CN102167039B - Unpiloted independently-driven and steered vehicle dynamics control quantity obtaining method - Google Patents

Abstract

The invention relates to an unpiloted independently-driven and steered vehicle dynamics control quantity obtaining method. The method comprises the steps of: computing a vehicle dynamics control quantity achievable region on the basis of obtaining the information of a vehicle-road tracking system; adjusting the tracking expect deviation of the system according to the region; judging and processing the feasibility of the finally obtained vehicle dynamics control quantity; and timely evaluating and using the disturbance information of the system to improve the effectiveness, the reasonableness and the robustness of the vehicle dynamics control quantity obtained in a computation way. Therefore, the unpiloted AWID (applied wireless identifications)-AWIS (alexa web information service) vehicle can track a road path with greater curvature on a low-attachment coefficient road surface and a separation road surface at better precision and a higher speed, so that the vehicle is ideal in dynamics control effect and safe to run.

Description

Driverless operation individual drive and turn to vehicle Full Vehicle Dynamics controlling quantity preparation method

Technical field

The invention belongs to the vehicle dynamics technical field; Be particularly related to a kind of driverless operation and entirely take turns individual drive-independent steering (All Wheel Independent Drive & Steering, be called for short AWID-AWIS) preparation method of whole vehicle dynamics Controlling amount.

Background technology

Full wheel individual drive-independent steering (AWID-AWIS) vehicle is a kind of new vehicle of international automobile circle development in recent years, it has cancelled the axletree of connection left and right wheels in the conventional truck, broken through the constraint of conventional drive-steering hardware, replace novel wheel individual drive-braking-steering hardware, (vehicle moves in the plane only to be had vertically, side direction and yaw three degree of freedom, but each wheel can produce vertically and two control effortes of side direction to make vehicle obtain the driving redundancy; Suppose that vehicle has m independent wheel, produce 2m control effort, drive like this redundancy r=2m-3, m >=3), this is fundamentally guaranteeing that the AWID-AWIS vehicle has advantages of some mode of motioies that conventional truck does not possess and hardly matches, as: (1) can realize that tight turn radius turns to flexibly, skidding and crab row turn to (all wheels all participate in turning to and deflection angle equates), significantly improves vehicle mobility; (2) each wheel all can be according to the variation of pavement conditions and independently determine best straight skidding rate and best sideslip angle operation point, thus provide best vertically and the side direction control effort; (3) can realize neatly between each wheel turning to and drive and brake between coordination, significantly improve vehicle power, manipulation and safety performance; (4) excellent motor-driven and tractive performance can be realized best efficiency of energy utilization, makes more energy-saving and environmental protection of vehicle.The AWID-AWIS vehicle both can someone be driven, but also driverless operation.

It is one of chief component of AWID-AWIS Study on Vehicle Dynamic Control system that Full Vehicle Dynamics is controlled, and in order to generation, meets the controlling quantity that the AWID-AWIS Study on Vehicle Dynamic Control requires, i.e. total longitudinal force, side force and yaw moment controlling quantity.Chinese patent application " preparation method of individual drive-independent steering whole vehicle dynamics Controlling amount " (application number: 201010559872.3) described a kind ofly for there being the people to drive the preparation method of individual drive-independent steering whole vehicle dynamics Controlling amount, follow the tracks of to have controlled for the dynam to chaufeur steering wheel angle, acceleration pedal opening angle, the instruction of brake pedal opening angle; And, on driverless operation AWID-AWIS vehicle, Full Vehicle Dynamics overhead control amount is used to the tracking to road, the method that this patent provides can't meet this requirement.

Be called vehicle-road track channel by driverless operation AWID-AWIS vehicle, road and relevant sensing, the system that control subsystem forms.For this system, two steps of general employing obtain the Full Vehicle Dynamics controlling quantitys at present, that is:

1) utilize wheel speed or GPS (global positioning system) sensor to obtain the actual vehicle speed v at vehicle barycenter place _x, utilize " GIS (geographic information system)+DGPS (differencial global positioning system) ", or in-vehicle lane mark vision detection system, or road magnetic nail checking system, the current trace point P in track obtained _clateral deviating distance Δ y (vehicle barycenter and P that (crossing vehicle barycenter edge perpendicular to the plane of vehicle y direction and the intersection point of track line of centers) located _cput the projection line length of line segment on road plane), and the vertical projecting line of the vehicle longitudinal axis on road plane is with the current trace point P in track _cyaw angle deviation delta ψ between place's track centerline tangent;

2) with { v _xd, Δ y _d, Δ ψ _d(Δ y wherein _d=0, Δ ψ _d=0) control target expectation value (v for Full Vehicle Dynamics _xd, Δ y _d, Δ ψ _dbe called desired speed, desired distance deviation, expectation yaw angle deviation), calculate itself and step 1) v that obtains _x, the expectation of the system keeps track between Δ y, Δ ψ deviation e _vxd=v _xd-v _x, e _{Δ y}=Δ y _d-Δ y, e _{Δ ψ}=Δ ψ _d-Δ ψ, as the input of Full Vehicle Dynamics controller, utilize whole vehicle kinetic model and PID, sliding formwork control, fuzzy control, H _∞the method such as robust control, optimal control is calculated and is obtained Full Vehicle Dynamics controlling quantity U=[F _xf _ym _z] ^t, i.e. total longitudinal force controlling quantity F _x, total side force controlling quantity F _y, total yaw moment controlling quantity M _z, but the calculating of U is not considered the Full Vehicle Dynamics controlling quantity and can be reached the effect of contraction in territory.

Above-mentioned steps 2) the Full Vehicle Dynamics controlling quantity U obtained ^cfinally be broken down into each wheel of bottom, carried out with the form of the vertical control effort of wheel and side direction control effort, realize the dynamic (dynamical) control of AWID-AWIS whole vehicle.

This method exists following not enough:

(1) do not consider longitudinal force and the side force information of each wheel of bottom, and the Full Vehicle Dynamics controlling quantity calculate obtained accordingly can reach domain information, this makes the Full Vehicle Dynamics controlling quantity of finally obtaining

may be unreasonable, can't by the bottom wheel that has constraint vertically and the side direction control effort effectively carry out, thereby conflicting between generation Full Vehicle Dynamics controlling quantity and system control ability.Therefore being necessary to calculate the Full Vehicle Dynamics controlling quantity can reach domain information.

(2) directly with system tracking error e _vxd, e _{Δ y}, e _{Δ ψ}for the input of Full Vehicle Dynamics controller, like this when tracking error is large, error rate is when too fast, calculates the Full Vehicle Dynamics controlling quantity obtained

also larger.Now, less if the Full Vehicle Dynamics controlling quantity can reach territory, the system control ability is limited, U ^cjust can not get carrying out fully, there will be equally the collision problem between Full Vehicle Dynamics controlling quantity and system control ability.Therefore be necessary system tracking error is processed, in the situation that allow to pass through e _vxd, e _{Δ y}, e _{Δ ψ}adjustment U that the Full Vehicle Dynamics controller is calculated ^cas much as possible little, and then strengthen the system stability allowance.

(3) there is no to consider real-time monitored and the utilization to system disturbance, this can cause, and for taking into account system, to control the Full Vehicle Dynamics controlling quantity that robustness generates too conservative, also likely surmount the constraint of bottom wheel control effort and can't effectively be carried out, and producing thus additional disturbance.Particularly, when system disturbance and additional disturbance surmount the working control ability of each wheel of bottom, system is controlled will unstability.

