CN112319610A - Man-machine sharing steering control method for intelligent automobile - Google Patents

Man-machine sharing steering control method for intelligent automobile Download PDF

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CN112319610A
CN112319610A CN202011097200.5A CN202011097200A CN112319610A CN 112319610 A CN112319610 A CN 112319610A CN 202011097200 A CN202011097200 A CN 202011097200A CN 112319610 A CN112319610 A CN 112319610A
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vehicle
steering
angle
driver
intelligent automobile
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CN112319610B (en
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谢正超
李文锋
赵晶
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South China University of Technology SCUT
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
    • B62D—MOTOR VEHICLES; TRAILERS
    • B62D15/00—Steering not otherwise provided for
    • B62D15/02—Steering position indicators ; Steering position determination; Steering aids
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0028—Mathematical models, e.g. for simulation
    • B60W2050/0029—Mathematical model of the driver
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0028—Mathematical models, e.g. for simulation
    • B60W2050/0031—Mathematical model of the vehicle
    • B60W2050/0034—Multiple-track, 2D vehicle model, e.g. four-wheel model
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0028—Mathematical models, e.g. for simulation
    • B60W2050/0037—Mathematical models of vehicle sub-units

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  • Engineering & Computer Science (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Automation & Control Theory (AREA)
  • Human Computer Interaction (AREA)
  • Steering Control In Accordance With Driving Conditions (AREA)

Abstract

The invention discloses a man-machine sharing steering control method of an intelligent automobile, aims to improve the path tracking performance and the driver control comfort of the intelligent automobile in a time delay communication environment, and belongs to the field of intelligent automobile driving auxiliary systems. The method comprises the following steps: establishing a human-vehicle-road system model; determining a system control target; and solving the gain of the shared steering controller, calculating the required active steering angle, and performing online control on the intelligent automobile. The invention can effectively improve the automobile path tracking precision and improve the operation comfort of the driver. Particularly, the invention considers the time delay phenomenon in the control loop in the man-machine sharing steering control of the intelligent automobile, and the delay comprises three types of network induced delay, signal transmission delay and actuator delay, so that the method has stronger robustness while ensuring the path tracking performance of the automobile and has more superiority in a time delay environment.

Description

Man-machine sharing steering control method for intelligent automobile
Technical Field
The invention belongs to the field of intelligent automobile driving auxiliary systems, and particularly relates to a man-machine sharing steering control method of an intelligent automobile.
Background
With the increasing holding capacity of automobiles, the road traffic environment becomes more and more complex, which puts an urgent need on improving the driving safety and the driving comfort of vehicles. The intelligent automobile can assist a driver in controlling the automobile in three aspects of perception, decision and execution by carrying a sensing part, a calculating unit and an advanced control executing device, and is an effective measure for improving the active safety of the automobile, improving the driving comfort and reducing or avoiding traffic accidents. As one of core technologies of an intelligent automobile, man-machine shared steering control means that a driver and an automation system both have an online control right for a vehicle steering function, and is a key technology for ensuring that a vehicle tracks an expected path. In the man-machine shared steering control technology, an automatic system corrects and compensates the operation behavior of a driver in real time through an active steering device or a steer-by-wire device so as to achieve the purposes of improving the path tracking performance and reducing the burden of the driver.
In order to meet the real-time communication requirement and performance requirement of an automobile electric control system, a shared vehicle-mounted Network is widely applied to intelligent automobiles, such as a Controller Area Network (CAN), a Local Interconnect Network (LIN), and the like. On one hand, the vehicle-mounted network communication has the advantages of realizing information resource sharing, improving diagnosis capability, reducing cost, being easy to expand and maintain and the like, and greatly promotes the development of intellectualization, automation and standardization of the automobile; on the other hand, the fact that the bandwidth of the vehicular network is limited inevitably causes constraint problems such as network induced delay, data packet loss, communication congestion, etc., and brings a serious challenge to the current control design. At present, a human-computer cooperation shared steering control method based on a constraint model prediction theory is proposed in an invention patent with a patent number of CN 107323457B, however, the method does not consider a network induced delay factor in the system, which may impair the performance of the designed controller and even cause instability of the system.
