CN113619564A - Active rollover prevention control method for unmanned carrier - Google Patents

Active rollover prevention control method for unmanned carrier Download PDF

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CN113619564A
CN113619564A CN202110894838.XA CN202110894838A CN113619564A CN 113619564 A CN113619564 A CN 113619564A CN 202110894838 A CN202110894838 A CN 202110894838A CN 113619564 A CN113619564 A CN 113619564A
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control
vehicle
active
angle
model
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刘玮
俞跃
刘萍
万益东
张庆杰
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Yancheng Institute of Technology
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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, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/02—Control of vehicle driving stability
    • B60W30/04—Control of vehicle driving stability related to roll-over prevention
    • 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
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/20—Conjoint control of vehicle sub-units of different type or different function including control of steering systems
    • 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
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/30—Conjoint control of vehicle sub-units of different type or different function including control of auxiliary equipment, e.g. air-conditioning compressors or oil pumps
    • 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, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/02—Control of vehicle driving stability
    • B60W30/045—Improving turning performance
    • 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
    • B60W2520/18—Roll
    • 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
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/20—Steering systems
    • 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
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/30—Auxiliary equipments

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

Abstract

The invention discloses an active rollover prevention control method for an unmanned transport vehicle, which comprises the following steps: establishing an unmanned carrier dynamics model and a two-degree-of-freedom vehicle model to obtain ideal values of the yaw velocity, the mass center slip angle and the vehicle body roll angle of the unmanned carrier; when the actual values of the yaw angular velocity and the centroid slip angle are larger than the ideal values, the vehicle is not considered to be in a stable state, the active steering controller is started to control, and the front wheel active turning angle is obtained based on model predictionΔ δAnd output to the active steering controller, the active steering actuator acts; otherwise, the vehicle is considered to be stable and the main operation is not carried outPerforming dynamic control; when the actual value of the roll angle of the vehicle body is larger than the ideal value of the roll angle of the vehicle body, the vehicle is considered to be in an unstable state, and roll control moment is obtained based on sliding mode controlΔM xc And calculates the actuating power of the push rod motorF xi And outputting the calculation result to a load platform controller, and enabling a load platform actuator to act. The invention provides a rollover prevention control strategy combining active steering and load platform mass center adjustment, which effectively reduces the rollover phenomenon of the unmanned carrier caused by the fact that the unmanned carrier is on a slope and under the condition of high mass center of goods accumulation.

Description

Active rollover prevention control method for unmanned carrier
Technical Field
The invention relates to an active rollover prevention control method for an unmanned transport vehicle, and belongs to the technical field of rollover control.
Background
The automatic guided vehicle has the obvious advantages of simplified overall vehicle arrangement structure, simple and convenient chassis active control and the like and wide market prospect, and is becoming a research hotspot of domestic and foreign scholars. At present, most of unmanned transport vehicles are driven in a distributed mode, and the unmanned transport vehicles serving as a novel driving mode of electric automobiles have unique stability control advantages in the aspects of driving/braking antiskid, differential power steering, active yaw control and the like, and can improve the active safety of the vehicles.
Experts and scholars at home and abroad carry out a great deal of research on rollover prevention control of electric vehicles and other vehicles and have already achieved related achievements.
The prior research mostly focuses on the rollover prevention control of passenger vehicles under the high-speed steering working condition, the research object of the invention is an unmanned transport vehicle in an intelligent factory, and the rollover can be caused by the mass center change of a vehicle body and goods when the vehicle runs on a slope due to the fact that the mass center is higher when the goods are transported.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides an active rollover prevention control method for an unmanned transport vehicle, so as to solve the technical problem that the rollover control performance of the unmanned transport vehicle is poor in the prior art.
In order to solve the technical problem, the invention is realized by adopting the following scheme:
the invention provides an active rollover prevention control method for an unmanned transport vehicle, which comprises the following steps: establishing an unmanned transport vehicle dynamics model and a two-degree-of-freedom vehicle model to obtainIdeal values of yaw angular velocity, mass center slip angle and vehicle body roll angle of the unmanned transport vehicle are obtained; when the actual values of the yaw angular velocity and the centroid slip angle are larger than ideal values, the vehicle is not in a stable state, an active steering controller is started to control, the front wheel active turning angle delta is obtained based on model prediction and is output to the active steering controller, and an active steering actuator acts; otherwise, the vehicle is considered to be stable, and active control is not carried out; when the actual value of the roll angle of the vehicle body is larger than the ideal value of the roll angle of the vehicle body, the vehicle is considered to be in an unstable state, and the roll control moment delta M is obtained based on the sliding mode controlxcAnd calculates the actuating force F of the push rod motorxiAnd outputting the calculation result to a load platform controller, and enabling a load platform actuator to act.
