle of the vehicle, so that the vehicle can drive along the planned target track.
In the prior art, the most commonly used method for realizing track tracking control is proportional-integral-derivative control (PID control for short), the PID control is simpler, but the gradual stability of control is poorer, so that the stability of transverse control of the vehicle is lower, and the tracking precision is lower.
The control tracking accuracy of the model predictive control (Model Predictive Control, MPC) is good, and the problems can be well solved. The control principle of the transverse driving MPC in the prior art is shown in fig. 1, wherein the feedforward steering wheel angle calculated by the track curvature and the feedback steering wheel angle calculated by the MPC are added, and then the target steering wheel angle obtained after the addition is subjected to amplitude limiting treatment to obtain the target steering wheel angle acted on the controlled vehicle. The feedback steering wheel angle calculated by the MPC is mainly based on a dynamic error model of the vehicle and the current state quantity, the system output in a period of time (namely, prediction time domain and control time domain) can be predicted, the objective function is solved under the condition of meeting the constraint of the objective function, the state, the control quantity and the control quantity change rate to obtain a control sequence in the control time domain, then the first value of the control time domain is used as the current output value to act on a control object, the process is repeated in the next period, and the optimization problem with constraint is completed by rolling, so that the continuous control on the transverse direction of the vehicle is realized.
While the MPC considers the control quantity change rate constraint when solving the objective function, the general control quantity change rate constraint is the maximum rotating speed which can be responded by the steer-by-wire system, the MPC does not constraint according to specific working conditions, cannot adapt to scenes of curves with different speeds and different curvatures, and cannot adapt to different working conditions.
Disclosure of Invention
The invention aims to provide an automatic driving vehicle control method and device based on MPC control, which are used for solving the problem that an automatic driving transverse MPC control method in the prior art cannot adapt to all working conditions.
In order to solve the technical problems, the invention provides an automatic driving vehicle control method based on MPC control, which comprises the following steps:
1) Obtaining the maximum steering wheel turning angle change rate limit value Deltau of the current curvature according to the curvature of the target track k_lmt (k) And obtaining the maximum steering wheel rotation angle change rate limit value Deltau of the current vehicle speed according to the actual vehicle speed v_lmt (k) Taking the minimum value of the two limit values to obtain the maximum constraint delta u of the steering wheel angle change rate max (k)；
2) According to the difference value between the target position and the actual position, combining a dynamics error model to meet the maximum constraint delta u of the steering wheel angle change rate max (k) Obtaining a feedback steering wheel angle at the current moment based on MPC control; and obtaining the target steering wheel angle at the current moment according to the feedback steering wheel angle at the current moment so as to transversely control the vehicle.
The beneficial effects are as follows: according to the invention, steering wheel corner change rate limit values are calculated adaptively according to different working conditions, specifically, the corresponding maximum steering wheel corner change rate limit value of front curvature and the corresponding maximum steering wheel corner change rate limit value of current vehicle speed are calculated according to different curvatures and vehicle speeds, the maximum steering wheel corner change rate limit value and the minimum steering wheel corner change rate limit value of current vehicle speed are restrained, and then an objective function is solved according to a dynamic error model under the constraint conditions of meeting states, control amounts and control amount change rates to obtain a control sequence in a control time domain, so that the requirements of different curvatures, vehicle speeds and other working conditions on the steering wheel corner control amount change rate can be met, and the transverse comfort is improved.
Further, if the vehicle working condition is that automatic driving is entered from non-automatic driving, steering wheel turning angle at the initial moment when MPC control is performed is enabled to be the actual steering wheel turning angle fed back currently by the vehicle when automatic driving is entered; and if not, enabling the steering wheel angle at the initial moment in MPC control to be the target steering wheel angle output at the current moment.
The beneficial effects are as follows: when the vehicle just enters automatic driving, the steering wheel angle at the initial moment in MPC control is the actual steering wheel angle fed back currently by the vehicle, so that the comfort caused by abrupt change of the steering wheel angle is prevented from being poor.
Further, the target steering wheel angle at the current moment is the sum of the feedback steering wheel angle at the current moment and the feedforward steering wheel angle at the current moment, and the feedforward steering wheel angle at the current moment is obtained by performing curvature compensation calculation on the curvature of the target track.
