Research On Tracking Control Method Of Unmanned Vehicle Based On Sliding Mode Variable Structure

With the rapid development of social economy,the popularization of 5G and the advancement of Internet technology have prompted people to put forward higher requirements for safe driving of vehicles in the future.And the technology of unmanned vehicles has undoubtedly become a hot issue of scientific research in recent years.Among them,unmanned vehicle trajectory tracking is the most important part of unmanned driving technology,and lateral control is a difficult problem in its research.This paper uses unmanned vehicles as the research carrier to study the two situations of trajectory tracking lateral control and trajectory tracking lateral control under limited input conditions.The specific contents include:(1)Vehicle lateral dynamics modelingBased on Newton’s second law,through the force analysis of the vehicle in the process of changing lanes and turning,neglecting the influence of factors such as air resistance and longitudinal speed on the lateral control,a dynamic model is established to provide a theoretical basis for the subsequent system control.(2)Research on unmanned vehicle trajectory tracking control method based on sliding mode extended state observerIn order to solve the problem of vehicle trajectory tracking,based on the established two-degree-of-freedom steering dynamics model of unmanned vehicles,the steering wheel angle is used as the control variable,and the lateral error displacement is the output.The external disturbance and the unmodeled part of the system are regarded as Compound disturbance,the trajectory tracking control algorithm based on non-singular terminal sliding mode is studied.Aiming at the unknown problem of compound disturbance,a trajectory tracking control algorithm based on the extended state observer is studied.(3)Research on the trajectory tracking control method of unmanned vehicles with limited inputWhen the vehicle is running under actual working conditions,the input will be limited due to factors such as the physical limitations of the actuator.Among them,saturated input is also common in non-linear systems.Based on the established dynamic model,this chapter uses hyperbolic tangent function instead of saturation function to study the unmanned vehicle trajectory tracking control method based on the backstepping method under the condition of limited input.At the same time,the neural network is used to track and estimate the combined disturbance to form Compensation control of the system improves the response effect of the system.By establishing a simulation platform on Matlab/Simulink,simulation experiments are carried out for the above two situations respectively.The simulation experiment results show that the effect of the sliding mode control algorithm added with the observer is better than the former,and the control effect is obvious.In the case of limited input,after the use of neural network to form compensation control for the backstepping method,the error gradually decreases,the system tends to be stable,and the control goal is achieved.