CN113401113A - Unmanned vehicle direct yaw moment control method and controller based on vehicle stable envelope line - Google Patents

Unmanned vehicle direct yaw moment control method and controller based on vehicle stable envelope line Download PDF

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CN113401113A
CN113401113A CN202110711327.XA CN202110711327A CN113401113A CN 113401113 A CN113401113 A CN 113401113A CN 202110711327 A CN202110711327 A CN 202110711327A CN 113401113 A CN113401113 A CN 113401113A
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vehicle
yaw
yaw moment
slip angle
angular velocity
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CN113401113B (en
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潘公宇
刘一
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Jiangsu University
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    • 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
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/02—Control of vehicle driving stability
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • 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
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/12—Lateral speed
    • B60W2520/125—Lateral acceleration

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Abstract

The invention discloses a method and a controller for controlling a direct yaw moment of an unmanned vehicle based on a vehicle stability envelope curve, and relates to the field of stability control of electric vehicles. Since the effects of the centroid slip angle and yaw rate on vehicle stability are particularly important, a vehicle stability envelope is established based on the centroid slip angle and yaw rate. Obtaining a centroid side slip angle and a yaw angular velocity of the actual vehicle according to Kalman filtering; and establishing sliding mode control to generate direct yaw moment according to the obtained centroid side offset angle and yaw angular velocity in combination with a vehicle stability envelope line, so that the centroid side offset angle and the yaw angular velocity of the vehicle are maintained in a vehicle stability line, and designing an approach law to reduce buffeting of the sliding mode control. And finally, distributing the driving force or the braking force by the obtained direct yaw moment through a yaw moment distributor. The invention realizes the driving stability of the automobile under the conditions of high-speed turning and obstacle avoidance.

Description

Unmanned vehicle direct yaw moment control method and controller based on vehicle stable envelope line
Technical Field
The invention relates to the field of unmanned vehicles, in particular to a method and a controller for controlling a direct yaw moment of an unmanned vehicle with a vehicle stable envelope line.
Background
At present, the new modernization is the irreversible trend of automobile development, and the intelligent unmanned automobile is a great technical innovation. The development of the unmanned automobile can effectively reduce traffic accidents and relieve traffic jam, and the unmanned automobile can generate greater social benefits with the continuous improvement of the intelligent degree. The intelligent electric automobile has the characteristics of parameter uncertainty, time randomness, strong nonlinearity and the like, and the design of a transverse motion control system has profound research significance.
The direct yaw moment control is an additional yaw moment generated by a difference in driving force or braking force between the left and right wheels of the vehicle to ensure lateral stability of the vehicle.
Disclosure of Invention
In order to solve the problem that the stability of the electric automobile is unstable due to excessive steering or insufficient steering under the extreme conditions of high speed, severe road and the like, the invention provides a method for controlling the stability envelope curve of the unmanned automobile direct yaw moment, which effectively improves the response speed and robustness of the system and improves the driving stability of the automobile under the extreme conditions of high speed, severe road and the like.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the method for controlling the direct yaw moment of the unmanned vehicle based on the vehicle stable envelope line comprises the following steps:
step one, establishing a vehicle stability envelope line according to a centroid side slip angle and a yaw velocity which influence the vehicle stability;
secondly, acquiring a mass center slip angle and a yaw angular velocity of the actual vehicle through designed Kalman filtering;
step three, designing direct yaw moment through sliding mode control to keep the mass center side slip angle and the yaw velocity of the vehicle in the stable envelope line of the vehicle;
designing an approach rate to reduce buffeting of sliding mode control and generate a direct yaw moment;
and step five, the yaw moment distributor calculates the driving force or braking moment of four wheels of the actual vehicle according to the direct yaw moment calculated in the step four, so that the vehicle is kept stable.