Disclosure of Invention
In order to realize the man-machine sharing control of the intelligent automobile in the network communication environment, the invention further considers network induction delay, signal transmission delay and actuator delay, and provides a man-machine sharing control method with time delay robustness, aiming at improving the path tracking performance and the driver control comfort of the intelligent automobile in the time delay communication environment.
The technical scheme adopted by the invention is as follows:
a man-machine sharing control method of an intelligent automobile is realized through the following steps:
respectively establishing a vehicle dynamics equation, a vehicle kinematics equation and a single-point preview driver steering model, and further establishing a global human-vehicle-road system model;
performing subsequent control design aiming at the established human-vehicle-road system model, wherein the subsequent control design comprises determining a system control target and designing a human-machine shared steering system of the intelligent automobile, the system control target is to ensure that the vehicle tracks an expected path with the minimum lateral error and heading angle error, and the conditions of I Z (t) I2＜γ||ω(t)||2Wherein the output performance vector z (t) ═ ye ψe]TCx (t), x (t) is the state vector of the system, C is the controlled output matrix; y iseIndicating that the vehicle is at the pre-aiming distance ldLateral error from the desired path, which can be expressed as ye＝yc+ldψe；ycAnd psieRespectively representing a lateral error and a heading angle error of the current position of the vehicle, wherein psieCan be expressed as an actual yaw angle psi and a desired heading angle psi of the vehicledA difference of (i.e.. psi)e＝ψ-ψd(ii) a Rho (sigma) refers to the curvature of a road, gamma is a reference value of a closed-loop system for inhibiting external interference, which is obtained by adopting a shared steering controller, and omega (t) is the interference input of the system; the control input u (t) of the man-machine sharing steering system is Kx (t-tau (t)), wherein tau (t) refers to the total time delay in a control loop, is the sum of network induced delay, signal transmission delay and actuator delay, and satisfies the condition that tau is more than or equal to 0 and less than or equal to taum≤τ(t)≤τMIn the formula, τmAnd τMRespectively representing the lower bound and the upper bound of the total time delay in the control loop, and K represents the gain matrix of the shared steering controller;
and obtaining an active steering angle by calculating a control input u (t) ═ Kx (t), and applying the active steering angle to the vehicle by a man-machine shared steering system to realize intelligent vehicle path tracking and safe driving.
Further, the vehicle dynamics equation is as follows:
Figure BDA0002724138120000021
wherein:
Fyf＝Fyfl+Fyfr＝2Cfαf，Fyr＝Fyrl+Fyrr＝2Crαr，
Figure BDA0002724138120000022
finger front
A wheel steering angle; deltadAnd deltacRespectively indicating the steering wheel angle of the driver and the active steering angle of the steering system; rsRefers to the gear ratio of the steering system; v. ofyAnd vxRespectively, the lateral speed and the longitudinal speed of the vehicle; psi,
Figure BDA0002724138120000023
And
Figure BDA0002724138120000024
respectively indicating the yaw angle, the yaw angular velocity and the yaw angular acceleration of the vehicle; beta refers to the centroid slip angle of the vehicle, which can be approximated as vyAnd vxThe ratio of (A) to (B); fwAnd lwThe lateral interference force of the vehicle and the distance between the stress point and the mass center are indicated; i iszRefers to the yaw moment of inertia of the vehicle; lfAnd lrRespectively the distances from the center of mass of the vehicle to the front axle and the rear axle; fyfIndicates the total cornering force of the front wheels, which is the front left wheel cornering force FyflAnd front right wheel cornering force FyfrSumming; fyrIndicates the total cornering force of the rear wheel, which is the rear left wheel cornering force FyrlAnd rear right wheel side biasing force FyrrSumming; cfAnd CrRespectively refer to the cornering stiffness of the front and rear tires of the vehicle; alpha is alphafIndicating the side of the front wheelDeflection angle; alpha is alpharIndicating the rear wheel side slip angle.