Above-mentioned deficiency make driverless operation AWID-AWIS vehicle on low adhesion value road surface, separate on road surface and travel, the dynamics Controlling effect while particularly running at high speed is undesirable, sometimes even can make vehicle generation unstability, the serious problems such as out of control.

Summary of the invention

The objective of the invention is for overcoming above-mentioned the deficiencies in the prior art, the preparation method of the Full Vehicle Dynamics controlling quantity of a kind of driverless operation individual drive-independent steering vehicle is provided, the method is on the basis that obtains vehicle-road track channel information, calculate the Full Vehicle Dynamics controlling quantity and can reach territory, following the tracks of the expectation deviation according to service system is adjusted, feasibility to the Full Vehicle Dynamics controlling quantity of final acquisition is judged, process, also estimate in real time simultaneously and utilized system disturbance information, thereby improve the validity of calculating the Full Vehicle Dynamics controlling quantity obtained, reasonableness and robust performance, make the driverless operation AWID-AWIS vehicle can be on low adhesion value road surface, separate on road surface with better precision, higher speed is followed the tracks of the larger road path of curvature, Study on Vehicle Dynamic Control is satisfactory for result, driving safety.

For achieving the above object, the present invention adopts following technical proposals:

A kind of driverless operation individual drive and turn to vehicle Full Vehicle Dynamics controlling quantity preparation method comprises the following steps:

1) estimate vehicle mass and rotor inertia, actual vehicle speed, lateral deviating distance and the yaw angle deviation data corresponding with the vehicle barycenter in collection vehicle-road track channel, and vehicle kinematics, the dynam essential information of for vehicle-road, following the tracks of, the combining information fusion method is obtained the required system status information data { X} of driverless operation AWID-AWIS whole vehicle dynamics Controlling;

2) according to step 1) the system status information data obtained, utilize Constrained geometric maps method to calculate the Full Vehicle Dynamics controlling quantity and can reach territory;

3) according to step 1) system status information data and the step 2 obtained) the Full Vehicle Dynamics controlling quantity obtained can reach the domain information data, and computing system is followed the tracks of the expectation deviation;

4) utilize driverless operation AWID-AWIS vehicle-road track channel kinetic model and step 3) the system keeps track expectation deviation that generates, integrating step 1) the system status information data of obtaining, the robust control method that employing is estimated in real time with disturbance generates the alternative controlling quantity of Full Vehicle Dynamics, and the alternative controlling quantity of this Full Vehicle Dynamics consists of the alternative controlling quantity of total longitudinal force, total alternative controlling quantity of side force, total alternative controlling quantity of yaw moment;

5) integrating step 2) the Full Vehicle Dynamics controlling quantity that obtains can reach territory, to step 4) feasibility of the alternative controlling quantity of Full Vehicle Dynamics that generates judged and adjusted, obtain the Full Vehicle Dynamics controlling quantity, i.e. total longitudinal force controlling quantity, total side force controlling quantity, total yaw moment controlling quantity.

Technical characterstic of the present invention and effect:

The present invention has increased the Full Vehicle Dynamics controlling quantity can reach the territory computing function, increased control constraint condition in calculating, proposed the Full Vehicle Dynamics controlling quantity and can reach angle bisection method of approach and the Constrained geometric maps method that calculate in territory, for the acquisition of Full Vehicle Dynamics controlling quantity provides constraint information;

Increased the function to driverless operation AWID-AWIS vehicle-road track channel tracking error is adjusted, implementation method is provided, can weaken or eliminate the conflict between Full Vehicle Dynamics controlling quantity and system working control ability, strengthen the stability margin of vehicle-road track channel;

Increased the function that the feasibility of the alternative controlling quantity of Full Vehicle Dynamics is judged and adjusts and obtain the Full Vehicle Dynamics controlling quantity, propose two-step method and calculated the Full Vehicle Dynamics controlling quantity: at first calculated the alternative controlling quantity of Full Vehicle Dynamics, then can reach the territory constraint information in conjunction with the Full Vehicle Dynamics controlling quantity is judged and is processed its feasibility, improved the particularity that the Full Vehicle Dynamics controlling quantity is calculated, can weaken or eliminate conflicting between the controlling quantity that calculate to obtain and system working control ability, the robustness of enhancing system control;

Increased system disturbance is carried out estimating in real time and the function of compensation, implementation method is provided, improved the reasonableness of whole vehicle dynamics Controlling amount, improved rapidity and the accuracy controlled;

Improved the robustness of validity, reasonableness and the Full Vehicle Dynamics control of Full Vehicle Dynamics controlling quantity, improved the road tracking performance of driverless operation AWID-AWIS vehicle on low adhesion value road surface, while separating road surface and high speed, dynamics Controlling is satisfactory for result, driving safety.

The accompanying drawing explanation

Fig. 1 is the FB(flow block) of driverless operation AWID-AWIS whole vehicle dynamics Controlling amount preparation method of the present invention;

Fig. 2 is the schematic diagram of asking the rectangle Approximate Sequence set in each wheel controlling quantity nonlinear restriction territory with the angle bisection method of approach of the present invention.

The specific embodiment

Below in conjunction with drawings and Examples, the present invention is further described.

Driverless operation AWID-AWIS whole vehicle dynamics Controlling preparation method of the present invention as shown in Figure 1, comprises the following steps:

1) estimate vehicle mass and rotor inertia, actual vehicle speed, lateral deviating distance and the yaw angle deviation data corresponding with the vehicle barycenter in collection vehicle-road track channel, and vehicle kinematics, the dynam essential information of for vehicle-road, following the tracks of, the combining information fusion method is obtained the required system status information data { X} of driverless operation AWID-AWIS whole vehicle dynamics Controlling; Concrete grammar is as follows:

1.1) described step 1) middle estimation vehicle mass and rotor inertia, be specially and utilize driverless operation AWID-AWIS vehicle nominal mass m _nwith nominal rotor inertia I _zn, obtain vehicle mass estimated valve m _est=m _n, rotor inertia estimated valve I _zest=I _zn;

1.2) described step 1) and in actual vehicle speed, lateral deviating distance and the yaw angle deviation data corresponding with the vehicle barycenter in collection vehicle-road track channel, be specially utilization " GIS (geographic information system)+DGPS (differencial global positioning system) ", or in-vehicle lane mark vision detection system, or road magnetic nail checking system, gather the current trace point P in track _clateral deviating distance Δ y (vehicle barycenter and P that (crossing vehicle barycenter edge perpendicular to the plane of vehicle y direction and the intersection point of track line of centers) located _cput the projection line length of line segment on road plane), and the vertical projecting line of the vehicle longitudinal axis on road plane is with the current trace point P in track _cyaw angle deviation delta ψ between place's track centerline tangent, acquisition method belongs to known technology;

1.3) described step 1) middle vehicle kinematics, the dynam essential information of following the tracks of for vehicle-road that gather, the combining information fusion method is obtained the required system status information data of driverless operation AWID-AWIS whole vehicle dynamics Controlling, be specially and utilize GIS+DGPS, or in-vehicle lane mark vision detection system, or road magnetic nail checking system, obtain the current trace point P in track _cthe road axis curvature ρ at place _pc, utilize wheel speed sensors, GPS (global positioning system), VG (vertical gyro) collection vehicle kinematics, dynam essential information, the combining information fusion method is obtained the required speed of a motor vehicle v of driverless operation AWID-AWIS whole vehicle dynamics Controlling _xwith system additivity information data { X} ₀(comprise longitudinal direction of car acceleration/accel, lateral acceleration, pitch angle, angle of roll, side slip angle and yaw rate data, and the current trace point P in track _cthe road axis curvature ρ at place _pc), gather, obtain v _x{ X} ₀method belong to known technology.System basic status information data { m _est, I _zest, v _x, Δ y, Δ ψ } and { X} ₀union construction system status information data { X}.