The unmanned vehicle direct yaw moment controller based on the vehicle stability envelope line comprises a vehicle stability envelope line generator, a Kalman filter, a sliding mode controller and a yaw moment distributor;
the vehicle stability envelope generator: establishing a vehicle stable envelope line according to the centroid side slip angle and the yaw angular speed;
the Kalman filter: estimating to obtain a mass center side slip angle and a yaw angular velocity of the actual vehicle according to the lateral acceleration and the yaw angular velocity obtained by the actual vehicle;
the sliding mode controller: according to the obtained centroid side drift angle and yaw angular velocity, combining with a vehicle stable envelope line, establishing sliding mode control to generate direct yaw moment, keeping the centroid side drift angle and yaw angular velocity of the vehicle in a vehicle stable line, and designing an approach law to reduce buffeting of the sliding mode control;
the yaw moment distributor: and (3) distributing the driving force or the braking force according to the direct yaw moment generated by the slip film controller, and calculating the driving force or the braking moment of four wheels of the actual vehicle to keep the vehicle stable.
Further, the vehicle stability envelope is specifically:
and in a coordinate system with the yaw velocity of the vehicle as a vertical axis and the centroid slip angle as a horizontal axis, the stable state of the vehicle is quickly determined through the envelope line of one parallelogram. If the yaw angle and the centroid slip angle of the vehicle are within the parallelogram, the vehicle state is stable; if the vehicle yaw rate and the centroid slip angle are outside the parallelogram, then the vehicle condition is not stable.
Further, the kalman filter is designed as follows:
and establishing a linear two-degree-of-freedom vehicle dynamic equation containing parameter uncertainty and interference and noise influence according to Newton's law.
Figure RE-GDA0003222431600000021
Figure RE-GDA0003222431600000022
Wherein beta is the vehicle mass center slip angle, r is the yaw angular velocity, m and IZRespectively vehicle mass and moment of inertia,/FAnd lRFront axle and rear axle respectivelyDistance of heart, vxFor vehicle longitudinal speed, delta front wheel angle, CFAnd CRRespectively, front and rear wheel cornering stiffnesses.
And establishing a discrete system state equation and an observation equation by using the model.
x(k+1)＝Ax(k)+Bδ(k)+ω(k)#(11)
y(k)＝Hx(k)+Dδ(k)+v(k)#(12)
Wherein the system n-dimensional state vector
Figure RE-GDA0003222431600000023
System state transition matrix
Figure RE-GDA0003222431600000031
Figure RE-GDA0003222431600000032
Random disturbance of system
Figure RE-GDA0003222431600000033
Systematic observation vector
Figure RE-GDA0003222431600000034
Observation matrix
Figure RE-GDA0003222431600000035
Figure RE-GDA0003222431600000036
System observation noise
Figure RE-GDA0003222431600000037
State one-step prediction
Figure RE-GDA0003222431600000038
And (3) state estimation calculation:
Figure RE-GDA0003222431600000039
a filter gain matrix:
Figure RE-GDA00032224316000000310
where R is the observed noise covariance matrix.
Estimating an error variance matrix:
P(k)＝[1-K(k)H(k)]P(k)-#(15)
one-step prediction error matrix:
P(k)-＝A(k)P(k)AT(k)+Q#(16)
and calculating the estimation of the state value by recursion of the observed value obtained by the real vehicle.
Further, the sliding mode controller is designed as follows:
defining a sliding surface s1Comprises the following steps:
Figure RE-GDA00032224316000000311
where rho is [0,1 ]]To design the parameters, | Δ rmaxTo the maximum absolute value of the set yaw-rate error, | Δ β tintmaxThe maximum absolute value of the slip angle error.
Differential sliding surface s1Obtaining:
Figure RE-GDA00032224316000000312
with a two-degree-of-freedom vehicle model (1), additional moments applied in the lateral direction can be obtained with respect to
Figure RE-GDA00032224316000000313
The formula of (a):
Figure RE-GDA00032224316000000314
substituting (19) into (18) to obtain
Figure RE-GDA00032224316000000315
Order to
Figure RE-GDA00032224316000000316
Can obtain
Figure RE-GDA00032224316000000317
Figure RE-GDA0003222431600000041
In order to reduce buffeting of sliding mode control, the invention designs an approach law with an exponential term:
Figure RE-GDA0003222431600000042
wherein 0<p1<1，p2>0。
Figure RE-GDA0003222431600000043
Wherein 0<c0<1，c1>0， c2>0 and c2E.g. N. H (S) is a positive value and does not affect the stability of the system. When the system is far from the sliding surface p1H, (S) becomes smaller, p2The ratio/H (S) is increased, thereby increasing the approaching speed and increasing the convergence speed to the sliding surface. When the system is close to the sliding surface p1H, (S) and p2The/h(s) are small, and therefore a small control gain is obtained, thereby reducing chattering.