The beneficial effects are as follows: adding the result of the feedforward control can improve the hysteresis caused by the feedback control.
Further, the kinetic error model is:
in the formula e cg 、The lateral deviation and the lateral deviation change rate are respectively; θ e 、/>Orientation angle deviation and orientation angle deviation change rate respectively; i z Is the rotational inertia of the vehicle; c (C) f C is the cornering stiffness of the front wheel r For the cornering stiffness of the rear wheels, l r For centroid to rear wheel distance, l f The distance from the mass center to the front wheel is m is the mass of the whole vehicle, V x For dividing the speed delta along the direction of the headstock f Is the deflection angle of the front wheel,is the derivative of the heading angle.
Further, the optimization objective function used in MPC control is:
wherein J is a set objective function; x (k) is a state matrix; u (k) is a control amount, which is a steering wheel angle; n is a prediction and control time domain; x is x k Is a prediction state matrix; x is x r Is a reference state matrix; q is a state weighting matrix; u (u) k Is a steering wheel angle matrix;r is a control weighting matrix.
Further, constraint functions used in MPC control are:
x(k+1)＝A d x(k)+B d u(k)
x min ≤x(k)≤x max
u_min≤u(k)≤u_max
|Δu(k)|≤Δu max
x(0)＝x 0
u(0)＝u 0
A d ＝(I-0.5A*T s ) -1 (I+0.5A*T s )
B d ＝B*T s
wherein x is min And x max Respectively minimum constraint and maximum constraint of the state matrix; u_min and u_max are the minimum constraint and the maximum constraint of the control quantity respectively; Δu (k) is the control amount change rate; deltau max A maximum constraint for controlling the rate of change of the quantity; x is x 0 In the state of the initial moment, x (0) is a matrix of the transverse distance deviation, the transverse distance deviation change rate, the course angle deviation and the course angle deviation change rate of the current moment; u (0) is the control amount at the initial time, u 0 Is the actual steering wheel angle at the current moment, T s For the control period.
Further, the clipping process is also required for the target steering wheel angle at the current time.
The beneficial effects are as follows: and carrying out amplitude limiting treatment on the target steering wheel angle so as to ensure the stable and reliable operation of the system.
Further, when the steering wheel angle change rate is larger than the normal gradient limit value, controlling the vehicle speed to be the reference vehicle speed v of the target track ref (k) And set vehicle speed v set Is smaller of (a); otherwise, controlling the speed of the vehicle in response to the target track.
The beneficial effects are as follows: considering that when the vehicle just enters automatic driving, the feedback actual steering wheel angle and the target steering wheel angle usually have larger step difference, if the steering wheel angle is directly responded, the steering wheel is suddenly changed to the target steering angle, so that the comfort is poor, and therefore, the steering wheel is smoothly transited from the current feedback actual steering wheel angle to the target steering wheel angle, when the change rate of the steering wheel angle is larger, the longitudinal response is controlled to be lower in speed (the smaller value of the reference speed of the target track and the set speed) during steering wheel centering, so that the abrasion of tires during steering wheel in-situ centering is avoided, and the steering wheel control comfort is improved.
In order to solve the technical problems, the invention also provides an automatic driving vehicle control device based on MPC control, which comprises a memory and a processor, wherein the processor is used for executing computer program instructions stored in the memory to realize the automatic driving vehicle control method based on MPC control and can achieve the same beneficial effects as the method.
Drawings
FIG. 1 is a prior art schematic diagram of autopilot lateral MPC control;
FIG. 2 is a flow chart of solving MPC feedback steering wheel angle constraints in view of steering wheel angle rate of change in accordance with the present invention;
fig. 3 is a flow chart of steering wheel angle smoothing and speed limiting upon entry into autopilot in accordance with the present invention.