2) according to step 1) the system status information data obtained, utilize Constrained geometric maps method to calculate the Full Vehicle Dynamics controlling quantity and can reach territory, specifically comprise:

2.1) the Full Vehicle Dynamics controlling quantity can reach territory computation model expression formula and be:

$\left\{\begin{array}{c}v=\mathrm{Bu}=f(F_x,F_y,M_z)\\ u={\left[\begin{array}{ccccccc}{F}_{x1}& F_{y1}& F_{x2}& F_{y2}& ...& F_{\mathrm{xm}}& F_{\mathrm{ym}}\end{array}\right]}^T\end{array}\right.---\left(1\right)$

$F_{\mathrm{xj}}^2+F_{\mathrm{yj}}^2\≤F_{\max j}^2,j=\mathrm{1,2},...,m---\left(2\right)$

$F_{x\max j}^{-}\≤F_{\mathrm{xj}}\≤F_{x\max j}^{+},j=\mathrm{1,2},...,m---\left(3\right)$

$F_{y\max j}^{-}\≤F_{\mathrm{yj}}\≤F_{y\max j}^{+},j=\mathrm{1,2},...,m---\left(4\right)$

The implication of described expression formula (1)～(4) is known u and B, asks v, in formula, v is that the Full Vehicle Dynamics controlling quantity can reach territory, be one by total longitudinal force controlling quantity F _x, total side force controlling quantity F _y, total yaw moment controlling quantity M _zthe 3 dimension limited function area of space that form, efficiency matrix B is according to step 1) { X}, wheel steering angle, vehicle chassis geometric parameter determine that (method of determining belongs to known method for the system status information data obtained, referring to document: Li Daofei, explain all. the integrated control of the vehicle dynamics based on optimum tire force distribution [J]. Shanghai Communications University's journal, 2008,42 (6): 887-891.), the wheel controlling quantity that u is the 2m dimension, consist of m wheel longitudinal force and m side force,

be lower bound, the upper bound of permission braking force or the propulsive effort of j wheel, j=1,2 ..., m, m is more than or equal to 3 positive integer,

be lower bound, the upper bound of the permission side force of j wheel, F _maxjbe the total power of permission tire force of j wheel, F _xj, F _yjbe j wheel longitudinal force controlling quantity, side force controlling quantity

value and the ability of drg, actuator, steering swivel system and allow the total power F of tire force _maxjit is information-related, and F _maxjall can use known method to obtain (referring to document Eiichi Ono, et al.Estimation of tire grip margin using electric power steering system[J] .Vehicle System Dynamics, 2004, vol.41, sup:421-430. (little wild English first-class. " using the electronic power assist steering system estimation tire adhesion force limit " [J]. " Vehicle System Dynamics " magazine, 2004, vol.41, sup:421-430.) and document: Yasui Yoshiyuki, et al.Estimation of lateral grip margin based on self-al igning torque for vehicle dynamics enhancement[J] .SAE Paper, No.2004-01-1070. (peace well benefaction etc. " tyre side based on self-aligning torque in Study on Vehicle Dynamic Control is estimated to limit of adhesion " [J], the SAE paper, No.2004-01-1070.))

2.2) ask the common factor of Linear Constraints formula (3)～(4) of each wheel

be j wheel controlling quantity linear restriction territory, and the common factor of Nonlinear Constraints formula (2)～(4) of each wheel

be j wheel controlling quantity nonlinear restriction territory, j=1,2 ..., m, m is more than or equal to 3 positive integer;

2.2.1) calculate the Full Vehicle Dynamics controlling quantity and can reach territory v: if

directly with

for constraint condition is calculated v, (method of calculating belongs to known method, see document: Durham, W.C., Constrained Control Allocation:Three Moment Problem.Journal of Guidance, Control, and Dynamics, 1994,17 (2): 330-336. (Du Hamu W.C. " three moment problems in the Control with constraints distribution ", " guidance, control and dynam " magazine, 1994,17 (2): 330-336)), if

at first use the angle bisection method of approach to ask each wheel controlling quantity nonlinear restriction territory

the set of rectangle Approximate Sequence

wherein

be j wheel controlling quantity nonlinear restriction territory

s approach the upper and lower boundary of the longitudinal force of rectangle,

for the upper and lower boundary of its side force, s=1,2 ..., p ₀, p ₀according to design accuracy, require to determine, j=1, 2, m, m is more than or equal to 3 positive integer, the Full Vehicle Dynamics controlling quantity can reach the territory computation model and is expressed as formula (1) and formula (5)～(6), and then use known method (to see document: Durham, W.C., Constrained Control Allocation:Three Moment Problem.Journal of Guidance, Control, and Dynamics, 1994, 17 (2): 330-336. (Du Hamu W.C. " three moment problems in the Control with constraints distribution ", " guidance, control and dynam " magazine, 1994, 17 (2): 330-336)) calculate each

corresponding controlling quantity can reach territory subdomain v ^s, s=1,2 ..., p ₀, get all v ^sunion can reach territory v as the Full Vehicle Dynamics controlling quantity, v=∪ (v ^s),

$F_{x\max j}^{-}{}_s\≤F_{\mathrm{xj}}\≤F_{x\max j}^{+}{}_s,s=\mathrm{1,2},...p_0,j=\mathrm{1,2},...m---\left(5\right)$

$F_{y\max j}^{-}{}_s\≤F_{\mathrm{yj}}\≤F_{y\max j}^{+}{}_s,s=\mathrm{1,2},....p_0,j=\mathrm{1,2},...m---\left(6\right)$

The rectangle Approximate Sequence collection approach that the present invention asks each wheel controlling quantity nonlinear restriction territory with the angle bisection method of approach as shown in Figure 2; In Fig. 2,

the sector region of hatching mark is j wheel controlling quantity nonlinear restriction territory

s=1,2 ... p ₀, j=1,2 ..., m, wherein

mean to approach for the first time

the rectangular domain obtained,

mean to approach for the second time

the rectangular domain obtained, mean to approach for the third time

the rectangular domain obtained ..., segmentation successively, until approximation accuracy meets the demands (in said method, approach all at every turn the residue sector region is done to 45 ° of isogonisms divisions, then get and approach rectangle, be called the angle bisection method of approach that calculate in wheel controlling quantity nonlinear restriction territory);

Step 2.1), the method for 2.2), 2.2.1) describing is called Constrained geometric maps method.

2.2.1.1) step 2.2.1) middle p ₀according to design accuracy, require to determine, being specially s area that approaches rectangle of note is Ss, and note allows approximate error ε=0.05, calculates as follows p ₀:

The first step: p ₀initialize 1, i.e. p ₀=1, calculate the nonlinear restriction territory

area, be designated as S;

Second step: calculate p ₀the individual area Sp that approaches rectangle ₀;

The 3rd step: calculate from the 1st to p ₀individual area sum of approaching rectangle

judgement

whether set up, if set up p ₀value is calculated and is finished; If be false, carry out the 4th step;

The 4th step: p ₀add 1, turn second step.