Combining equations (22) and (21), the control rate is obtained as follows:
Figure RE-GDA0003222431600000044
further, the yaw moment distributor is specifically designed as follows:
the longitudinal force distribution of the vehicle tire is distributed according to the axle load proportion, and the front and rear axle load values are as follows:
Figure RE-GDA0003222431600000045
in the formula axFor longitudinal acceleration, FZF，FZRThe vertical load of the front and rear shafts is adopted, and h is the height of the mass center of the whole vehicle.
The longitudinal force of each wheel should satisfy the following conditions while satisfying the yaw moment and the total longitudinal force requirement:
Figure RE-GDA0003222431600000046
the four tire forces are obtained according to the yaw moment and the vertical load, and the longitudinal force of each wheel distributed according to the load ratio is as follows:
Figure RE-GDA0003222431600000047
in the formula Fx1、Fx2、Fx3、Fx4The longitudinal forces of the left front wheel, the right front wheel, the left rear wheel and the right rear wheel respectively, FxThe total longitudinal driving force is determined by the pedal opening, B is the wheel base, and L is the wheel base.
The invention has the beneficial effects that:
1. the invention establishes a vehicle stability envelope curve based on a two-degree-of-freedom vehicle model and a Pacejka tire model to obtain a centroid side deviation angle and yaw velocity envelope curve which can enable the vehicle to maintain stable, and the vehicle can maintain stable as long as the centroid side deviation angle and the yaw velocity of the actual vehicle are in the envelope curve. The problem of obtaining ideal slip angle and yaw rate under the limit working condition is solved.
2. The method comprises the steps of obtaining the mass center slip angle and the yaw angular velocity of an actual vehicle through designed Kalman filtering; the problem that the centroid slip angle is difficult to measure is solved.
3. According to the invention, the direct yaw moment is designed through sliding mode control to keep the mass center side slip angle and the yaw velocity of the vehicle in the stable envelope curve of the vehicle, so that the control failure caused by inaccurate modeling and external environment condition change of the system is solved, and the rapidity and the robustness of the system are improved.
4. According to the method, the buffeting of the sliding mode control is reduced by designing the approach rate, a direct yaw moment is generated, and the buffeting problem in the sliding mode control is solved.
5. The method is easy to realize and is suitable for wide popularization and application.
Drawings
Fig. 1 is a schematic diagram of a direct yaw moment control method for an electric vehicle based on a vehicle stability envelope according to the present invention.
Fig. 2 is a vehicle stability envelope of the present invention vehicle direct yaw moment control method based on the vehicle stability envelope.
Detailed Description
The invention will be further explained with reference to the drawings.
As shown in fig. 1, the direct yaw moment controller of the electric vehicle based on the vehicle stability envelope of the present invention is implemented by a vehicle stability envelope generator, a sliding mode controller, a yaw moment divider, and a kalman filter. And a vehicle stability envelope generator that establishes a vehicle stability envelope based on the centroid slip angle and the yaw rate. The Kalman filter is used for obtaining lateral acceleration and yaw angular velocity through the actual vehicle and inputting the lateral acceleration and the yaw angular velocity into the Kalman filter to obtain a mass center lateral deviation angle and the yaw angular velocity of the actual vehicle; and the sliding mode controller is used for establishing sliding mode control to generate direct yaw moment according to the obtained mass center side offset angle and yaw velocity in combination with the vehicle stable envelope line, so that the mass center side offset angle and the yaw velocity of the vehicle are maintained in the vehicle stable line, and a closing law is designed to reduce buffeting of the sliding mode control. And a yaw moment distributor for distributing the driving force or the braking force by passing the obtained direct yaw moment through the yaw moment distributor. The invention realizes the driving stability of the automobile under the conditions of high-speed turning and obstacle avoidance.
As shown in fig. 2, a vehicle stability envelope is constructed for the centroid slip angle and yaw rate.