Detailed Description
The main conception of the invention is that the steering wheel turning angle change rate constraint is adaptively calculated in real time according to different working conditions, then an objective function is solved according to a dynamics error model under the constraint conditions of meeting state, control quantity and control quantity change rate to obtain a control sequence in a control time domain, and the transverse comfort is improved while meeting the requirements of different working conditions on the control quantity change rate; moreover, for smoothing from an actual steering wheel angle to a target steering wheel angle and controlling the vehicle to run slowly during smoothing upon entering automatic driving, not only wear of tires during steering wheel in-situ return is avoided, but also steering wheel control comfort is improved.
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. The following examples will assist those skilled in the art in further understanding the present invention, but are not intended to limit the invention in any way. It should be noted that it will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the spirit of the invention, which are all within the scope of the invention.
Method embodiment:
according to the invention, steering wheel turning angle change rate constraint is calculated in real time and adaptively according to different working conditions, then an objective function is solved according to a dynamic error model under the constraint conditions of satisfying state, control quantity and control quantity change rate to obtain feedback steering wheel turning angles in a control time domain, and a MPC feedback steering wheel turning angle flow chart is solved by considering the steering wheel turning angle change rate constraint, as shown in figure 2.
1) Obtaining the maximum steering wheel rotation angle change rate limit value delta u of the current curvature according to the curvature k table of the target track (obtained according to the minimum turning radius of the actual vehicle and the curvature calibration of the driving working condition) k_lmt (k)。
2) Obtaining the maximum steering wheel angle change rate limit value delta u of the current vehicle speed according to v (k) table lookup (obtained by vehicle speed calibration according to the driving working condition) v_lmt (k)。
3) Taking the two results obtained in step 1) and step 2) down to obtain the maximum constraint of the steering wheel angle change rate, namely Deltau max (k)＝min(Δu k_lmt (k)，Δu v_lmt (k))。
4) I.e. in the satisfied state (x) according to the dynamic error model min 、x max ) Control amount u min 、u max Control amount change rate Deltau max (k) Solving targets under constraint conditionsThe function obtains a control sequence in a control time domain, and the feedback steering wheel angle u at the current moment is obtained cmd (k) A. The invention relates to a method for producing a fibre-reinforced plastic composite Wherein, the dynamics error model of the vehicle is as follows:
in the formula e cg 、Respectively a lateral deviation and a lateral deviation change rate, wherein the unit of the lateral deviation is m; θ e 、/>The angular deviation and the angular deviation change rate are respectively, and the angular unit radian is the angular unit radian; i Z The unit Kg.m2 is the rotational inertia of the vehicle; c (C) f C is the cornering stiffness of the front wheel r For the cornering stiffness of the rear wheels, l r For centroid to rear wheel distance, l f The distance from the mass center to the front wheel is m is the mass of the whole vehicle, V x For dividing the speed delta along the direction of the headstock f Is the front wheel deflection angle +>Is the derivative of the heading angle. The kinetic error model is expressed as +.>The set optimization objective function and constraint function are as follows:
x(k+1)＝A d x(k)+B d u(k)
x min ≤x(k)≤x max
u_min≤u(k)≤u_max
|Δu(k)|≤Δu max
x(0)＝x 0
u(0)＝u 0
A d ＝(I-0.5A*T s ) -1 (I+0.5A*T s )
B d ＝B*T s
wherein J is a set objective function; x (k) is a state matrix; u (k) is a control amount, which is a steering wheel angle; n is a prediction and control time domain, and the unit is s; x is x k For predicting state matrix；x r As a reference state matrix, default to 0; q is a state weighting matrix; u (u) k Is a steering wheel angle matrix; r is a control weighting matrix; x is x min And x max Respectively minimum and maximum constraints of the state matrix; u_min and u_max are the minimum and maximum constraints of the control quantity respectively; deltau max The maximum constraint for the control quantity change rate is obtained through real-time self-adaptive calculation according to different working conditions; x is x 0 Is the state at the initial moment; u (u) 0 The control quantity is the control quantity at the initial moment; x (0) is a matrix of 4 rows and 1 columns of transverse distance deviation, transverse distance deviation change rate, course angle deviation and course angle deviation change rate at the current moment; u (0) is the actual turning angle of the steering wheel at the current moment, T s For the control period.