Further, the vehicle kinematics equation is as follows:
Figure BDA0002724138120000025
wherein, yeIndicating that the vehicle is at the pre-aiming distance ldLateral error from the desired path, which can be expressed as ye＝yc+ldψe；ycAnd psieRespectively indicating the lateral error and the heading angle error of the current position of the vehicle, wherein psieCan be expressed as an actual yaw angle psi and a desired heading angle psi of the vehicledA difference of (i.e.. psi)e＝ψ-ψd(ii) a ρ (σ) denotes a road curvature.
Further, the single point preview driver steering model is as follows:
Figure BDA0002724138120000031
is approximated to
Figure BDA0002724138120000032
In the formula taud＝τd1+τd2，
Figure BDA0002724138120000033
s is a Laplace transform operator; the expression of the driver steering model in the time domain is:
Figure BDA0002724138120000034
wherein G ish，τd1，τd2And τpRespectively indicating the turning angle gain, pure time delay, neuromuscular time delay and aiming time of a driver in a driver model; tau isd＝τd1+τd2，
Figure BDA0002724138120000035
δdAnd ypRespectively representing the driver's angle of rotation deltadAnd the pre-aiming distance l of the driverpTransverse error y ofpWherein l ispCan be represented as lp＝τpvx，ypCan be represented as yp＝ye+(lp-ld)ψe(ii) a s is a Laplace transform operator;
Figure BDA0002724138120000036
representing the first and second derivatives of the driver steering angle, respectively.
Further, the human-vehicle-road system model is as follows:
Figure BDA0002724138120000037
in the formula (I), the compound is shown in the specification,
Figure BDA0002724138120000038
ω(t)＝[Fwρ(σ)]T，u(t)＝δc，
Figure BDA0002724138120000039
Figure BDA00027241381200000310
where x (t) is the state vector of the system, ω (t) is the interference input to the system, u (t) is the control input to the system, A, B1And B2Respectively a system matrix, an interference input matrix and a control input matrix.
Further, in the control input u (t) Kx (t- τ (t)) of the human-machine shared steering system, the gain matrix K of the controller is obtained by solving the following two linear inequalities and its calculation formula is: k is YW-1In the following two inequalities, τm、τMκ and γ are positive numbers given by the user according to actual needs P, R1、R2、S1、S2、Q1、Q2、Q3、Q4For positive definite matrices of appropriate dimensions, M1、M2W and Y are general matrices of appropriate dimensions;
Figure BDA0002724138120000041
Figure BDA0002724138120000042
in the formula:
Figure BDA0002724138120000043
Figure BDA0002724138120000044
Figure BDA0002724138120000045
Figure BDA0002724138120000046
Ω6＝[Γ5Γ6]+[Γ5Γ6]T
Γ1＝diag(S2+Q3 3(S2+Q3) 5(S2+Q3))，Γ2＝diag(S2+Q4 3(S2+Q4) 5(S2+Q4))
Γ3＝diag(Q3 3Q3 5Q3)，Γ4＝diag(Q4 3Q4 5Q4)
Γ5＝e1+e11β，
Figure BDA0002724138120000047
F1(t)＝[e1 τme5 (τ(t)-τm)e6+(τM-τ(t))e7 τme8]，F2＝[e11 e1-e2 e2-e4 2(e1-e5)]
F3＝[e2-e3 e2+e3-2e6 e2-e3+6e6-6e9]，F4＝[e3-e4 e3+e4-2e7 e3-e4+6e7-6e10]
Figure BDA0002724138120000048
τc＝τM-τm，
Figure BDA0002724138120000051
where n is 1, 2.
Further, the obtained shared steering controller is used for carrying out on-line control on the intelligent automobile, so that the global system meets the requirements of asymptotic stability and expected performance | | z (t) |2＜γ||ω(t)||2Wherein γ is an inhibition indicator reference value.