The invention relates to an electric vehicle direct yaw moment control method based on a vehicle stable envelope line, which comprises the following concrete implementation steps:
1) generating a vehicle stability envelope
The slip angle β and the yaw rate r of the vehicle state have a crucial effect on the stability of the vehicle. The vehicle stability envelope curve is shown in fig. 1, and as long as the centroid side offset angle beta and the yaw rate r of the vehicle running are within the range of the envelope curve, the running stability of the vehicle can be ensured. The beta-r borderline formula is as follows:
Figure RE-GDA0003222431600000061
Figure RE-GDA0003222431600000062
a1＝tanαr,peak#(3)
Figure RE-GDA0003222431600000063
Figure RE-GDA0003222431600000064
CD and AB are the left boundary and the right boundary of the vehicle stable envelope line mass center side deflection angle respectively, and BC and AD are the upper boundary and the lower boundary of the vehicle stable envelope line yaw angular speed respectively. lRIs the distance of the center of mass to the rear wheel, vxIs the longitudinal velocity, αr,peakMu is the road surface friction coefficient for the maximum slip angle of the rear wheel.
Since the rear wheel is more easily saturated than the front wheel due to the large load on the rear wheel, the stability margin is determined by the rear wheel force peak, and the rear wheel maximum slip angle formula is as follows:
Figure RE-GDA0003222431600000065
where μ is the road surface coefficient of friction. Bringing r into the CD and AB segments, maximum slip angle betamaxAnd minimum slip angle betaminCan be expressed as:
Figure RE-GDA0003222431600000066
Figure RE-GDA0003222431600000067
2) designing a Kalman filter
The centroid slip angle is particularly important for stability under extreme conditions. At present, a highly integrated sensor can measure the yaw velocity of a vehicle in the running process, but the centroid slip angle cannot be directly measured, so that the centroid slip angle is estimated through Kalman filtering.
The algorithm is as follows:
and establishing a linear two-degree-of-freedom vehicle dynamic equation containing parameter uncertainty and interference and noise influence according to Newton's law.
Figure RE-GDA0003222431600000071
Figure RE-GDA0003222431600000072
Wherein beta is the vehicle mass center slip angle, r is the yaw angular velocity, m and IzRespectively vehicle mass and moment of inertia,/FAnd lRDistances from the front and rear axes, respectively, to the center of mass, vxIs a longitudinal direction of the vehicleThe speed of the moving-direction is controlled,
Figure RE-GDA0003222431600000073
for lateral acceleration, delta front wheel angle, CFAnd CRRespectively, front and rear wheel cornering stiffnesses.
And establishing a discrete system state equation and an observation equation by using the model.
x(k+1)＝Ax(k)+Bδ(k)+ω(k)#(11)
y(k)＝Hx(k)+Dδ(k)+v(k)#(12)
Wherein the system n-dimensional state vector
Figure RE-GDA0003222431600000074
System state transition matrix
Figure RE-GDA0003222431600000075
Figure RE-GDA0003222431600000076
Systematic observation vector
Figure RE-GDA0003222431600000077
Observation matrix
Figure RE-GDA0003222431600000078
Figure RE-GDA0003222431600000079
Random disturbance of system
Figure RE-GDA00032224316000000710
System observation noise
Figure RE-GDA00032224316000000711
ω1(k)、ω2(k)、v1(k)、v2(k) The white noise is independent and normally distributed, and the delta t is the system sampling time.
State one-step prediction
Figure RE-GDA00032224316000000712
And (3) state estimation calculation:
Figure RE-GDA00032224316000000713
a filter gain matrix:
K(k)＝P(k)-H(k)T[H(k)P(k)-H(k)T+R]-1
where R is the observed noise covariance matrix.
Estimating an error variance matrix:
P(k)＝[1-K(k)H(k)]P(k)-#(15)
one-step prediction error matrix:
P(k)-＝A(k)P(k)AT(k)+Q#(16)
wherein Q is the covariance of the random perturbation of the system.
And calculating the estimation of the state value by recursion of the observed value obtained by the real vehicle.
