| As an intelligent steering system,the steer-by-wire system has changed the traditional mechanical structure of automobiles and is the inevitable direction of the development of modern automobile steering systems.The position accuracy of the steering motor of the autonomous driving electric steer-by-wire system and the stability of the vehicle are of great significance to the reliability and safety of autonomous vehicles.Based on the dual-steering actuator steer-by-wire system,this paper studies the position tracking accuracy,position following speed and vehicle stability of the actuator motor of the automatic driving steer-by-wire system.The research to be carried out in this paper is as follows:(1)Based on the autonomous driving structure and working principle of the bywire steering system of the dual-steering actuator motor,determine the dynamic equation of the steer-by-wire system and the mathematical formula of the permanent magnet synchronous motor,use Simulink to build the simulation model of permanent magnet synchronous motor and by-wire steering system,input the output front wheel angle into the vehicle model of carsim without steering system,and build a simulation platform for the control strategy designed later.(2)Based on the by-wire steering system of the dual-steering actuator motor,the position-loop control strategy of the steering actuator motor is designed.In this paper,the permanent magnet synchronous motor is used as the steering execution motor,the position loop control of the permanent magnet synchronous motor is designed by the fuzzy self-disturbance rejection algorithm,the three parameters in the self-disturbance rejection expansion observer are fuzzy adaptive adjustment,the algorithm model and SVPWM are built using matlab/simulink,and the sinusoidal function and square wave function are used as angle input to simulate the designed algorithm.Therefore,the effectiveness of the control strategy on the position following response speed and accuracy of PMSM and the reduction of the influence of load interference are verified.(3)Based on the research of vehicles with automatic driving dual-steering motor steer-by-wire system,an RBF neural network AMC control algorithm is designed to realize the decoupling control of the yaw angle velocity and centroid declination,and the RBF neural network adaptively adjusts the three parameters in the auto-disturbance rejection expansion observer,and determines the ideal yaw angle speed and ideal centroid declination angle through the two-degree-of-freedom vehicle reference model.Build a simulation model of vehicle stability.Finally,the simulation analysis of high adhesion pavement coefficient and low adhesion pavement coefficient is carried out by serpentine working condition and angular step working condition,Therefore,the effectiveness of the proposed RBF neural network disturbance rejection stability controller based on the comprehensive feedback of yaw angle velocity and centroid declination angle is verified for improving the stability and driving safety of vehicles. |