The invention has the beneficial effects that:
the invention considers the time delay phenomenon in the control loop in the man-machine sharing steering control of the intelligent automobile, and the delay comprises three types of network induction delay, signal transmission delay and actuator delay, thereby ensuring the path tracking performance of the automobile, having stronger robustness and having more superiority in the time delay environment.
Drawings
FIG. 1 is a design flow chart of the present invention.
FIG. 2 is a schematic diagram of a model of the vehicle dynamics integration mechanism of the present invention.
FIG. 3 is a comparison graph of a vehicle path under a J-turn condition according to an embodiment of the present invention.
FIG. 4 is a comparison chart of vehicle heading angles under J-turn operating conditions according to an embodiment of the invention.
FIG. 5 is a comparison chart of driver steering angles under the J-turn condition according to an embodiment of the present invention.
FIG. 6 is a graph comparing driver steering angle rate of change under J-turn conditions, according to an embodiment of the present invention.
Detailed Description
The present invention is further described in the following examples and with reference to the accompanying drawings so that one skilled in the art can better understand the present invention and can practice it, but the examples should not be construed as limiting the present invention.
FIG. 1 is a flow chart of an embodiment of the present invention, comprising the steps of:
step one, establishing a human-vehicle-road system model:
the human-vehicle-road system is a closed-loop system integrating vehicle dynamics, vehicle kinematics, driver steering behavior and road curvature information into a whole, respectively considering vehicle dynamics behavior, kinematics behavior and driver steering behavior in the modeling of the vehicle system.
1) As shown in fig. 2, X-Y is a plane coordinate system fixed to the ground, where X denotes a direction of a straight road surface and Y denotes a direction perpendicular to the X axis; x-y is a coordinate system fixed to the vehicle, where x represents the longitudinal direction of the vehicle and y represents the lateral direction of the vehicle, with the origin of the coordinate system located at the center of mass of the vehicle. The invention focuses on the lateral dynamics and the stability of the vehicle, ignores the longitudinal force behavior of the vehicle, and establishes a vehicle dynamics equation under the assumption of a small corner:
Figure BDA0002724138120000052
wherein, Fyf＝Fyfl+Fyfr＝2Cfαf，Fyr＝Fyrl+Fyrr＝2Crαr，
Figure BDA0002724138120000061
Figure BDA0002724138120000062
The unit of the steering angle of the front wheel is as follows: rad; deltadAnd deltacThe steering wheel angle of a driver and the active steering angle of a steering system are respectively indicated, and the unit is as follows: rad; rsThe unit is 1, which refers to the transmission ratio of a steering system; v. ofyAnd vxThe lateral speed and the longitudinal speed of the vehicle are respectively indicated, and the unit is as follows: m/s; psi,
Figure BDA0002724138120000063
And
Figure BDA0002724138120000064
respectively refer to the yaw angle, the yaw velocity and the yaw acceleration of the vehicle, and the unit is respectively as follows: rad, rad/s and rad/s2(ii) a Beta refers to the centroid slip angle of the vehicle, with the unit: rad, which can be approximated by vyAnd vxThe ratio of (A) to (B); fwAnd lwThe unit of the distance between the lateral interference force of the vehicle and the stress point and the center of mass is N and m; i iszRefers to the yaw moment of inertia of the vehicle, with the unit: kg m2；lfAnd lrThe distances from the center of mass of the vehicle to the front axle and the rear axle are respectively expressed in the following units: m; fyfIndicates the total cornering force of the front wheels, which is the front left wheel cornering force FyflAnd front right wheel cornering force FyfrThe sum, the unit is: n; fyrIndicates the total cornering force of the rear wheel, which is the rear left wheel cornering force FyrlAnd rear right wheel side biasing force FyrrThe sum, the unit is: n; cfAnd CrRespectively refer to the cornering stiffness of the front and rear tires of the vehicle, with the unit: n/rad; alpha is alphafRepresents the front wheel side slip angle in units of: rad; alpha is alpharRepresents the rear wheel side slip angle in units of: and (7) rad.