Preferably, the automated guided vehicle dynamics model is:
the longitudinal, lateral and yaw motion equations are:
Figure BDA0003197467880000021
where m is the vehicle mass, vxAnd vyRespectively the longitudinal and transverse speeds of the mass center under the vehicle body coordinate system;
Figure BDA0003197467880000022
and
Figure BDA0003197467880000023
acceleration in the longitudinal and transverse directions; γ and
Figure BDA0003197467880000024
respectively yaw angular velocity and yaw angular acceleration, FxiAnd Fyi(i ═ fl, fr, rl, rr) are the tire longitudinal and lateral forces, respectively; i isZThe moment of inertia of the vehicle around the Z axis; lfAnd lrDistances from the center of mass to the front and rear axes, respectively; d1And d2Respectively representing the distance from the equivalent wheel to the left and right wheels; deltafl、δfrRespectively the left and right steering angles of the front wheels; deltarl、δrrThe rear wheel left and right steering angle.
The method for establishing the tire model based on the magic formula comprises the following steps:
Figure BDA0003197467880000031
wherein y (x) represents the lateral or longitudinal force to which the tire is subjected; the independent variable x may represent the slip angle or the longitudinal slip ratio of the tire, respectively; B. c, D, E are fitting coefficients, which in turn are determined from the vertical load and camber angle of the tire, where B is the stiffness factor; c is a curve shape factor; d is a crest factor; and E is a curve curvature factor.
Preferably, the state space equation of the two-degree-of-freedom vehicle model is
Figure BDA0003197467880000032
Wherein the content of the first and second substances,
x＝[β γ]T；u＝δ
Figure BDA0003197467880000033
Figure BDA0003197467880000034
calculating the ideal value beta of the centroid slip angledAnd yaw rate ideal value gammadRespectively as follows:
Figure BDA0003197467880000035
Figure BDA0003197467880000036
wherein mu is a road surface adhesion coefficient; gamma rayrefIs twoNominal value of yaw rate calculated by the degree-of-freedom reference model, and hence
Figure BDA0003197467880000041
Wherein K is a stability factor,
Figure BDA0003197467880000042
ideal value phi for controlling roll angle of car bodydWith lateral acceleration ayThe relationship of (1) is:
Figure BDA0003197467880000043
preferably, the active steering control is prioritized over the loaded platform control.
Preferably, the active steering controller and the load platform controller are electrically and mechanically connected with the cooperative controller respectively, the cooperative controller obtains the running state of the unmanned carrying vehicle, new control instructions are formed through calculation, and iterative control is completed through repeated instructions.
Preferably, the active steering controller uses a model prediction algorithm, and uses the yaw rate and the centroid yaw angle as system control inputs and uses the front and rear wheel steering angle rotation amount as a control output. The system constraint output is:
y＝C1X (3-6)
in the formula (I), the compound is shown in the specification,
Figure BDA0003197467880000044
X＝[β γ]T；
the state space incremental model for transforming the system continuous state equation into the discrete time system is as follows:
Figure BDA0003197467880000045
in the formula, Ao＝exp(ATs)，
Figure BDA0003197467880000046
Determining an objective function:
Figure BDA0003197467880000051
in the formula rβ,j(k+i)、rγ,j(k + i) are the jth component of the reference output sequence, respectively; gamma-shapedu,iIs a weighted matrix of control inputs, and the system's future P-th predicted input can be expressed as:
Y(k+1|k)＝SxΔx(k)+Iyc(k)+SuΔU(k) (3-9)
Figure BDA0003197467880000052
in the formula Inc×ncIs the identity matrix, nc is the matrix dimension of the control.