3) according to step 1) system status information data and the step 2 obtained) the Full Vehicle Dynamics controlling quantity obtained can reach the domain information data, and computing system is followed the tracks of the expectation deviation; Concrete grammar is as follows:

3.1) set the initial value that Full Vehicle Dynamics is controlled the target expectation value: desired speed desired distance deviation delta y _d=0, expectation yaw angle deviation delta ψ _d=0, calculate itself and step 1) v that obtains _x, the expectation of the system keeps track between Δ y, Δ ψ deviation initial value:

according to the current trace point P in track _cthe road axis curvature ρ at place _pc, the maximum lateral acceleration constraint of vehicle a _ymaxdetermine, suc as formula (7):

$0<v_{\mathrm{xd}}^0\&le;\sqrt{\left|\frac{a_{y\max }}{{\mathrm{\&rho;}}_{\mathrm{Pc}}}\right|}---\left(7\right)$

3.2) according to step 2) the Full Vehicle Dynamics controlling quantity obtained can reach territory v, utilize one group of Expert Rules (rule 1, rule 2 ..., regular n, n is more than or equal to 3 positive integer) to step 3.1) obtain with

adjusted, be exemplified below:

Rule 1: if v is larger, and

with

absolute value all less, without right with

adjusted system keeps track expectation deviation

Rule 2: if v is less, and

with

absolute value be all median size, use formula (8)～(10) right

with adjust, obtain system keeps track expectation deviation e _vxd, e _{Δ y}and e _{Δ ψ}:

$e_{\mathrm{vxd}}=(1-\frac{T_s}{T_{\mathrm{vxd}}^2})e_{\mathrm{vxd}}^0---\left(8\right)$

$e_{\mathrm{\&Delta;y}}=(1-\frac{T_s}{T_{\mathrm{\&Delta;y}}^2})e_{\mathrm{\&Delta;y}}^0---\left(9\right)$

$e_{\mathrm{\&Delta;\&psi;}}=(1-\frac{T_s}{T_{\mathrm{\&Delta;\&psi;}}^2})e_{\mathrm{\&Delta;\&psi;}}^0---\left(10\right)$

T _sfor vehicle-road track channel control cycle; ²t _vxd, ²t _{Δ y}, ²t _{Δ ψ}for time constant, according to expertise, determine, get and make T _s2.5 times,

Rule n: if v is less, and with

absolute value all larger, use formula (11)～(13) right with

adjusted, obtained system keeps track expectation deviation e _vxd, e _{Δ y}and e _{Δ ψ}:

$e_{\mathrm{vxd}}=(1-\frac{T_s}{T_{\mathrm{vxd}}^n})e_{\mathrm{vxd}}^0---\left(11\right)$

$e_{\mathrm{\&Delta;y}}=(1-\frac{T_s}{T_{\mathrm{\&Delta;y}}^n})e_{\mathrm{\&Delta;y}}^0---\left(12\right)$

$e_{\mathrm{\&Delta;\&psi;}}=(1-\frac{T_s}{T_{\mathrm{\&Delta;\&psi;}}^n})e_{\mathrm{\&Delta;\&psi;}}^0---\left(13\right)$

ⁿt _vxd, ⁿt _{Δ y}, ⁿt _{Δ ψ}for time constant, according to expertise, determine, get and make T _s5.0 times.

3.2.1) step 3.2) and in " less ", " median size ", " larger " be the fuzzy membership value, utilize the fuzzy logic method based on expertise to determine, positive integer n according to v,

with

the division of four fuzzy subdomains of variable and the concrete fuzzy reasoning method adopted are definite, and above-mentioned fuzzy membership value and the fuzzy logic method based on expertise are the known technology in fuzzy logic control technology field; Design and the said method of rule 3～regular n-1 are similar.

4) utilize driverless operation AWID-AWIS vehicle-road track channel kinetic model and step 3) the system keeps track expectation deviation that generates, integrating step 1) the system status information data of obtaining, the robust control method that employing is estimated in real time with disturbance generates the alternative controlling quantity of Full Vehicle Dynamics, and the alternative controlling quantity of this Full Vehicle Dynamics consists of the alternative controlling quantity of total longitudinal force, total alternative controlling quantity of side force, total alternative controlling quantity of yaw moment; Specifically comprise:

4.1) entirely take turns individual drive-independent steering whole vehicle kinetic model expression formula and be:

${\stackrel{\&CenterDot;}{v}}_x=f_{\mathrm{vx}}\left(t\right)+\frac{1}{m_{\mathrm{est}}}{F}_x---\left(14\right)$

$\mathrm{\&Delta;}{\stackrel{\&CenterDot;\&CenterDot;}{y}}_{\mathrm{Pc}}=f_{\mathrm{\&Delta;y}}\left(t\right)-\frac{1}{m_{\mathrm{est}}}{F}_y---\left(15\right)$

$\mathrm{\&Delta;}{\stackrel{\&CenterDot;\&CenterDot;\&CenterDot;}{\mathrm{\&psi;}}}_{\mathrm{Pc}}=f_{\mathrm{\&Delta;\&psi;}}\left(t\right)-\frac{1}{I_{\mathrm{zest}}}{M}_z---\left(16\right)$

In formula

be respectively v _x, Δ y, Δ ψ single order and second derivative; m _estfor vehicle mass estimated valve, I _zestfor the rotor inertia estimated valve; F _xfor total longitudinal force controlling quantity, F _yfor total side force controlling quantity, M _zfor total yaw moment controlling quantity; f _vx, f _{Δ y}and f _{Δ ψ}(" inside disturbing ", " disturbing outward ", " inside disturb+disturb outward ", " summation " are the known concept in this known robust control technique of Active Disturbance Rejection Control (ADRC) to be respectively " summation " that driverless operation AWID-AWIS vehicle-track channel is vertical, horizontal and 3 dynam passages of weaving " are inside disturbed+disturbed " outward, see document: Han Jingqing. the control technology [M] of Auto Disturbances Rejection Control Technique-estimation compensation uncertain factor. Beijing: National Defense Industry Press, 2009.);

4.2) use the ADRC robust controller of band " inside disturbing " and " disturbing " assessment function to calculate the alternative controlling quantity of Full Vehicle Dynamics outward:

4.2.1) the Second-Order Discrete extended state observer shown in employing formula (17) is to f _vxestimate in real time, three rank Discrete Extended State Observers shown in employing formula (18) are to f _{Δ y}and f _{Δ ψ}estimate in real time respectively;

$\left\{\begin{array}{c}e=z_1\left(k\right)-y\left(k\right)\\ z_1(k+1)=z_1\left(k\right)+h(z_2\left(k\right)\\ -{\mathrm{\&beta;}}_{01}\mathrm{fal}(e,{\mathrm{\&alpha;}}_1,{\mathrm{\&delta;}}_0)+b_{0}u\left(k)\right)\\ z_2(k+2)=z_2\left(k\right)-h{\mathrm{\&beta;}}_{02}\mathrm{fal}(e,{\mathrm{\&alpha;}}_2,{\mathrm{\&delta;}}_0)\end{array}\right.---\left(17\right)$