2) As shown in fig. 2, the vehicle kinematics equation is established:
Figure BDA0002724138120000065
wherein, yeIndicating that the vehicle is at the pre-aiming distance ldLateral error from the desired path in units of: m, which can be represented as ye＝yc+ldψe；ycAnd psieRespectively showing the lateral error and the course angle error of the current position of the vehicle, wherein the unit is respectively as follows: m and rad, whereineCan be expressed as an actual yaw angle psi and a desired heading angle psi of the vehicledA difference of (i.e.. psi)e＝ψ-ψd(ii) a ρ (σ) denotes road curvature in units of: 1/m.
3) Establishing a single-point preview driver steering model:
Figure BDA0002724138120000066
is approximated to
Figure BDA0002724138120000067
Wherein G ish，τd1And τd2The unit respectively refers to the turning angle gain, the pure time delay and the neuromuscular time delay of a driver in a driver model, and the unit respectively is as follows: 1. seconds and seconds; tau isd＝τd1+τd2，
Figure BDA0002724138120000068
δdAnd ypRespectively representing the turning angle of a driver and the pre-aiming distance l of the driverpThe unit of the transverse error is as follows: rad and m, wherein lpCan be represented as lp＝τpvx，ypCan be represented as yp＝ye+(lp-ld)ψe(ii) a s is the Laplace transform operator.
The expression of the driver steering model in the time domain is:
Figure BDA0002724138120000071
in the formula (I), the compound is shown in the specification,
Figure BDA0002724138120000072
representing the first and second derivatives, tau, of the driver angle, respectivelypIndicating the preview time in seconds.
4) Finally, establishing a human-vehicle-road system model:
Figure BDA0002724138120000073
where x (t) is the state vector of the system, ω (t) is the interference input to the system, u (t) is the control input to the system, A, B1And B2Respectively a system matrix, an interference input matrix and a control input matrix.
In the formula (I), the compound is shown in the specification,
Figure BDA0002724138120000074
ω(t)＝[Fw ρ(σ)]T，u(t)＝δc，
Figure BDA0002724138120000075
Figure BDA0002724138120000076
step two, determining a control target
The purpose of shared steering control is to ensure that the vehicle is able to track a desired path (reference path) with minimal lateral and heading angle errors, while good path tracking performance also means that vehicle dynamic stability and driver handling comfort are ensured. Thus, the output performance vector is as follows:
z(t)＝[ye ψe]T＝Cx(t)
wherein C represents the controlled output matrix,
Figure BDA0002724138120000077
the performance index is considered as follows: | | z (t) | non-woven phosphor2＜γ||ω(t)||2Wherein gamma is a reference value of the inhibition index, and the size of the reference value can be adjusted by a user within an allowable range according to actual needs.
Step three, designing a shared steering controller:
the control input aiming at the man-machine sharing steering system of the intelligent automobile is as follows:
u(t)＝Kx(t-τ(t))
wherein u (t) represents the control input quantity, t represents the time variable, and τ (t) refers to the total time delay (i.e. the sum of the network-induced delay, the signal transmission delay and the actuator delay) in the control loop and satisfies 0 ≦ τm≤τ(t)≤τM. Wherein, taumAnd τMThe lower and upper bounds, respectively, of the total time delay in the control loop, and K represents the gain matrix of the controller. Given a positive number τm、τMκ, and γ, if a positive definite matrix of appropriate dimensions P, R exists1、R2、S1、S2、Q1、Q2、Q3、Q4General matrix M1、M2W and Y are such that the following two linear inequalities hold simultaneously, the calculation formula of the control gain matrix is: k is YW-1。
Figure BDA0002724138120000081
Figure BDA0002724138120000082
The representation of each matrix in the formula is as follows:
Figure BDA0002724138120000083
Figure BDA0002724138120000084
Figure BDA0002724138120000085
Ω6＝[Γ5Γ6]+[Γ5Γ6]T
Γ1＝diag(S2+Q3 3(S2+Q3) 5(S2+Q3))，Γ2＝diag(S2+Q4 3(S2+Q4) 5(S2+Q4))
Γ3＝diag(Q3 3Q3 5Q3)，Γ4＝diag(Q4 3Q4 5Q4)
Γ5＝e1+e11β，
Figure BDA0002724138120000086
F1(t)＝[e1 τme5 (τ(t)-τm)e6+(τM-τ(t))e7 τme8]，F2＝[e11 e1-e2 e2-e4 2(e1-e5)]
F3＝[e2-e3 e2+e3-2e6 e2-e3+6e6-6e9]，F4＝[e3-e4 e3+e4-2e7 e3-e4+6e7-6e10]
Figure BDA0002724138120000087
τc＝τM-τm，
Figure BDA0002724138120000091
where n is 1, 2.., 12, which is in the matrixOf the symmetry term, XTRepresenting the transpose of matrix X.