3) Design sliding mode controller
The sliding mode controller generates a direct yaw moment, so that the mass center side offset angle and the yaw velocity of the vehicle are maintained in a vehicle stable envelope line, the purpose of keeping the vehicle stable is achieved, and buffeting of sliding mode control is reduced through a designed approach law. Defining a sliding surface s1Comprises the following steps:
Figure RE-GDA0003222431600000081
where rho is [0,1 ]]To design the parameters, | Δ rmaxTo the maximum absolute value of the set yaw-rate error, | Δ β tintmaxThe maximum absolute value of the slip angle error.
Differential sliding surface s1Obtaining:
Figure RE-GDA0003222431600000082
wherein (r, beta) is a point outside the stable envelope line, (r)safe,βsafe) To the nearest point on the stability envelope.
With a two-degree-of-freedom vehicle model (1), additional moments applied in the lateral direction can be obtained with respect to
Figure RE-GDA00032224316000000811
The formula of (a):
Figure RE-GDA0003222431600000083
wherein FFy、FRyFront and rear wheel side forces, M, respectivelyzIs the yaw moment.
Substituting (19) into (18) to obtain
Figure RE-GDA0003222431600000084
Order to
Figure RE-GDA0003222431600000085
Can obtain
Figure RE-GDA0003222431600000086
Figure RE-GDA0003222431600000087
In order to reduce buffeting of sliding mode control, the invention designs an approach law with an exponential term:
Figure RE-GDA0003222431600000088
wherein 0<p1<1，p2>0。
Figure RE-GDA0003222431600000089
Wherein 0<c0<1，c1>0， c2>0 and c2E.g. N. H (S) is a positive value and does not affect the stability of the system. When the system is far from the sliding surface p1H, (S) becomes smaller, p2The ratio/H (S) is increased, thereby increasing the approaching speed and increasing the convergence speed to the sliding surface. When the system is close to the sliding surface p1H, (S) and p2The/h(s) are small, and therefore a small control gain is obtained, thereby reducing chattering.
Combining equations (22) and (21), the control rate is obtained as follows:
Figure RE-GDA00032224316000000810
4) distributor for designing transverse moment
The direct yaw moment output by the sliding mode controller generates driving force or braking force of wheels through the yaw moment distributor.
The vehicle tire longitudinal force distribution is generally distributed in axle load proportion. The front and rear axle load values are as follows:
Figure RE-GDA0003222431600000091
in the formula axFor longitudinal acceleration, FZF，FZRThe vertical load of the front shaft and the rear shaft is adopted, and h is the height of the mass center of the whole vehicle.
The longitudinal force of each wheel should satisfy the following conditions while satisfying the yaw moment and the total longitudinal force requirement:
Figure RE-GDA0003222431600000092
in combination (24) (25), the longitudinal forces of the individual wheels, distributed according to the load ratio, are obtained as follows:
Figure RE-GDA0003222431600000093
in the formula Fx1、Fx2、Fx3、Fx4The longitudinal forces of the left front wheel, the right front wheel, the left rear wheel and the right rear wheel respectively, FxThe total longitudinal driving force is determined by the pedal opening, and B is the wheel track.
The above-listed series of detailed descriptions are merely specific illustrations of possible embodiments of the present invention, and they are not intended to limit the scope of the present invention, and all equivalent means or modifications that do not depart from the technical spirit of the present invention are intended to be included within the scope of the present invention.

Claims (10)

1. The method for controlling the direct yaw moment of the unmanned vehicle based on the vehicle stable envelope line is characterized by comprising the following steps of:
s1, establishing a vehicle stability envelope curve according to the centroid slip angle and the yaw rate which influence the vehicle stability;
s2, acquiring the centroid slip angle and the yaw rate of the actual vehicle;
s3, designing a sliding mode controller for direct yaw moment, and keeping the mass center side slip angle and the yaw velocity of the vehicle in the stable envelope curve of the vehicle;
s4, designing an approach rate to reduce buffeting of the sliding mode controller and generating a direct yaw moment;
and S5, obtaining the driving force or braking torque of the four wheels of the actual vehicle according to the direct yaw moment generated in the steps S3 and S4, and keeping the vehicle stable.
