Model-free Adaptive Control Of Steer-by-Wire System

As a means of transportation for daily travel,the driving comfort and driving safety of vehicles are important indicators to evaluate the performance of vehicles.The steering system is a key component of the vehicle system,and the stability control of the lateral movement of the vehicle is very important to the driving safety of the car.The steering-by-wire(SBW)system is a new type of vehicle steering system.This system gets rid of the constraints of mechanical steering system components and uses electronic control technology to achieve the steering control of the car.The steer-by-wire control strategy plays a decisive role in the steering performance of SBW vehicles.This paper takes the steer-by-wire system as the research object,and conducts the following research on its control strategy.This paper first elaborates the structure of the steer-by-wire system and its related performance characteristics.Based on the analysis of the working principle of the system,a dynamic model of the steer-by-wire system is established,and the whole vehicle model of the steer-by-wire is completed through the Car Sim platform.This paper studies and analyzes the model-free adaptive control(MFAC)algorithm,proposes a method for system tuning of MFAC key parameters using intelligent swarm optimization algorithm,and designs an MFAC controller based on immune particle swarm algorithm.It effectively solves the problem that the key parameters in the MFAC algorithm are mostly set empirically and therefore lack a system setting method.Secondly,this paper studies the mechanical steering characteristics of traditional automobiles,and introduces the concept of ideal variable transmission ratio by analyzing the influence of auto steady-state steering gain on vehicle lateral control.On this basis,in order to avoid problems such as "unmodeled dynamics" in practical applications of SBW vehicles based on the ideal variable transmission ratio control strategy,fully utilize the input and output data of the vehicle steering system,and design a model-free adaptive SBW control scheme based on improved control rate.The influence of the relevant parameters in the improved model-free adaptive controller on the handling of the SBW vehicle is studied,and the stability of the SBW system based on IMFAC is analyzed.The simulation test verifies the effectiveness of the designed control strategy,and the vehicle steering characteristics are effectively improved.Finally,on the basis of the IMFAC-based SBW vehicle system,considering the driver’s behavior characteristics,a preview optimal curvature fuzzy PID driver model is established,and then the SBW car “driver-vehicle-road” closed-loop system based on the driver model and IMFAC is constructed.Select typical vehicle test conditions,and combine the driver’s state feedback information to simulate the IMFAC-based SBW vehicle closed-loop system.The experimental results show that the SBW driver-vehicle-road closed-loop system based on the driver model and IMFAC realizes the steering operation more accurately,and effectively improves the steering stability and driving safety of the vehicle.