Research On Optimal Control Of Vehicle Stability System Based On Feedback Linearization

In recent years,the frequent occurrence of traffic accidents has led to a large number of casualties and property losses,which makes people aware of the importance of vehicle active safety system.As a vehicle stability control system,the active safety system can intervene in the vehicle control before the danger occurs,thus avoiding the occurrence of rollover,side slip and other out of control phenomenon,effectively improve the stability of vehicle operation.In this paper,the controller is designed for the yaw and roll motion of the vehicle with the tire longitudinal force,yaw rate,roll angle and other state variables.Finally,the effect of the controller is verified.First of all,the eight-degree-of-freedom vehicle model considering the crosswind disturbance is established,and the model is linearly processed by the method of state feedback in the nonlinear feedback theory of multi-input and multi-output system.is established,and the model is linearized by the State Feedback Method in Nonlinear Feedback Theory of Multiple Input Multiple Output System.In order to achieve full state feedback,it is necessary to design and select the output of the system.The method of differential homeomorphism is used to transform the coordinates,and the state feedback can be introduced to convert the original nonlinear system into a linear system.Then,the vehicle stability controller is designed.Considering that there is no interference decoupling in the process of linearization,there is still interference in the system,so the design of the robust controller can keep the vehicle stable under the external disturbance.The output of the vehicle stabilization controller is the resultant force(moment)to maintain the stability of the vehicle.According to the analysis of the running characteristics of the vehicle,it can be seen that the resultant force(moment)can't be directly controlled in the actual vehicle control system.In this paper,in order to facilitate the analysis,it can be regarded as the virtual intermediate quantity,which can't be directly applied to the actuator of the vehicle,so the next thing to do is transform the virtual intermediate into an amount that can be applied to the wheel actuator.In order to make the resultant force(moment)can be applied to the wheel of the implementing agencies,it is necessary to convert it into the form of tire force,and then force and torque conversion before acting on the actuator,the process is typical Redundant control,this paper adopts the method of control allocation to solve this problem.Because the tire longitudinal force is not only affected by the adhesion of the road surface,but also by the actuator constraints,the control allocation problem can be described as a constrained optimization problem.It can be seen from the wheel dynamics formula that the tire longitudinal force is the main reason of vehicle movement,which can directly affect the actuator of the wheel,and the tire lateral force is due to the vehicle tires deformation,does not have an effect on the implementing agency.Therefore,this article only to achieve the force(moment)to the tire longitudinal force distribution,and the tire lateral force can be obtained according to the corresponding relationship between the tire cornering characteristics.In this paper,the corresponding optimization objective function is selected,and the distribution problem is transformed into a quadratic programming problem,which is based on the constraint of friction circle and actuator.There are many ways to solve the quadratic programming.In this paper,the active set method is used to obtain the tire longitudinal force.Finally,in order to verify the effect of the designed controller,this paper will build a eight degree of freedom vehicle model with the designed controller in Matlab/Simulink,and verify the control effect of the controller under different operating conditions.In addition,AMESim and Simulink will be co-simulation,based on the fifteen degree of freedom vehicle model provided by AMESim to verify the operation of the entire control system.