5) When the feedback steering wheel angle at the previous moment and the feedforward steering wheel angle at the current moment (obtained by performing curvature compensation calculation on the curvature of the target track) are added, further performing amplitude limiting treatment to obtain the target steering wheel angle at the current moment so as to perform transverse control on the vehicle.
In addition, there is usually a large step difference between the actual steering wheel angle fed back when the automatic driving is just entered and the target steering wheel angle, and the target steering wheel angle cannot be directly responded, otherwise, the steering wheel will suddenly change to the target steering angle, so that the comfort is poor. At this time, it is necessary to smoothly transition from the actual steering wheel angle fed back at present to the target steering wheel angle, during which the steering wheel cannot directly respond to the desired speed of the target track due to the fact that the steering wheel does not respond to the target steering wheel angle necessarily causes a lateral control error, but also cannot statically steer back, which causes tire wear, so that the present invention controls a vehicle speed (calibration value) with a lower longitudinal response during steering wheel back, and a specific flowchart is shown in fig. 3 below.
1) Judging whether the vehicle enters an automatic driving mode or not, and judging that the vehicle enters the automatic driving mode according to the fact that the previous moment is the non-automatic driving mode and the current moment is the automatic driving mode: when entering automatic driving, the initial time control quantity u (0) in the MPC constraint is the actual steering wheel angle fed back by the vehicle currently, otherwise, the initial time control quantity u (0) is equal to the initial target steering wheel angle output by the current time MPC.
2) The steering wheel rotation angle change rate constraint is adaptively calculated in real time according to different working conditions, namely the steering wheel change rate constraint limit value is obtained by looking up a table according to the current speed and the curvature, and the specific process is shown in figure 2.
3) Judging whether the speed is limited: when the steering wheel angle change rate is less than or equal to the normal gradient limit value (a calibration value, such as 3rad/10ms, which is smaller than the maximum constraint of the steering wheel angle change rate), the speed limit flag bit is reset, the speed of the target track is responded at the moment, otherwise (the steering wheel angle change rate is greater than the normal gradient limit value), the speed limit flag bit is activated, and the speed v is controlled at the moment cmd (k) Reference vehicle speed v as target track ref (k) And set vehicle speed v set (calibration value, e.g. 3 km/h), i.e. v cmd (k)＝min(v ref (k),v set ). The content of this section is vehicle speed control, which does not involve the MPC control in fig. 1 and requires separate control.
In summary, the invention has the following characteristics: 1) The steering wheel angle change rate limit value is calculated adaptively according to different working conditions, and the transverse comfortableness can be improved while the requirements of the working conditions such as different curvatures, vehicle speeds and the like on the steering wheel angle control quantity change rate are met. 2) For the smooth steering wheel angle from the actual steering wheel angle to the target steering wheel angle when automatic driving is just entered and the controlled vehicle runs slowly in the smooth process, the tire abrasion during the steering wheel in-situ alignment is avoided and the steering wheel control comfort is improved.
Device example:
the embodiment of the invention discloses an automatic driving vehicle control method device based on MPC control, which comprises a memory, a processor and an internal bus, wherein the processor and the memory are communicated with each other and data are interacted through the internal bus. The memory includes at least one software functional module stored in the memory, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory to implement an automatic driving vehicle control method based on MPC control in the method embodiment of the invention. The processor may be a microprocessor MCU, a programmable logic device FPGA, or other processing device. The memory may be various types of memories for storing information by using electric energy, such as RAM, ROM, etc., and may be other types of memories.

Claims (9)

1. An automatic driving vehicle control method based on MPC control is characterized by comprising the following steps:
1) Obtaining the maximum steering wheel turning angle change rate limit value Deltau of the current curvature according to the curvature of the target track k_lmt (k) And obtaining the maximum steering wheel rotation angle change rate limit value Deltau of the current vehicle speed according to the actual vehicle speed v_lmt (k) Taking the minimum value of the two limit values to obtain the maximum constraint delta u of the steering wheel angle change rate max (k)；
2) According to the difference value between the target position and the actual position, combining a dynamics error model to meet the maximum constraint delta u of the steering wheel angle change rate max (k) Obtaining a feedback steering wheel angle at the current moment based on MPC control; and obtaining the target steering wheel angle at the current moment according to the feedback steering wheel angle at the current moment so as to transversely control the vehicle.