The control quantity, the control increment and the output quantity of the system satisfy the following control constraints and output constraints:
Figure BDA0003197467880000053
Figure BDA0003197467880000054
Figure BDA0003197467880000055
the constraint optimization problem is converted into a quadratic programming problem by adopting numerical solution, and the objective function is at the moment k
Figure BDA0003197467880000056
In the formula
Figure BDA0003197467880000057
Solving the control input increment delta U (k) at the moment k, and taking the first step delta U (k) as a control input quantity
Δu(k)＝(I nu×nu 0 … 0)ΔU*(k) (3-11)
In the formula, Δ u (k) is a front wheel steering angle Δ δ to be solved.
Preferably, the method further comprises the following steps: when the vehicle body rolls, the load platform controller generates a control moment opposite to the rolling direction:
Figure BDA0003197467880000061
in the formula,. DELTA.MxcMoment for roll control of the loaded platform, FxiIs the actuating power of the push rod motor.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention provides a rollover prevention control strategy combining active steering and load platform mass center adjustment by taking an unmanned carrier driven by a hub motor as an object, and effectively reduces the rollover phenomenon of the unmanned carrier caused by a slope and a high mass center of goods accumulation.
2. According to the invention, a combined controller containing an active steering and a load platform is constructed by adopting a model prediction and sliding mode control algorithm according to an ideal state value of a vehicle lateral stability parameter, the active steering controller and the load platform controller are coordinately controlled, the side-turning prevention control is carried out on the unmanned transport vehicle, and the control effect is far better than that of a single control system.
3. The invention also effectively demonstrates the practical effectiveness and the remarkable progress of the active rollover prevention control method of the unmanned transport vehicle through simulation and prototype experiments.
Drawings
Fig. 1 is a flowchart of an active rollover prevention control method for an automated guided vehicle according to an embodiment of the present invention;
FIG. 2 is a diagram of a dynamics model of an automated guided vehicle according to an embodiment of the present invention;
FIG. 3 is a time-varying simulation diagram of the yaw rate of the automated guided vehicle under four control modes provided by the embodiment of the invention;
FIG. 4 is a simulation diagram of the change of the lateral deviation angle of the center of mass of the automated guided vehicle with time under four control modes provided by the embodiment of the invention;
FIG. 5 is a simulation diagram of changes in the roll angles of the body of the automated guided vehicle with time under four control modes provided by the embodiment of the invention;
FIG. 6 is a graph comparing actual control of the yaw rate of an automated guided vehicle to an ideal control curve provided by an embodiment of the present invention;
FIG. 7 is a comparison graph of the actual control curve and the ideal control curve of the centroid slip angle of the automated guided vehicle according to the embodiment of the present invention;
FIG. 8 is a comparison graph of the actual control curve and the ideal control curve of the roll angle of the body of the automated guided vehicle according to the embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art through specific situations.
As shown in fig. 1, the invention constructs an active anti-rollover control strategy integrating active steering and a load platform, firstly, a dynamics theory analysis is performed on the unmanned transport vehicle, a dynamics model of the unmanned transport vehicle is established, a practical application scene of the anti-rollover control of the transport vehicle is considered to be a road environment with a certain gradient, in order to facilitate the development of the control strategy, a vehicle model is simplified, and a three-degree-of-freedom dynamics model pair as shown in fig. 2 is established for analysis, wherein the model comprises dynamics states of a vehicle body in three directions of yaw, longitudinal and lateral, so as to meet the anti-rollover control requirement. Suppose that: regardless of pitch and vertical motion of the vehicle; neglecting the tire cornering characteristics of the left and right wheels varying due to the variation in load; the influence of unsprung mass roll and lateral wind is not considered, and the influence of a suspension roll stiffness damping coefficient and equivalent roll stiffness is simplified; the aerodynamic effect was neglected. The longitudinal, transverse and yaw motion equations of the whole vehicle are as follows:
Figure BDA0003197467880000081
where m is the vehicle mass, vxAnd vyRespectively the longitudinal and transverse speeds of the mass center under the vehicle body coordinate system;
Figure BDA0003197467880000082
and
Figure BDA0003197467880000083
acceleration in the longitudinal and transverse directions; γ and
Figure BDA0003197467880000084
respectively yaw angular velocity and yaw angular acceleration, FxiAnd Fyi(i ═ fl, fr, rl, rr) are the tire longitudinal and lateral forces, respectively; i isZThe moment of inertia of the vehicle around the Z axis; lfAnd lrDistances from the center of mass to the front and rear axes, respectively; d1And d2Respectively representing the distance from the equivalent wheel to the left and right wheels; deltafl、δfrRespectively the left and right steering angles of the front wheels; deltarl、δrrThe rear wheel left and right steering angle.