2. The method for controlling the direct yaw moment of the unmanned aerial vehicle based on the vehicle stability envelope curve of claim 1, wherein the vehicle stability envelope curve established in S1 is specifically:
in a coordinate system with the yaw angular velocity of the vehicle as a vertical axis and the centroid side deviation angle as a horizontal axis, quickly determining the stable state of the vehicle through the envelope line of one parallelogram, and if the yaw angular velocity of the vehicle and the centroid side deviation angle are within the parallelogram, indicating that the state of the vehicle is stable; if the vehicle yaw angular velocity and the centroid slip angle are outside the parallelogram, the vehicle state is unstable;
to keep the centroid slip angle β and the yaw rate r within this range, the equation for the β -r boundary line is designed as follows:
Figure FDA0003133061350000011
Figure FDA0003133061350000012
a1＝tan αr，peak#(3)
Figure FDA0003133061350000013
Figure FDA0003133061350000014
wherein lRIs the distance of the center of mass to the rear wheel, vxIs the longitudinal velocity, αr，peakIs the maximum slip angle of the rear wheel, mu is the road surface friction coefficient;
since the rear wheel is more easily saturated than the front wheel due to the large load on the rear wheel, the stability margin is determined by the rear wheel force peak, and the rear wheel maximum slip angle formula is as follows:
Figure FDA0003133061350000015
where mu is the road friction coefficient, r is taken into the CD and AB sections, and the maximum slip angle betamaxAnd minimum slip angle betaminCan be expressed as:
Figure FDA0003133061350000021
Figure FDA0003133061350000022
3. the method for controlling the direct yaw moment of the unmanned vehicle based on the vehicle stability envelope curve of claim 1, wherein in the step S2, the centroid slip angle is estimated by a designed kalman filter, and the specific process is as follows:
according to Newton's law, a linear two-degree-of-freedom vehicle dynamic equation containing parameter uncertainty and interference and noise influence is established:
Figure FDA0003133061350000023
Figure FDA0003133061350000024
wherein beta is the vehicle mass center slip angle, r is the yaw angular velocity, m and IZRespectively vehicle mass and moment of inertia,/FAnd lRDistances from the front and rear axes, respectively, to the center of mass, vxAs is the longitudinal speed of the vehicle,
Figure FDA0003133061350000025
is lateral acceleration, delta front wheel angle, CFAnd CRFront and rear wheel cornering stiffness, respectively;
establishing a discrete system state equation and an observation equation by using the model:
x(k+1)＝Ax(k)+Bδ(k)+ω(k)#(11)
y(k)＝Hx(k)+Dδ(k)+v(k)#(12)
wherein the system n-dimensional state vector
Figure FDA0003133061350000026
System state transition matrix
Figure FDA0003133061350000027
Random disturbance of system
Figure FDA0003133061350000028
Systematic observation vector
Figure FDA0003133061350000029
Observation matrix
Figure FDA00031330613500000210
System observation noise
Figure FDA00031330613500000211
ω1(k)、ω2(k)、v1(k)、v2(k) White noise which is mutually independent and normally distributed, and delta t is system sampling time;
state one-step prediction
Figure FDA00031330613500000212
And (3) state estimation calculation:
Figure FDA0003133061350000031
a filter gain matrix:
K(k)＝P(k)-H(k)T[H(k)P(k)-H(k)T+R]-1
wherein R is an observation noise covariance matrix;
estimating an error variance matrix:
P(k)＝[1-K(k)H(k)]P(k)-#(15)
one-step prediction error matrix:
P(k)-＝A(k)P(k)AT(k)+Q#(16)
and calculating the estimation of the state value by recursion of the observed value obtained by the real vehicle.
4. The method for controlling a direct yaw moment of an unmanned vehicle based on a vehicle stability envelope according to claim 1, wherein in S2, the yaw rate is obtained by a sensor.