τm、τMκ and γ are positive numbers given by the user according to actual needs. P, R1、R2、S1、S2、Q1、Q2、Q3、Q4For positive definite matrices of any appropriate dimension, M1、M2W and Y are general matrices of any suitable dimension defined for deriving controller design conditions, in the sense of constructing sufficient conditions to ensure that the system meets stability and performance requirements. Therefore, the two Linear Matrix Inequalities (LMI) are a sufficient condition for the controller to exist and have solvability, and the two Matrix inequalities are solved by the corresponding LMI toolbox, so that the desired gain K of the shared human-computer controller can be obtained.
And step three, calculating control input u (t) ═ Kx (t-tau (t)), wherein the calculated control input is the required active steering angle and is applied to the vehicle through a man-machine shared steering system, and the intelligent vehicle is controlled on line, so that intelligent vehicle path tracking and safe driving are realized.
In the embodiment, the time delay phenomenon in the control loop is considered in the man-machine sharing steering control of the intelligent automobile, and the delay comprises the types of network induced delay, signal transmission delay, actuator delay and the like, so that the path tracking performance of the automobile is ensured, the robustness is high, and the advantage is good in the time delay environment.
The main technical performance indexes and equipment parameters of the man-vehicle-road system used in the embodiment are as follows: m 1412kg, Iz＝1536.7kg·m2，Cf＝49412N/rad，Cr＝60174N/rad，lf＝1.016m，lr＝1.458m，vx＝10m/s，ld＝0.5m，Fw＝300N，lw＝0.3m，Gh＝-2，τd1＝0.10s，τd2＝0.22s，τp＝1.5s，Rs＝22，τm＝0.001s、τM0.039s and k 1. Gamma is derived fromThe reference value of the suppression index of the closed-loop system obtained by the shared steering controller to the external interference can be adjusted and set by a user within an allowable range according to actual needs. It is to be noted that the minimum value of the satisfied inequality condition γ in this example is γminIn other words, the user can satisfy the requirement of 2.4996 as long as he selects the suppression index reference value γ not less than this value.
In this example, the minimum inhibition index reference value, i.e., γ 2.4996, is selected.
Given a circular path of radius 500m with a curvature of
Figure BDA0002724138120000092
FIG. 3 is a comparison graph of a vehicle path under a J-turn condition, FIG. 4 is a comparison graph of a vehicle heading angle under the J-turn condition according to an embodiment of the invention, FIG. 5 is a comparison graph of a driver turning angle under the J-turn condition according to an embodiment of the invention, and FIG. 6 is a comparison graph of a driver turning angle change rate under the J-turn condition according to an embodiment of the invention. As can be seen from the figure, the method can effectively reduce the path tracking error, well inhibit the steering angle and the change rate of the driver, and can effectively improve the path tracking precision and the operation comfort of the driver.
The above embodiments are merely illustrative of the technical ideas and features of the present invention and are intended to enable those skilled in the art to better understand and implement the same. The protection scope of the present invention is not limited to the above embodiments, and all equivalent changes and modifications made according to the principles and design ideas disclosed by the present invention are within the protection scope of the present invention.