In addition, an unmanned transport vehicle tire model is established for completely expressing the longitudinal force, the lateral force, the aligning moment, the overturning moment, the resisting moment and the combined working condition of the longitudinal force and the lateral force of the tire. The expression of the tire model is established based on the magic formula as follows:
Figure BDA0003197467880000091
wherein y (x) represents the lateral or longitudinal force to which the tire is subjected; the independent variable x may represent the slip angle or the longitudinal slip ratio of the tire, respectively; B. c, D, E are fitting coefficients, which in turn are determined from the vertical load and camber angle of the tire, where B is the stiffness factor; c is a curve shape factor; d is a crest factor; and E is a curve curvature factor.
In the invention, the hub motor adopted by the unmanned transport vehicle is a permanent magnet synchronous motor, the torque response of the hub motor can be simplified into a second-order delay system and a transfer function
Figure BDA0003197467880000092
In the formula, TmFor actual output torque of the motor, Tm *And xi is the structural parameter of the motor.
The precondition for the active rollover prevention control of the vehicle is that the rollover risk of the vehicle can be judged in advance. When the vehicle runs on a longitudinal road on a slope, the lateral acceleration of the vehicle exceeds a certain limit value, the vertical counter force of the wheels on the inner side of the vehicle is zero, and the vehicle can deviate from an expected track and even generate uncontrollable results such as rollover and the like. Assuming that the longitudinal speed and the lateral speed of the vehicle are basically unchanged, neglecting the lateral rolling, pitching and vertical movements, selecting a linear 2-degree-of-freedom reference model as a dynamic prediction model of a model prediction controller, wherein the state space equation is
Figure BDA0003197467880000093
Wherein:
x＝[βγ]T；u＝δ
Figure BDA0003197467880000101
Figure BDA0003197467880000102
considering the adhesion condition of the road surface, the maneuvering performance requirement of the vehicle and the stability requirement of the vehicle, the ideal value beta of the centroid slip angle can be calculated by a two-degree-of-freedom vehicle modeldAnd yaw rate ideal value gammadAre respectively as
Figure BDA0003197467880000103
Figure BDA0003197467880000104
Wherein mu is a road surface adhesion coefficient; gamma rayrefNominal value of yaw rate calculated for a 2-degree-of-freedom reference model, and therefore
Figure BDA0003197467880000105
Wherein K is a stability factor,
Figure BDA0003197467880000106
ideal value phi for controlling roll angle of car bodydWith lateral acceleration ayCan be expressed as:
Figure BDA0003197467880000107
and moreover, the designed controller comprises a model prediction control algorithm-based real-time solution of the optimal front wheel steering angle delta and a variable coefficient sliding mode control rate-based calculation of the load platform control moment delta Mx, and the result obtained by the solution is calculated to generate control instructions of each mechanism. Firstly, yaw stability control is carried out on the vehicle through active steering, when the control effect is insufficient, the load platform starts to intervene, roll control on the vehicle body is realized through adjustment of the mass center, the mass center roll angle and the vehicle body roll angle can be controlled within an ideal area through combined control of the mass center and the vehicle body, and the roll stability of the intelligent carrying vehicle is greatly improved.
In FIG. 1,. beta.dIs an ideal centroid slip angle, gammadFor ideal yaw rate, phidFor ideal body roll angle, Δ δ*To output a steering angle of ideal, Fxi *The push rod motor outputs acting force for ideal.
When lateral stability control is carried out, active steering is to adjust the stability of a vehicle by adjusting the steering angle of wheels, and the priority of the active steering is higher than that of load platform control because the energy consumed by the steering of the wheels is smaller and the response is faster. The main control flow is as follows:
(1) when the yaw angular velocity and the mass center slip angle are larger than ideal values, the vehicle is not considered to be in a stable state, the active steering controller is started to control, and the front wheel active turning angle delta is calculated based on model prediction and is output to the active steering controller; otherwise, the vehicle is considered to be stable and no active control is performed.