$\left\{\begin{array}{c}e=z_1\left(k\right)-y\left(k\right)\\ z_1(k+1)=z_1\left(k\right)+h(z_2\left(k\right)-{\mathrm{\&beta;}}_{01}e)\\ z_2(k+1)=z_2\left(k\right)+h\left(z_3\left(k\right)\right)\\ -{\mathrm{\&beta;}}_{02}\mathrm{fal}(e,{\mathrm{\&alpha;}}_1,{\mathrm{\&delta;}}_0)+b_{0}u\left(k\right)\\ z_3(k+1)=z_3\left(k\right)-h{\mathrm{\&beta;}}_{03}\mathrm{fal}(e,{\mathrm{\&alpha;}}_2,{\mathrm{\&delta;}}_0)\end{array}\right.---\left(18\right)$

In formula (17) and formula (18), k represents current control step, and h is control cycle; Y (k) represents v _x, Δ y or Δ ψ k pacing value; z ₁(k) represent v _x, Δ y or Δ ψ k step estimated valve; E is v _x, Δ y or Δ ψ k pacing value y (k) and estimated valve z ₁(k) deviation between; β ₀₁, β ₀₂, β ₀₃, α ₁, α ₂, β, δ ₀for controller parameter; Fal (e, α ₁, δ ₀), fal (e, α ₂, δ ₀) by expression formula (19-1), (19-2), expressed respectively, sign (e) means the symbolic function of e; In formula (17), z ₂(k) represent f _vxestimated valve, b ₀=1/m _est, u (k)=F _xC(k), k walks the alternative controlling quantity F of total longitudinal force _xC(k); In formula (18), z ₂(k) represent the estimated valve of Δ y or Δ ψ first derivative, z ₃(k) represent f _{Δ y}or f _{Δ ψ}estimated valve, b ₀=-1/m _est(corresponding f _{Δ y}estimate), or b ₀=-1/I _zest(corresponding f _{Δ ψ}estimate), u (k)=F _yCor u (k)=M (k) _zC(k), k walks the alternative controlling quantity F of total side force _yCor total alternative controlling quantity M of yaw moment (k) _zC(k); Controller parameter β ₀₁, β ₀₂, β ₀₃, α ₁, α ₂, β, δ ₀be designed to known method (see document: Han Jingqing. the control technology [M] of Auto Disturbances Rejection Control Technique-estimation compensation uncertain factor. Beijing: National Defense Industry Press, 2009.);

$\mathrm{fal}(e,{\mathrm{\&alpha;}}_1,{\mathrm{\&delta;}}_0)=\left\{\begin{array}{cc}\frac{e}{{{\mathrm{\&delta;}}_0}^{{\mathrm{\&alpha;}}_1-1}}& \left|e\right|\&le;{\mathrm{\&delta;}}_0\\ {\left|e\right|}^{{\mathrm{\&alpha;}}_1}\mathrm{sign}\left(e\right),& \left|e\right|>{\mathrm{\&delta;}}_0\end{array}\right.---(19-1)$

$\mathrm{fal}(e,{\mathrm{\&alpha;}}_2,{\mathrm{\&delta;}}_0)=\left\{\begin{array}{cc}\frac{e}{{{\mathrm{\&delta;}}_0}^{{\mathrm{\&alpha;}}_2-1}}& \left|e\right|\&le;{\mathrm{\&delta;}}_0\\ {\left|e\right|}^{{\mathrm{\&alpha;}}_2}\mathrm{sign}\left(e\right),& \left|e\right|>{\mathrm{\&delta;}}_0\end{array}\right.---(19-2)$

4.2.2) calculating the alternative controlling quantity of Full Vehicle Dynamics: the single order Discrete Nonlinear proportional regulator shown in employing formula (20) is to f _vxcarry out real-Time Compensation, the Second-Order Discrete non-linear ratio controller shown in employing formula (21) is to f _{Δ y}and f _{Δ ψ}carry out respectively real-Time Compensation, each channel error is carried out to feedback compensation;

$\left\{\begin{array}{c}{u}_0=K_p\mathrm{fal}({\mathrm{<figure-callout\; id="1"\; label="e"\; filenames="HDA0000049262040000012.png"\; state="\{\{state\}\}">e</figure-callout>}}_1,{\mathrm{\&alpha;}}_p,{\mathrm{\&delta;}}_p)\\ u\left(k\right)=u_0-z_2\left(k\right)/b_0\end{array}---\left(20\right)\right.$

$\left\{\begin{array}{c}{u}_0=K_p\mathrm{fal}({\mathrm{<figure-callout\; id="1"\; label="e"\; filenames="HDA0000049262040000012.png"\; state="\{\{state\}\}">e</figure-callout>}}_1,{\mathrm{\&alpha;}}_p,{\mathrm{\&delta;}}_p)+K_d\mathrm{fal}(e_2,{\mathrm{\&alpha;}}_d,{\mathrm{\&delta;}}_d)\\ u\left(k\right)=u_0-z_3\left(k\right)/b_0\end{array}\right.---\left(21\right)$

In formula (20) and formula (21), fal (e ₁, α _p, δ _p), fal (e ₂, α _d, δ _d) by formula (22-1), formula (22-2), expressed respectively; K _p, K _d, α _p, δ _p, α _d, δ _dfor controller parameter, u ₀for intermediate variable; In formula (20), e ₁e _vxdtracking signal, b ₀, u (k), z ₂(k) meaning cotype (17); In formula (21), e ₁e _{Δ y}or e _{Δ ψ}tracking signal, e ₂e _{Δ y}or e _{Δ ψ}the tracking signal differential, b ₀, u (k), z ₂(k) meaning cotype (18); The alternative controlling quantity of driverless operation AWID-AWIS whole vehicle dynam is 3 n dimensional vector ns, is designated as U _c, U _c=[F _xCf _yCm _zC] ^t, k step value t is the transposition symbol; Controller parameter K _p, K _d, α _p, δ _p, α _d, δ _dbe designed to known method (see document: Han Jingqing. the control technology [M] of Auto Disturbances Rejection Control Technique-estimation compensation uncertain factor. Beijing: National Defense Industry Press, 2009.); e ₁, e ₂use Nonlinear Tracking Differentiator (TD) algorithm of discrete form to calculate, also for known method (see document: Han Jingqing. the control technology [M] of Auto Disturbances Rejection Control Technique-estimation compensation uncertain factor. Beijing: National Defense Industry Press, 2009, pp66～73.)

$\mathrm{fal}({\mathrm{<figure-callout\; id="1"\; label="e"\; filenames="HDA0000049262040000012.png"\; state="\{\{state\}\}">e</figure-callout>}}_1,{\mathrm{\&alpha;}}_P,{\mathrm{\&delta;}}_P)=\left\{\begin{array}{cc}\frac{{\mathrm{<figure-callout\; id="1"\; label="e"\; filenames="HDA0000049262040000012.png"\; state="\{\{state\}\}">e</figure-callout>}}_1}{{{\mathrm{\&delta;}}_P}^{{\mathrm{\&alpha;}}_P-1}}& \left|{\mathrm{<figure-callout\; id="1"\; label="e"\; filenames="HDA0000049262040000012.png"\; state="\{\{state\}\}">e</figure-callout>}}_1\right|\&le;{\mathrm{\&delta;}}_P\\ {\left|e_1\right|}^{{\mathrm{\&alpha;}}_P}\mathrm{sign}\left(e_1\right),& \left|{\mathrm{<figure-callout\; id="1"\; label="e"\; filenames="HDA0000049262040000012.png"\; state="\{\{state\}\}">e</figure-callout>}}_1\right|>{\mathrm{\&delta;}}_P\end{array}\right.---(22-1)$

$\mathrm{fal}(e_2,{\mathrm{\&alpha;}}_d,{\mathrm{\&delta;}}_d)=\left\{\begin{array}{cc}\frac{e_2}{{{\mathrm{\&delta;}}_d}^{{\mathrm{\&alpha;}}_d-1}}& \left|e_2\right|\&le;{\mathrm{\&delta;}}_d\\ {\left|e_2\right|}^{{\mathrm{\&alpha;}}_d}\mathrm{sign}\left(e_2\right),& \left|e_2\right|>{\mathrm{\&delta;}}_d\end{array}\right.---(22-2)$

Step 4.1), the method for 4.2), 4.2.1), 4.2.2) describing is called the robust control method of estimating in real time with disturbance that the alternative controlling quantity of driverless operation AWID-AWIS vehicle-road track channel Full Vehicle Dynamics is calculated.