5. The method for controlling the direct yaw moment of the unmanned vehicle based on the vehicle stability envelope curve according to claim 1, wherein the specific process of designing the sliding mode controller of the direct yaw moment at S3 is as follows:
defining a sliding surface s1Comprises the following steps:
Figure FDA0003133061350000032
where rho is [0,1 ]]To design the parameters, | Δ rmaxTo the maximum absolute value of the set yaw-rate error, | Δ β tintmaxIs the maximum absolute value of the slip angle error;
differential sliding surface s1Obtaining:
Figure FDA0003133061350000033
with a two-degree-of-freedom vehicle model (1), additional moments applied in the lateral direction can be obtained with respect to
Figure FDA0003133061350000039
The formula of (a):
Figure FDA0003133061350000034
substituting (19) into (18) to obtain
Figure FDA0003133061350000035
Order to
Figure FDA0003133061350000036
Intermediate values can be obtained
Figure FDA0003133061350000037
Figure FDA0003133061350000038
6. The method according to claim 5, wherein the step of S4 is a step of directly controlling the yaw moment of the unmanned vehicle according to an exponential term, specifically as follows:
Figure FDA0003133061350000041
wherein 0 < p1＜1，p2＞0，
Figure FDA0003133061350000042
Wherein 0 < c0＜1，c1＞0，c2> 0 and c2Epsilon is N, H (S) is a positive value, and the stability of the system is not influenced;
when the system is far away from the sliding surface, p1H, (S) smaller, p2(S) increases the size of the sliding surface, increases the approaching speed, and increases the convergence speed to the sliding surface;
when the system is close to the sliding surface, p1H, (S) and p2(S) are all small, and a small control gain is obtained so as to reduce buffeting;
combining equations (22) and (21), the control rate is obtained as follows:
Figure FDA0003133061350000043
7. the method for controlling the direct yaw moment of the unmanned aerial vehicle based on the vehicle stability envelope according to claim 6, wherein the specific process of S5 is as follows:
the longitudinal force distribution of the vehicle tire is distributed according to the axle load proportion, and the front and rear axle load values are as follows:
Figure FDA0003133061350000044
in the formula axFor longitudinal acceleration, FZF，FZRThe vertical load of the front shaft and the rear shaft is adopted, and h is the height of the mass center of the whole vehicle;
the longitudinal force of each wheel should satisfy the following conditions while satisfying the yaw moment and the total longitudinal force requirement:
Figure FDA0003133061350000045
combining (24) and (25) to obtain the longitudinal force of each wheel distributed according to the load ratio as follows:
Figure FDA0003133061350000046
in the formula Fx1、Fx2、Fx3、Fx4The longitudinal forces of the left front wheel, the right front wheel, the left rear wheel and the right rear wheel are respectively, Fx is total longitudinal driving force and is determined by pedal opening, and B is wheel track.
8. The unmanned vehicle direct yaw moment controller based on the vehicle stability envelope line is characterized by comprising a vehicle stability envelope line generator, a Kalman filter, a sliding mode controller and a yaw moment distributor;
the vehicle stability envelope generator: establishing a vehicle stable envelope line according to the centroid side slip angle and the yaw angular speed;
the Kalman filter: estimating to obtain a mass center side slip angle and a yaw angular velocity of the actual vehicle according to the lateral acceleration and the yaw angular velocity obtained by the actual vehicle;
the sliding mode controller: according to the obtained centroid side drift angle and yaw angular velocity, combining with a vehicle stable envelope line, establishing sliding mode control to generate direct yaw moment, keeping the centroid side drift angle and yaw angular velocity of the vehicle in a vehicle stable line, and designing an approach law to reduce buffeting of the sliding mode control;
the yaw moment distributor: and (3) distributing the driving force or the braking force according to the direct yaw moment generated by the slip film controller, and calculating the driving force or the braking moment of four wheels of the actual vehicle to keep the vehicle stable.