(2) If the active steering fails to make the vehicle reach a steady state, i.e. the roll angle phi of the vehicle body>ΦdIf the vehicle is still in an unstable state, the roll is obtained based on the sliding mode controlControl moment Δ MxcAnd calculating the actuating force F of the push rod motorxiAnd outputting the calculation result to the load platform controller.
(3) Each actuator takes the generated active steering angle delta and the load platform push rod motor as power FxiSending the data to a whole vehicle model and controlling the running state of the vehicle; and the cooperative controller acquires the running state of the vehicle, performs the next calculation to form a new control instruction, and repeats the instruction to complete iterative control.
The cooperative controller needs to perform cooperative control on the active steering and the load platform, and is more complex compared with a single control system, the calculation requirement on the controller is higher, and the control effect is far better than that of the single control system.
Specifically, the active steering controller controls the rollover method by taking the yaw velocity and the mass center yaw angle of the vehicle as control variables, the lateral stability of the vehicle can be kept by adjusting the front wheel steering angle, and the roll phenomenon of the vehicle can be improved to a certain extent when the yaw motion of the vehicle body is controlled due to the fact that a certain coupling phenomenon exists among the motions of the vehicle in all directions. Meanwhile, when the vehicle rolls, the roll component of one vehicle body causes the whole vehicle body to incline towards the roll direction, so that the vehicle is easy to deviate from a preset track gradually, and the track precision of the vehicle can be improved by giving a front wheel steering angle opposite to the roll direction.
And (3) building an active steering controller by utilizing a model prediction algorithm, taking the yaw rate and the centroid yaw angle as system control input, and taking the angular rotation quantity of the front and rear wheels as control output. Ignoring other interference, the system constraint output is:
y＝C1X (3-6)
in the formula (I), the compound is shown in the specification,
Figure BDA0003197467880000121
X＝[β γ]T
the incremental model of state space for transforming the continuous state equation of the system into a discrete-time system is
Figure BDA0003197467880000122
In the formula, Ao＝exp(ATs)，
Figure BDA0003197467880000123
To bring the ideal controlled input close to the reference input, an objective function is determined:
Figure BDA0003197467880000131
in the formula rβ,j(k+i)、rγ,j(k + i) are the jth component of the reference output sequence, respectively; gamma-shapedu,iIs a weighted matrix of control inputs, and the system's future P-th predicted input can be expressed as:
Y(k+1|k)＝SxΔx(k)+Iyc(k)+SuΔU(k) (3-9)
Figure BDA0003197467880000132
in the formula Inc×ncIs the identity matrix, nc is the matrix dimension of the control.
Considering the constraints of the control process, i.e., the control amount, the control increment, and the output amount of the system satisfy the following control constraints and output constraints
Figure BDA0003197467880000133
Figure BDA0003197467880000134
Figure BDA0003197467880000135
The constraint optimization problem is converted into a quadratic programming problem by adopting numerical solution, and the objective function is at the moment k
Figure BDA0003197467880000136
In the formula
Figure BDA0003197467880000137
Solving the control input increment delta U (k) at the moment k, and taking the first step delta U (k) as a control input quantity
Δu(k)＝(Inu×nu 0 … 0)ΔU*(k) (3-11)
In the formula, Δ u (k) is a front wheel steering angle Δ δ to be solved.
Specifically, the method for controlling the rollover by the load platform controller comprises the following steps: and after the yaw stability control is carried out, the vehicle is still in an unstable state, and the load platform is started to carry out roll control. When the vehicle runs laterally on a slope with a certain angle, the longitudinal force requirement is large, the lateral force of the tire tends to be saturated, the lateral force generated in the running process cannot be overcome, the vehicle deviates from an expected track, and even the vehicle turns over.