5) integrating step 2) the Full Vehicle Dynamics controlling quantity that obtains can reach territory, to step 4) feasibility of the alternative controlling quantity of Full Vehicle Dynamics that generates judged and adjusted, obtain the Full Vehicle Dynamics controlling quantity, be total longitudinal force controlling quantity, total side force controlling quantity, total yaw moment controlling quantity, specifically comprise:

5.1) note F _x(k), F _y(k), M _z(k) be respectively total longitudinal force controlling quantity F _x, total side force controlling quantity F _y, total yaw moment controlling quantity M _zk step value, the Full Vehicle Dynamics controlling quantity is U, U=[F _xf _ym _z] ^t, its k step value U (k)=[F _x(k) F _y(k) M _z(k)] ^t, read step 2.2.1) and the Full Vehicle Dynamics controlling quantity that obtains can reach territory v and step 4.2.2) the alternative controlling quantity U of Full Vehicle Dynamics that obtains _c(k)=[F _xC(k) F _yC(k) M _zC(k)] ^t;

5.2) if U _c(k) ∈ v, k step Full Vehicle Dynamics controlling quantity be U (k)=[F _xC(k) F _yC(k) M _zC(k)] ^t;

If

to the alternative controlling quantity U of k step Full Vehicle Dynamics _c(k) processed, obtained Full Vehicle Dynamics controlling quantity U (k), specifically comprised:

5.2.1) definition optimization aim function

$d\left(k\right)={\left|\right|U_C\left(k\right)-{\mathrm{Bu}}_C\left(k\right)\left|\right|}_2$

$=\sqrt{{(F_{\mathrm{xC}}\left(k\right)-B(1,:)u_C\left(k\right))}^2+{(F_{\mathrm{yC}}\left(k\right)-B(2,:)u_C\left(k\right))}^2+{(M_{\mathrm{zC}}\left(k\right)-B(3,:)u_C\left(k\right))}^2}---\left(23\right)$

B (1 :), B (2 :), B (3 :) mean respectively the first row, the second row, the capable vector of the third line of efficiency matrix B, set up Non-linear Optimal Model

min d(k)＝||U _C(k)-Bu _C(k)|| ² (24)

$s.t.F_{\mathrm{Cxj}}^2+F_{\mathrm{Cyi}}^2\&le;F_{\max j}^2,j=\mathrm{1,2},...,m---\left(25\right)$

$F_{x\max j}^{-}\&le;F_{\mathrm{Cxj}}\&le;F_{x\max j}^{+},j=\mathrm{1,2},...,m---\left(26\right)$

$F_{y\max j}^{-}\&le;F_{\mathrm{Cyj}}\&le;F_{y\max j}^{+},j=\mathrm{1,2},...,m---\left(27\right)$

The implication of described expression formula (24)～(27) is the alternative controlling quantity U of known Full Vehicle Dynamics _c(k) and efficiency matrix B,, under the constraint of expression formula (25)～(27), ask the u that makes d (k) minimum _c(k); u _c(k) the alternative control vector of vehicle wheel forces of tieing up for 2m, u _c(k)=[F _cx1f _cy1f _cx2f _cy2f _cxmf _cym] ^t, F _cxj, F _cyjbe j the alternative controlling quantity of wheel longitudinal force, the alternative controlling quantity of side force, j=1,2 ..., m, m is more than or equal to 3 positive integer;

be lower bound, the upper bound of permission braking force or the propulsive effort of j wheel;

be lower bound, the upper bound of the permission side force of j wheel; F _maxjbe the total power of permission tire force of j wheel; Efficiency matrix B is according to step 1) { X}, wheel steering angle, vehicle chassis geometric parameter are determined for the system status information data obtained;

5.2.2) the fmincon () function that uses MATLAB V7.6.0 version software to provide is to step 5.2.1) and in the nonlinear optimal problem described of expression formula (24)～(27) solved, result is designated as

the method is known technology; Will

substitution formula (28) is calculated, and result is the Full Vehicle Dynamics controlling quantity U (k) after adjustment,

$U\left(k\right)={\mathrm{Bu}}_C^O\left(k\right)---\left(28\right).$

Claims (6)

1. a driverless operation individual drive and turn to vehicle Full Vehicle Dynamics controlling quantity preparation method, is characterized in that, comprises the following steps:

1) estimate vehicle mass and rotor inertia, actual vehicle speed, lateral deviating distance and the yaw angle deviation data corresponding with the vehicle barycenter in collection vehicle-road track channel, and vehicle kinematics, the dynam essential information of for vehicle-road, following the tracks of, the combining information fusion method is obtained driverless operation and is entirely taken turns the required system status information data { X} of individual drive-independent steering whole vehicle dynamics Controlling;

2) the system status information data of obtaining according to step 1), utilize Constrained geometric maps method to calculate the Full Vehicle Dynamics controlling quantity and can reach territory;

3) system status information data and the step 2 according to step 1), obtained) the Full Vehicle Dynamics controlling quantity obtained can reach the domain information data, and computing system is followed the tracks of the expectation deviation;

4) utilize driverless operation entirely to take turns the system keeps track expectation deviation of individual drive-independent steering vehicle-road track channel kinetic model and step 3) generation, integrating step 1) the system status information data of obtaining, the robust control method that employing is estimated in real time with disturbance generates the alternative controlling quantity of Full Vehicle Dynamics, and the alternative controlling quantity of this Full Vehicle Dynamics consists of the alternative controlling quantity of total longitudinal force, total alternative controlling quantity of side force, total alternative controlling quantity of yaw moment;

5) integrating step 2) the Full Vehicle Dynamics controlling quantity that obtains can reach territory, the feasibility of the alternative controlling quantity of Full Vehicle Dynamics that step 4) is generated is judged and is adjusted, obtain the Full Vehicle Dynamics controlling quantity, i.e. total longitudinal force controlling quantity, total side force controlling quantity, total yaw moment controlling quantity.