Claims (7)

1. A man-machine sharing steering control method of an intelligent automobile is characterized by comprising the following steps:
respectively establishing a vehicle dynamics equation, a vehicle kinematics equation and a single-point preview driver steering model, and further establishing a global human-vehicle-road system model;
performing subsequent control design aiming at the established human-vehicle-road system model, including determining system control target and designing intelligent automobileThe man-machine sharing steering system of the vehicle has the control aim of ensuring that the vehicle tracks an expected path with the minimum lateral error and heading angle error and meets the condition that | | z (t) | air suspension2＜γ||ω(t)||2Wherein the output performance vector z (t) ═ yeψe]TCx (t), x (t) is the state vector of the system, C is the controlled output matrix; y iseIndicating that the vehicle is at the pre-aiming distance ldLateral error from the desired path, which can be expressed as ye＝yc+ldψe；ycAnd psieRespectively representing a lateral error and a heading angle error of the current position of the vehicle, wherein psieCan be expressed as an actual yaw angle psi and a desired heading angle psi of the vehicledA difference of (i.e.. psi)e＝ψ-ψd(ii) a Rho (sigma) refers to the curvature of a road, gamma is a reference value of a closed-loop system for inhibiting external interference, which is obtained by adopting a shared steering controller, and omega (t) is the interference input of the system; the control input u (t) of the man-machine sharing steering system is Kx (t-tau (t)), wherein tau (t) refers to the total time delay in a control loop, is the sum of network induced delay, signal transmission delay and actuator delay, and satisfies the condition that tau is more than or equal to 0 and less than or equal to taum≤τ(t)≤τMIn the formula, τmAnd τMRespectively representing the lower bound and the upper bound of the total time delay in the control loop, and K represents the gain matrix of the shared steering controller;
the method comprises the steps of obtaining an active steering angle through calculating control input u (t) ═ Kx (t-tau (t)), applying the active steering angle to a vehicle through a man-machine shared steering system, and achieving intelligent automobile path tracking and safe driving.
2. The human-machine sharing steering control method for the intelligent automobile according to claim 1, wherein the vehicle dynamics equation is as follows:
Figure FDA0002724138110000011
wherein: fyf＝Fyfl+Fyfr＝2Cfαf，Fyr＝Fyrl+Fyrr＝2Crαr，
Figure FDA0002724138110000012
A front wheel steering angle; deltadAnd deltacRespectively indicating the steering wheel angle of the driver and the active steering angle of the steering system; rsRefers to the gear ratio of the steering system; v. ofyAnd vxRespectively, the lateral speed and the longitudinal speed of the vehicle; psi,
Figure FDA0002724138110000013
And
Figure FDA0002724138110000014
respectively indicating the yaw angle, the yaw angular velocity and the yaw angular acceleration of the vehicle; beta refers to the centroid slip angle of the vehicle, which can be approximated as vyAnd vxThe ratio of (A) to (B); fwAnd lwThe lateral interference force of the vehicle and the distance between the stress point and the mass center are indicated; i iszRefers to the yaw moment of inertia of the vehicle; lfAnd lrRespectively the distances from the center of mass of the vehicle to the front axle and the rear axle; fyfIndicates the total cornering force of the front wheels, which is the front left wheel cornering force FyflAnd front right wheel cornering force FyfrSumming; fyrIndicates the total cornering force of the rear wheel, which is the rear left wheel cornering force FyrlAnd rear right wheel side biasing force FyrrSumming; cfAnd CrRespectively refer to the cornering stiffness of the front and rear tires of the vehicle; alpha is alphafRepresenting a front wheel side slip angle; alpha is alpharIndicating the rear wheel slip angle, m refers to the mass of the vehicle.