9. The vehicle stability envelope-based unmanned aerial vehicle direct yaw moment controller of claim 8, wherein the vehicle stability envelope is specifically:
in a coordinate system with the yaw angular velocity of the vehicle as a vertical axis and the centroid side deviation angle as a horizontal axis, quickly determining the stable state of the vehicle through the envelope line of one parallelogram, and if the yaw angular velocity of the vehicle and the centroid side deviation angle are within the parallelogram, indicating that the state of the vehicle is stable; if the vehicle yaw angular velocity and the centroid slip angle are outside the parallelogram, the vehicle state is unstable;
the kalman filter is designed as follows:
establishing a linear two-degree-of-freedom vehicle dynamic equation containing parameter uncertainty and interference and noise influence according to Newton's law;
Figure FDA0003133061350000051
Figure FDA0003133061350000052
wherein beta is the vehicle mass center slip angle, r is the yaw angular velocity, m and IZRespectively vehicle mass and moment of inertia,/FAnd lRDistances from the front and rear axes, respectively, to the center of mass, vxFor vehicle longitudinal speed, delta front wheel angle, CFAnd CRFront and rear wheel cornering stiffness, respectively;
establishing a discrete system state equation and an observation equation by using the model:
x(k+1)＝Ax(k)+Bδ(k)+ω(k)#(11)
y(k)＝Hx(k)+Dδ(k)+v(k)#(12)
wherein the system n-dimensional state vector
Figure FDA0003133061350000061
System state transition matrix
Figure FDA0003133061350000062
Random disturbance of system
Figure FDA0003133061350000063
Systematic observation vector
Figure FDA0003133061350000064
Observation matrix
Figure FDA0003133061350000065
System observation noise
Figure FDA0003133061350000066
State one-step prediction
Figure FDA0003133061350000067
And (3) state estimation calculation:
Figure FDA0003133061350000068
a filter gain matrix:
K(k)＝P(k)-H(k)T[H(k)P(k)-H(k)T+R]-1
wherein R is an observation noise covariance matrix;
estimating an error variance matrix:
P(k)＝[1-K(k)H(k)]P(k)-#(15)
one-step prediction error matrix:
P(k)-＝A(k)P(k)AT(k)+Q#(16)
and calculating the estimation of the state value by recursion of the observed value obtained by the real vehicle.
10. The vehicle stability envelope-based unmanned aerial vehicle direct yaw moment controller of claim 8, wherein the sliding-mode controller is designed to:
defining a sliding surface s1Comprises the following steps:
Figure FDA0003133061350000069
where rho is [0,1 ]]To design the parameters, | Δ rmaxTo the maximum absolute value of the set yaw-rate error, | Δ β tintmaxIs the maximum absolute value of the slip angle error;
differential sliding surface s1Obtaining:
Figure FDA00031330613500000610
with a two-degree-of-freedom vehicle model (1), additional moments applied in the lateral direction can be obtained with respect to
Figure FDA00031330613500000611
The formula of (a):
Figure FDA0003133061350000071
substituting (19) into (18) to obtain
Figure FDA0003133061350000072
Order to
Figure FDA0003133061350000073
Can obtain
Figure FDA0003133061350000074
Figure FDA0003133061350000075
In order to reduce buffeting of sliding mode control, the invention designs an approach law with an exponential term:
Figure FDA0003133061350000076
wherein 0 < p1＜1，p2＞0。
Figure FDA0003133061350000077
Wherein 0 < c0＜1，c1＞0，c2> 0 and c2Epsilon N, H (S) is a positive value, the stability of the system is not influenced, and p is when the system is far away from the sliding surface1H, (S) smaller, p2(S) becomes large, thereby increasing the approaching speed and accelerating the convergence speed to the sliding surface, p is when the system approaches to the sliding surface1H, (S) and p2(s) are small, thus achieving a small control gain, thereby reducing buffeting;
combining equations (22) and (21), the control rate is obtained as follows:
Figure FDA0003133061350000078
the yaw moment distributor is specifically designed as follows:
the longitudinal force distribution of the vehicle tire is distributed according to the axle load proportion, and the front and rear axle load values are as follows:
Figure FDA0003133061350000079
in the formula axFor longitudinal acceleration, FZF，FZRThe vertical load of the front shaft and the rear shaft is adopted, and h is the height of the mass center of the whole vehicle;
the longitudinal force of each wheel should satisfy the following conditions while satisfying the yaw moment and the total longitudinal force requirement:
Figure FDA00031330613500000710
the four tire forces are obtained according to the yaw moment and the vertical load, and the longitudinal force of each wheel distributed according to the load ratio is as follows:
Figure FDA0003133061350000081
in the formula Fx1、Fx2、Fx3、Fx4The longitudinal forces of the left front wheel, the right front wheel, the left rear wheel and the right rear wheel respectively, FxThe total longitudinal driving force is determined by the pedal opening, and B is the wheel track.
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