2. driverless operation individual drive according to claim 1 and turn to vehicle Full Vehicle Dynamics controlling quantity preparation method is characterized in that:

1.1) estimate vehicle mass and rotor inertia in described step 1), be specially and utilize driverless operation entirely to take turns individual drive-independent steering vehicle nominal mass m _nwith nominal rotor inertia I _zn, obtain vehicle mass estimated valve m _est=m _n, rotor inertia estimated valve I _zest=I _zn;

1.2) actual vehicle speed, lateral deviating distance and the yaw angle deviation data corresponding with the vehicle barycenter in collection vehicle-road track channel in described step 1), be specially and utilize GIS+DGPS, or in-vehicle lane mark vision detection system, or road magnetic nail checking system, gather the current trace point P in track _cthe lateral deviating distance at place, and the vertical projecting line of the vehicle longitudinal axis on road plane is with the current trace point P in track _cyaw angle deviation delta ψ between place's track centerline tangent; Wherein, P _cfor crossing vehicle barycenter edge perpendicular to the plane of vehicle y direction and the intersection point of track line of centers, Δ y is vehicle barycenter and P _cthe projection line length of some line segment on road plane;

1.3) gather vehicle kinematics, the dynam essential information of following the tracks of for vehicle-road in described step 1), the combining information fusion method is obtained driverless operation and is entirely taken turns the required system status information data of individual drive-independent steering whole vehicle dynamics Controlling, be specially and utilize GIS+DGPS, or in-vehicle lane mark vision detection system, or road magnetic nail checking system, obtain the current trace point P in track _cthe road axis curvature ρ at place _pC, utilize wheel speed sensors, GPS, vertical gyro collection vehicle kinematics, dynam essential information, the combining information fusion method is obtained driverless operation and is entirely taken turns individual drive-required speed of a motor vehicle v of independent steering whole vehicle dynamics Controlling _xwith system additivity information data { X} ₀, described system additivity information data { X} ₀comprise longitudinal direction of car acceleration/accel, lateral acceleration, pitch angle, angle of roll, side slip angle and yaw rate data, and the current trace point P in track _cthe road axis curvature ρ at place _pC;

1.4) in described step 1) the system status information data { X} is by system basic status information data { m _est, I _zest, v _x, Δ y, Δ ψ } and system additivity information data { X} ₀union form.

3. driverless operation individual drive according to claim 2 and turn to vehicle Full Vehicle Dynamics controlling quantity preparation method, it is characterized in that: the system status information data of obtaining according to step 1) described step 2), utilize Constrained geometric maps method to calculate the Full Vehicle Dynamics controlling quantity and can reach territory, specifically comprise:

2.1) the Full Vehicle Dynamics controlling quantity can reach territory computation model expression formula and be:

The implication of described expression formula (1)～(4) is known u and B, asks v; In formula, v is that the Full Vehicle Dynamics controlling quantity can reach territory, be one by total longitudinal force controlling quantity F _x, total side force controlling quantity F _y, total yaw moment controlling quantity M _zthe three-dimensional limited function area of space formed; The system status information data that efficiency matrix B obtains according to step 1) { determine by X}, wheel steering angle, vehicle chassis geometric parameter; The wheel controlling quantity that u is the 2m dimension, consist of m wheel longitudinal force and m side force;

be lower bound, the upper bound of permission braking force or the propulsive effort of j wheel, j=1,2 ..., m, m is more than or equal to 3 positive integer;

be lower bound, the upper bound of the permission side force of j wheel; F _maxjbe the total power of permission tire force of j wheel; F _xj, F _yjbe j wheel longitudinal force controlling quantity, side force controlling quantity;

2.2) ask the common factor of Linear Constraints formula (3)～(4) of each wheel be j wheel controlling quantity linear restriction territory, and the common factor of Nonlinear Constraints formula (2)～(4) of each wheel

be j wheel controlling quantity nonlinear restriction territory, j=1,2 ..., m, m is more than or equal to 3 positive integer;

2.2.1) calculate the Full Vehicle Dynamics controlling quantity and can reach territory v: if

directly with for constraint condition is calculated v; If

at first use the angle bisection method of approach to ask each wheel controlling quantity nonlinear restriction territory

the set of rectangle Approximate Sequence

wherein

be j wheel controlling quantity nonlinear restriction territory s approach the upper and lower boundary of the longitudinal force of rectangle,

for the upper and lower boundary of its side force, s=1,2 ..., p ₀, p ₀according to design accuracy, require to determine, j=1,2 ..., m, m is more than or equal to 3 positive integer, and the Full Vehicle Dynamics controlling quantity can reach the territory computation model and is expressed as formula (1) and formula (5)～(6), and then calculates each

corresponding controlling quantity can reach territory subdomain v ^s, s=1,2 ..., p ₀, get all v ^sunion can reach territory v as the Full Vehicle Dynamics controlling quantity,

Step 2.1), the method for 2.2), 2.2.1) describing is called Constrained geometric maps method;

2.2.1.1) step 2.2.1) middle p ₀according to design accuracy, require to determine, being specially s area that approaches rectangle of note is Ss, and note allows approximate error ε=0.05, calculates as follows p ₀:

The first step: p ₀initialize 1, i.e. p ₀=1, calculate the nonlinear restriction territory

area, be designated as S;

Second step: calculate p ₀the individual area Sp that approaches rectangle ₀;

The 3rd step: calculate from the 1st to p ₀individual area sum of approaching rectangle judgement

whether set up, if set up p ₀value is calculated and is finished; If be false, carry out the 4th step;

The 4th step: p ₀add 1, turn second step.

4. driverless operation individual drive according to claim 3 and turn to vehicle Full Vehicle Dynamics controlling quantity preparation method, it is characterized in that: system status information data and the step 2 described step 3), according to step 1), obtained) the Full Vehicle Dynamics controlling quantity obtained can reach domain information, and it is as follows that computing system is followed the tracks of expectation deviation concrete grammar:

3.1) set the initial value that Full Vehicle Dynamics is controlled the target expectation value: desired speed

desired distance deviation delta y _d=0, expectation yaw angle deviation delta ψ _d=0, calculate the v that itself and step 1) are obtained _x, the expectation of the system keeps track between Δ y, Δ ψ deviation initial value:

according to the current trace point P in track _cthe road axis curvature at place

, the maximum lateral acceleration constraint of vehicle a _ymaxdetermine, suc as formula (7):

3.2) according to step 2) the Full Vehicle Dynamics controlling quantity obtained can reach territory v, utilize one group of Expert Rules rule 1, rule 2 ..., regular n, n is more than or equal to 3 positive integer, to step 3.1) obtain

with

adjusted,

Rule 1: if v is larger, and

with

absolute value all less, without right

with

adjusted system keeps track expectation deviation

Rule 2: if v is less, and

with

absolute value be all median size, use formula (8)～(10) right

with

adjusted, obtained system keeps track expectation deviation e _vxd, e _{Δ y}and e _{Δ ψ}:

T _sfor vehicle-road track channel control cycle;

for time constant, according to expertise, determine, get and make T _s2.5 times;

┇

Rule n: if v is less, and

with

absolute value all larger, use formula (11)～(13) right

with

adjusted, obtained system keeps track expectation deviation e _vxd, e _{Δ y}and e _{Δ ψ}:

for time constant, according to expertise, determine, get and make T _s5.0 times;

3.2.1) step 3.2) and in " less ", " median size ", " larger " be the fuzzy membership value, utilize the fuzzy logic method based on expertise to determine, positive integer n according to v,

with

the division of four fuzzy subdomains of variable and the concrete fuzzy reasoning method adopted are determined; Design and the said method of rule 3～regular n-1 are similar.