2. The MPC control-based automatic driving vehicle control method according to claim 1, wherein if the vehicle condition is to enter automatic driving from non-automatic driving, the steering wheel angle at the initial time when the MPC control is entered into automatic driving is made to be the actual steering wheel angle currently fed back by the vehicle; and if not, enabling the steering wheel angle at the initial moment in MPC control to be the target steering wheel angle output at the current moment.
3. The MPC control-based automatic driving vehicle control method according to claim 1, wherein the target steering wheel angle at the current time is a sum of the feedback steering wheel angle at the current time and the feedforward steering wheel angle at the current time, and the feedforward steering wheel angle at the current time is obtained by performing curvature compensation calculation on the curvature of the target track.
4. The MPC control-based automatic driving vehicle control method of claim 1, wherein the dynamics error model is:
in the formula e cg 、The lateral deviation and the lateral deviation change rate are respectively; θ e 、/>Orientation angle deviation and orientation angle deviation change rate respectively; i Z Is the rotational inertia of the vehicle; c (C) f C is the cornering stiffness of the front wheel r For the cornering stiffness of the rear wheels, l r For centroid to rear wheel distance, l f The distance from the mass center to the front wheel is m is the mass of the whole vehicle, V x For dividing the speed delta along the direction of the headstock f Is the front wheel deflection angle +>Is the derivative of the heading angle.
5. The MPC control-based automatic driving vehicle control method according to claim 1, wherein the optimization objective function used in the MPC control is:
wherein J is a set objective function; x (k) is a state matrix; u (k) is a control amount, which is a steering wheel angle; n is a prediction and control time domain; x is x k Is a prediction state matrix; x is x r Is a reference state matrix; q is a state weighting matrix; u (u) k Is a steering wheel angle matrix; r is a control weighting matrix.
6. The MPC control-based automatic driving vehicle control method according to claim 5, wherein the constraint function used in the MPC control is:
x(k+1)＝A d x(k)+B d u(k)
x min ≤x(k)≤x max
u_min≤u(k)≤u_max
|Δu(k)|≤Δu max
x(0)＝x 0
u(0)＝u 0
A d ＝(I-0.5A*T s ) -1 (I+0.5A*T s )
B d ＝B*T s
wherein x is min And x max Respectively the minimum of the state matrixBeam and maximum constraint; u_min and u_max are the minimum constraint and the maximum constraint of the control quantity respectively; Δu (k) is the control amount change rate; deltau max A maximum constraint for controlling the rate of change of the quantity; x is x 0 In the state of the initial moment, x (0) is a matrix of the transverse distance deviation, the transverse distance deviation change rate, the course angle deviation and the course angle deviation change rate of the current moment; u (0) is the control amount at the initial time, u 0 Is the actual steering wheel angle at the current moment, T s For the control period.
7. The MPC control-based automatic driving vehicle control method according to any one of claims 1 to 6, wherein the clipping process is further performed on the target steering wheel angle at the present time.
8. The MPC control-based automatic driving vehicle control method according to claim 1, wherein the vehicle speed is controlled to be the reference vehicle speed v of the target track when the steering wheel angle change rate is greater than the normal gradient limit value ref (k) And set vehicle speed v set Is smaller of (a); otherwise, controlling the speed of the vehicle in response to the target track.
9. An autonomous vehicle control apparatus based on MPC control, characterized by comprising a memory and a processor for executing computer program instructions stored in the memory to implement the autonomous vehicle control method based on MPC control as claimed in any of claims 1 to 8.
CN202310466552.0A 2023-04-26 2023-04-26 Automatic driving vehicle control method and device based on MPC control Pending CN116679592A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310466552.0A CN116679592A (en) 2023-04-26 2023-04-26 Automatic driving vehicle control method and device based on MPC control

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310466552.0A CN116679592A (en) 2023-04-26 2023-04-26 Automatic driving vehicle control method and device based on MPC control

Publications (1)

Publication Number Publication Date
CN116679592A true CN116679592A (en) 2023-09-01

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Country Status (1)

Country Link
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