When the load platform is controlled to roll, the component of the spring load mass in the roll direction is reduced, the component of the whole vehicle body in the roll direction is reduced, the difference between the vertical forces borne by the left wheel and the right wheel is reduced compared with the vertical force borne before control, and the position of the center of mass is adjusted. The linear motor is used for outputting vertical moment to generate roll control moment to control the roll of the vehicle body, so that the vertical component force of the vehicle body and platform goods in the roll direction is reduced, and the active safety function of improving the roll is achieved. When the whole vehicle body rolls, the floating platform can generate a control moment opposite to the rolling direction
Figure BDA0003197467880000141
In the formula,. DELTA.MxcFor tilting of loaded platformsThe torque is controlled by the control device,
the moment can firstly adjust the mass center of the platform and the goods, and reduce the difference of the vertical loads of two wheels of the axle on the same side, thereby controlling the roll motion of the whole vehicle body and reducing the roll angle. Reasonable roll does not affect the running state of the vehicle, and when the roll angle is too large, the roll danger is caused. Because the intelligent vehicle has no human intervention, the vehicle needs to be maintained within an ideal roll angle range through mass center adjustment. Model tracking error for roll control may be expressed as
e＝φd-φ (3-13)
Establishing a sliding mode function
Figure BDA0003197467880000151
Taking Lyapunov function
Figure BDA0003197467880000152
Then
Figure BDA0003197467880000153
Easy verification
Figure BDA0003197467880000154
Therefore, the system becomes stable.
The load platform, while improving the roll of the vehicle body, also generates a force in the direction opposite to its direction of motion that changes the unsprung mass motion of the vehicle to some extent. If one side of the linear motor is acted upwards actively, the side unsprung mass is acted downwards. If the vehicle body is tilted to the right, i.e. the roll angle is positive
Fx1＝Fx3＝0 (3-18)
Fx2＞0 Fx4＞0 (3-19)
If the vehicle body is tilted to the left, i.e. the roll angle is negative
Fx2＝Fx4＝0 (3-20)
Fx1＞0 Fx3＞0 (3-21)
For simplifying the calculation of the output torque of the linear motors on both sides of the load platform, when Fxi>At 0 time, there are
Figure BDA0003197467880000155
By
Figure BDA0003197467880000161
I.e. Δ MxcThe control torque is output by each linear motor of the load platform.
In addition, the invention also provides a simulation verification method for the active rollover prevention system by utilizing Matlab/Simulink and Carsim. A slope road surface working condition and a whole vehicle model are built in Carsim, a controller model is built in Simulink, and the control effect of the control strategy on the lateral stability of the unmanned transport vehicle under the low-speed slope working condition is checked. The change conditions of parameters such as yaw velocity, mass center slip angle and vehicle body roll angle of the vehicle during active steering, platform control and cooperative control are analyzed, and the simulation result is shown in fig. 3-5.
According to the simulation result, it can be seen that: when the control is not carried out, the yaw velocity fluctuation of the vehicle is obvious after 1s, the mass center slip angle and the vehicle body roll angle can be rapidly increased, the vehicle can turn over in 2.4s, and the simulation is stopped. After the active steering and the load platform are added for control, the roll angle, the yaw velocity and the mass center side slip angle of the vehicle are all controlled, the three control methods can effectively control the vehicle to roll, the combined control effect is most obvious, and 5s simulation can be smoothly completed. When the active steering control is independently adopted, the centroid side deflection angle can be controlled to be 4.2 degrees, and the vehicle body side inclination angle can be stabilized to be 6.2 degrees after being controlled; when the load platform is independently used for control, the centroid side deflection angle can be stabilized at 3.8 degrees, and the vehicle body side inclination angle can be stabilized at 4.3 degrees; when the two are adopted for combined control, the centroid side deflection angle can be controlled to be 3.4 degrees, and the vehicle body side inclination angle can be stabilized to be 3.8 degrees. Compared with the independent control of the active steering and the load platform, the mass center slip angle under the combined control is respectively improved by 19.04 percent and 15.79 percent, and the vehicle body slip angle is respectively improved by 23.3 percent and 16.06 percent. Therefore, the control capability is weaker when the platform control and the active steering are independently adopted, the combined control effect is more stable than other single control, and the ideal control effect can be achieved.
In addition, the invention provides a prototype vehicle-mounted experiment, a test vehicle type is a small intelligent carrier researched and developed by a subject group, and the whole vehicle parameters are shown in table 1. The vehicle is driven by a hub motor, a stepping motor realizes steering, and carries a three-degree-of-freedom load platform, and the load platform takes a push rod motor as a power source and can be controlled to move up and down to realize the adjustment of the position of a mass center. The test is carried out on a section of concrete slope pavement, the pavement adhesion coefficient is 0.6, and the slope gradient included angle is 20 degrees. In consideration of the requirement of low speed in a factory environment, experiments are carried out at the speed of 30km/h, sensor transmission data is used as observed quantity, parameters such as a roll angle, a mass center roll angle and the like of a vehicle body in the running process of the vehicle can be estimated through a Kalman filtering method, and the estimated values can be used for judging the state of the vehicle and controlling the vehicle.