5. driverless operation individual drive according to claim 4 and turn to vehicle Full Vehicle Dynamics controlling quantity preparation method, it is characterized in that: utilize driverless operation entirely to take turns individual drive-independent steering vehicle-road track channel kinetic model and step 1) described step 4) the system status information data of obtaining, the system keeps track expectation deviation that step 3) generates, the robust control method that employing is estimated in real time with disturbance generates the alternative controlling quantity of Full Vehicle Dynamics, specifically comprises:

4.1) entirely take turns individual drive-independent steering whole vehicle kinetic model expression formula and be:

In formula

be respectively v _x, Δ y, Δ ψ single order and second derivative; m _estfor vehicle mass estimated valve, I _zestfor the rotor inertia estimated valve; F _xfor total longitudinal force controlling quantity, F _yfor total side force controlling quantity, M _zfor total yaw moment controlling quantity; f _vx, f _{Δ y}and f _{Δ ψ}be respectively driverless operation and entirely take turns " summation " that individual drive-independent steering vehicle-track channel is vertical, horizontal and three dynam passages of weaving " are inside disturbed+disturbed " outward;

4.2) use the ADRC robust controller of band " inside disturbing " and " disturbing " assessment function to calculate the alternative controlling quantity of Full Vehicle Dynamics outward:

4.2.1) the Second-Order Discrete extended state observer shown in employing formula (17) is to f _vxestimate in real time, three rank Discrete Extended State Observers shown in employing formula (18) are to f _{Δ y}and f _{Δ ψ}estimate in real time respectively;

In formula (17) and formula (18), k represents current control step, and h is control cycle; Y (k) represents v _x, Δ y or Δ ψ k pacing value; z ₁(k) represent v _x, Δ y or Δ ψ k step estimated valve; E is v _x, Δ y or Δ ψ k pacing value y (k) and estimated valve z ₁(k) deviation between; β ₀₁, β ₀₂, β ₀₃, α ₁, α ₂, δ ₀for controller parameter; Fal (e, α ₁, δ ₀), fal (e, α ₂, δ ₀) by expression formula (19-1), (19-2), expressed respectively, sign (e) means the symbolic function of e; In formula (17), z ₂(k) represent f _vxestimated valve, b ₀=1/m _est, u (k)=F _xC(k), k walks the alternative controlling quantity F of total longitudinal force _xC(k); In formula (18), z ₂(k) represent the estimated valve of Δ y or Δ ψ first derivative, z ₃(k) represent f _{Δ y}or f _{Δ ψ}estimated valve, b ₀=-1/m _est, corresponding f _{Δ y}estimate, or b ₀=-1/I _zest, corresponding f _{Δ ψ}estimate u (k)=F _yCor u (k)=M (k) _zC(k), k walks the alternative controlling quantity F of total side force _yCor total alternative controlling quantity M of yaw moment (k) _zC(k);

4.2.2) calculating the alternative controlling quantity of Full Vehicle Dynamics: the single order Discrete Nonlinear proportional regulator shown in employing formula (20) is to f _vxcarry out real-Time Compensation, the Second-Order Discrete non-linear ratio controller shown in employing formula (21) is to f _{Δ y}and f _{Δ ψ}carry out respectively real-Time Compensation, each channel error is carried out to feedback compensation;

In formula (20) and formula (21), fal (e ₁, α _p, δ _p), fal (e ₂, α _d, δ _d) by formula (22-1), formula (22-2), expressed respectively; K _p, K _d, α _p, δ _p, α _d, δ _dfor controller parameter, u ₀for intermediate variable; In formula (20), e ₁e _vxdtracking signal, b ₀, u (k), z ₂(k) meaning cotype (17); In formula (21), e ₁e _{Δ y}or e _{Δ ψ}tracking signal, e ₂e _{Δ y}or e _{Δ ψ}the tracking signal differential, b ₀, u (k), z ₃(k) meaning cotype (18); It is 3 n dimensional vector ns that driverless operation is taken turns individual drive-alternative controlling quantity of independent steering whole vehicle dynam entirely, is designated as U _c, U _c=[F _xCf _yCm _zC] ^t, k step value U _c(k)=[F _xC(k) F _yC(k) M _zC(k)] ^t, T is the transposition symbol;

Step 4.1), the method for 4.2), 4.2.1), 4.2.2) describing is called driverless operation and entirely takes turns the robust control method of estimating in real time with disturbance that the alternative controlling quantity of individual drive-independent steering vehicle-road track channel Full Vehicle Dynamics is calculated.

6. driverless operation individual drive according to claim 5 and turn to vehicle Full Vehicle Dynamics controlling quantity preparation method, it is characterized in that: Full Vehicle Dynamics controlling quantity integrating step 2 described step 5)) obtained can reach territory, the feasibility of the alternative controlling quantity of Full Vehicle Dynamics that step 4) is generated is judged and is adjusted, obtain the Full Vehicle Dynamics controlling quantity, be total longitudinal force controlling quantity, total side force controlling quantity, total yaw moment controlling quantity, specifically comprise:

5.1) note F _x(k), F _y(k), M _z(k) be respectively total longitudinal force controlling quantity F _x, total side force controlling quantity F _y, total yaw moment controlling quantity M _zk step value, the Full Vehicle Dynamics controlling quantity is U, U=[F _xf _ym _z] ^t, its k step value U (k)=[F _x(k) F _y(k) M _z(k)] ^t, read step 2.2.1) and the Full Vehicle Dynamics controlling quantity that obtains can reach territory v and step 4.2.2) the alternative controlling quantity U of Full Vehicle Dynamics that obtains _c(k)=[F _xC(k) F _yC(k) M _zC(k)] ^t;

5.2) if U _c(k) ∈ v, k step Full Vehicle Dynamics controlling quantity U (k)=U _c(k), i.e. U (k)=[F _xC(k) F _yC(k) M _zC(k)] ^t;

If

to the alternative controlling quantity U of k step Full Vehicle Dynamics _c(k) processed, obtained Full Vehicle Dynamics controlling quantity U (k), specifically comprised:

5.2.1) definition optimization aim function

B (1 :), B (2 :), B (3 :) mean respectively the first row, the second row, the capable vector of the third line of efficiency matrix B, set up Non-linear Optimal Model

mind(k)＝||U _C(k)-Bu _C(k)|| ₂ (24)

The implication of described expression formula (24)～(27) is the alternative controlling quantity U of known Full Vehicle Dynamics _c(k) and efficiency matrix B,, under the constraint of expression formula (25)～(27), ask the u that makes d (k) minimum _c(k); u _c(k) the alternative control vector of vehicle wheel forces of tieing up for 2m, u _c(k)=[F _cx1f _cy1f _cx2f _cy2f _cxmf _cym] ^t, F _cxj, F _cyjbe j the alternative controlling quantity of wheel longitudinal force, the alternative controlling quantity of side force, j=1,2 ..., m, m is more than or equal to 3 positive integer;

be lower bound, the upper bound of permission braking force or the propulsive effort of j wheel;

be lower bound, the upper bound of the permission side force of j wheel; F _maxjbe the total power of permission tire force of j wheel; The system status information data that efficiency matrix B obtains according to step 1) { determine by X}, wheel steering angle, vehicle chassis geometric parameter;

5.2.2) fmincon(that uses MATLAB V7.6.0 version software to provide) function is to step 5.2.1) in the nonlinear optimal problem described of expression formula (24)～(27) solved, result is designated as

will

substitution formula (28) is calculated, and result is the Full Vehicle Dynamics controlling quantity U (k) after adjustment,

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