3. The human-machine sharing steering control method for the intelligent automobile according to claim 1, wherein the vehicle kinematic equation is as follows:
Figure FDA0002724138110000021
wherein, yeIndicating that the vehicle is at the pre-aiming distance ldLateral error from the desired path, which can be expressed as ye＝yc+ldψe；ycAnd psieRespectively indicating the lateral error and the heading angle error of the current position of the vehicle, wherein psieCan be expressed as an actual yaw angle psi and a desired heading angle psi of the vehicledA difference of (i.e.. psi)e＝ψ-ψd(ii) a ρ (σ) denotes a road curvature.
4. The human-computer shared steering control method for the intelligent automobile according to claim 1, wherein the single-point preview driver steering model is as follows:
Figure FDA0002724138110000022
is approximated to
Figure FDA0002724138110000023
In the formula taud＝τd1+τd2，
Figure FDA0002724138110000024
s is a Laplace transform operator; the expression of the driver steering model in the time domain is:
Figure FDA0002724138110000025
wherein G ish，τd1，τd2And τpRespectively indicating the turning angle gain, pure time delay, neuromuscular time delay and aiming time of a driver in a driver model; tau isd＝τd1+τd2，
Figure FDA0002724138110000026
δdAnd ypRespectively representing the driver's angle of rotation deltadAnd the pre-aiming distance l of the driverpTransverse error ofDifference ypWherein l ispCan be represented as lp＝τpvx，ypCan be represented as yp＝ye+(lp-ld)ψe(ii) a s is a Laplace transform operator;
Figure FDA0002724138110000027
representing the first and second derivatives of the driver steering angle, respectively.
5. The human-machine sharing steering control method for the intelligent automobile according to claim 1, wherein the human-vehicle-road system model is as follows:
Figure FDA0002724138110000028
in the formula (I), the compound is shown in the specification,
Figure FDA0002724138110000029
ω(t)＝[Fw ρ(σ)]T，u(t)＝δc，
Figure FDA00027241381100000210
Figure FDA00027241381100000211
where x (t) is the state vector of the system, ω (t) is the interference input to the system, u (t) is the control input to the system, A, B1And B2Respectively a system matrix, an interference input matrix and a control input matrix.
6. The method as claimed in claim 1, wherein in the control input u (t) Kx (t- τ (t)) of the human-machine shared steering system, the gain matrix K of the controller is obtained by solving the following two linear inequalities and its calculation formulaComprises the following steps: k is YW-1In the following two inequalities, τm、τMκ and γ are positive numbers given by the user according to actual needs P, R1、R2、S1、S2、Q1、Q2、Q3、Q4For positive definite matrices of appropriate dimensions, M1、M2W and Y are general matrices of appropriate dimensions;
Figure FDA0002724138110000031
Figure FDA0002724138110000032
in the formula:
Figure FDA0002724138110000033
Figure FDA0002724138110000034
Figure FDA0002724138110000035
Figure FDA0002724138110000036
Ω6＝[Γ5Γ6]+[Γ5Γ6]T
Γ1＝diag(S2+Q3 3(S2+Q3) 5(S2+Q3))，Γ2＝diag(S2+Q4 3(S2+Q4) 5(S2+Q4))
Γ3＝diag(Q3 3Q3 5Q3)，Γ4＝diag(Q4 3Q4 5Q4)
Γ5＝e1+e11β，
Figure FDA0002724138110000037
F1(t)＝[e1 τme5 (τ(t)-τm)e6+(τM-τ(t))e7τme8]，F2＝[e11 e1-e2 e2-e4 2(e1-e5)]
F3＝[e2-e3 e2+e3-2e6 e2-e3+6e6-6e9]，F4＝[e3-e4 e3+e4-2e7 e3-e4+6e7-6e10]
Figure FDA0002724138110000041
τc＝τM-τm，
Figure FDA0002724138110000042
where n is 1, 2.
7. The human-machine sharing steering control method of the intelligent automobile according to any one of claims 1 to 6, wherein: the obtained shared steering controller is used for carrying out online control on the intelligent automobile, so that the global system meets the requirements of asymptotic stability and expected performance | | z (t) | red eyes2＜γ||ω(t)||2Wherein γ is an inhibition indicator reference value.
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