TABLE 1
Figure BDA0003197467880000171
The ideal control curve is compared with the curve obtained by actual control, and the result is shown in fig. 6-8. As can be seen from the figure: under the working condition of an actual slope road surface, the unmanned transport vehicle is subjected to combined control, the fluctuation of a yaw velocity curve is stable at 18 degrees/s, the mass center side slip angle can be stably controlled at 3.2 degrees, the vehicle body side tilt angle can be stably controlled at 3.7 degrees, and the vehicle does not turn on one side. The cooperative controller can well track the ideal centroid slip angle and the vehicle body slip angle, and an expected control effect is achieved. Although the ideal control curve has a certain error with the actual control curve, the error is smaller and is within 8%, and the test result still can prove that the joint control can effectively control parameters of the vehicle such as yaw velocity, mass center slip angle, vehicle body slip angle and the like, so that the risk of vehicle rollover is reduced.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.

Claims (7)

1. An active rollover prevention control method for an unmanned transport vehicle is characterized by comprising the following steps:
establishing an unmanned carrier dynamics model and a two-degree-of-freedom vehicle model to obtain ideal values of the yaw velocity, the mass center slip angle and the vehicle body roll angle of the unmanned carrier;
when the actual values of the yaw angular velocity and the centroid slip angle are larger than ideal values, the vehicle is not in a stable state, an active steering controller is started to control, the front wheel active turning angle delta is obtained based on model prediction and is output to the active steering controller, and an active steering actuator acts; otherwise, the vehicle is considered to be stable, and active control is not carried out;
when the actual value of the roll angle of the vehicle body is larger than the ideal value of the roll angle of the vehicle body, the vehicle is considered to be in an unstable state, and the roll control moment delta M is obtained based on the sliding mode controlxcAnd calculates the actuating force F of the push rod motorxiAnd outputting the calculation result to a load platform controller, and enabling a load platform actuator to act.
2. The automated guided vehicle active rollover prevention control method of claim 1, wherein the automated guided vehicle dynamics model is:
the longitudinal, lateral and yaw motion equations are:
Figure FDA0003197467870000011
where m is the vehicle mass, vxAnd vyRespectively the longitudinal and transverse speeds of the mass center under the vehicle body coordinate system;
Figure FDA0003197467870000021
and
Figure FDA0003197467870000022
acceleration in the longitudinal and transverse directions; γ and
Figure FDA0003197467870000023
respectively yaw angular velocity and yaw angular acceleration, FxiAnd Fyi(i ═ fl, fr, rl, rr) are the tire longitudinal and lateral forces, respectively; i isZThe moment of inertia of the vehicle around the Z axis; lfAnd lrDistances from the center of mass to the front and rear axes, respectively; d1And d2Respectively representing the distance from the equivalent wheel to the left and right wheels; deltafl、δfrRespectively the left and right steering angles of the front wheels; deltarl、δrrThe rear wheel left and right steering angle.
The method for establishing the tire model based on the magic formula comprises the following steps:
Figure FDA0003197467870000024
wherein y (x) represents the lateral or longitudinal force to which the tire is subjected; the independent variable x may represent the slip angle or the longitudinal slip ratio of the tire, respectively; B. c, D, E are fitting coefficients, which in turn are determined from the vertical load and camber angle of the tire, where B is the stiffness factor; c is a curve shape factor; d is a crest factor; and E is a curve curvature factor.
3. The automated guided vehicle active rollover prevention control method of claim 1, wherein the state space equation of the two-degree-of-freedom vehicle model is
Figure FDA0003197467870000025
Wherein the content of the first and second substances,
x＝[β γ]T；u＝δ
Figure FDA0003197467870000026
Figure FDA0003197467870000027
calculating the ideal value beta of the centroid slip angledAnd yaw rate ideal value gammadRespectively as follows:
Figure FDA0003197467870000031
Figure FDA0003197467870000032
wherein mu is a road surface adhesion coefficient; gamma rayrefNominal value of yaw rate calculated for a two-degree-of-freedom reference model, and hence
Figure FDA0003197467870000033
Wherein K is a stability factor,
Figure FDA0003197467870000034
ideal value phi for controlling roll angle of car bodydWith lateral acceleration ayThe relationship of (1) is:
Figure FDA0003197467870000035
4. the automated guided vehicle active rollover prevention control method of claim 1, wherein the active steering control is prioritized over load platform control.
5. The automated guided vehicle active rollover prevention control method according to claim 1, wherein the active steering controller and the load platform controller are electrically and mechanically connected with a cooperative controller, respectively, the cooperative controller obtains the operation state of the automated guided vehicle, calculates to form a new control command, and repeats the command to complete iterative control.
6. The automated guided vehicle active rollover prevention control method of claim 1, wherein the active steering controller uses a model predictive algorithm with yaw rate and centroid yaw angle as system control inputs and front and rear wheel angular rotation as control outputs. The system constraint output is:
y＝C1X (3-6)
in the formula (I), the compound is shown in the specification,
Figure FDA0003197467870000041
X＝[β γ]T；
the state space incremental model for transforming the system continuous state equation into the discrete time system is as follows:
Figure FDA0003197467870000042
in the formula, Ao＝exp(ATs)，
Figure FDA0003197467870000043
Determining an objective function:
Figure FDA0003197467870000044
in the formula rβ,j(k+i)、rγ,j(k + i) are the jth component of the reference output sequence, respectively; gamma-shapedu,iIs a weighted matrix of control inputs, and the system's future P-th predicted input can be expressed as:
Y(k+1|k)＝SxΔx(k)+Iyc(k)+SuΔU(k) (3-9)
Figure FDA0003197467870000045
in the formula Inc×ncIs the identity matrix, nc is the matrix dimension of the control.
The control quantity, the control increment and the output quantity of the system satisfy the following control constraints and output constraints:
Figure FDA0003197467870000046
Figure FDA0003197467870000047
Figure FDA0003197467870000051
the constraint optimization problem is converted into a quadratic programming problem by adopting numerical solution, and the objective function is at the moment k
Figure FDA0003197467870000052
In the formula
Figure FDA0003197467870000053
Solving the control input increment delta U (k) at the moment k, and taking the first step delta U (k) as a control input quantity
Δu(k)＝(Inu×nu 0 … 0)ΔU*(k) (3-11)
In the formula, Δ u (k) is a front wheel steering angle Δ δ to be solved.
7. The automated guided vehicle active rollover prevention control method of claim 1, further comprising the steps of: when the vehicle body rolls, the load platform controller generates a control moment opposite to the rolling direction:
Figure FDA0003197467870000054
in the formula,. DELTA.MxcMoment for roll control of the loaded platform, FxiIs the actuating power of the push rod motor.
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Cited By (4)

* Cited by examiner, † Cited by third party
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CN114859733A (en) * 2022-05-23 2022-08-05 南京林业大学 Differential steering unmanned vehicle trajectory tracking and attitude control method
US11518254B1 (en) * 2021-09-10 2022-12-06 Adata Technology Co., Ltd. Power adjustment system and power adjustment method of autonomous mobile device
CN115973131A (en) * 2023-03-20 2023-04-18 上海伯镭智能科技有限公司 Mine unmanned vehicle rollover prevention method and related device
CN116824113A (en) * 2023-08-29 2023-09-29 四川普鑫物流自动化设备工程有限公司 Four-way vehicle rollover prevention scheduling method and device

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11518254B1 (en) * 2021-09-10 2022-12-06 Adata Technology Co., Ltd. Power adjustment system and power adjustment method of autonomous mobile device
CN114859733A (en) * 2022-05-23 2022-08-05 南京林业大学 Differential steering unmanned vehicle trajectory tracking and attitude control method
CN114859733B (en) * 2022-05-23 2023-03-14 南京林业大学 Differential steering unmanned vehicle trajectory tracking and attitude control method
CN115973131A (en) * 2023-03-20 2023-04-18 上海伯镭智能科技有限公司 Mine unmanned vehicle rollover prevention method and related device
CN116824113A (en) * 2023-08-29 2023-09-29 四川普鑫物流自动化设备工程有限公司 Four-way vehicle rollover prevention scheduling method and device
CN116824113B (en) * 2023-08-29 2023-12-01 四川普鑫物流自动化设备工程有限公司 Four-way vehicle rollover prevention scheduling method and device

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