Design And Implementation Of Four-wheel Independent Drive And Steering Robot Platform Control System

With the development of robotics,mobile robots are becoming more and more widely used in many occasions such as industrial,military,hazardous environment or service industry.This puts strict requirements on the stability and flexibility of the robot platform.In addition,when the mobile robot is along When the planned trajectory is running,it is expected to track the trajectory well.Therefore,mobile robots are required to have good mechanical structure and control strategies.In order to improve the existing mechanical parts of the four-wheeled robot,the space is large,and the turning space is limited.A four-wheel independent driving robot platform control system is designed.The main research work is as follows:(1)Design the overall scheme of the robot platform control system,establish the dynamic model of the platform,complete the software and hardware design of the robot platform control system,and design a fuzzy neural network PID controller based on the analysis of the conventional PID control performance;The control accuracy and operational stability of the robot platform are used to filter the steering signal of the platform.In order to avoid the limitation of adjusting the weight by the gradient descent method,the weight adjustment of the fuzzy neural network algorithm is carried out by using Lyapunov theory.Improve.Through the fuzzy neural network algorithm,the simulation results of the radial basis network algorithm and the traditional PID control algorithm are compared.It is concluded that the control algorithm used in this paper has the advantages of small overshoot,fast stability and high control precision.(2)For the problem that the running stability of the robot platform is affected by the speed and the steering,and the speed stability is related to the acceleration and deceleration processing of the speed,the S-curve algorithm is used to process the speed of the robot platform,before and after the S-curve algorithm is processed.The simulation results and the control accuracy of the robot platform verify that theS-curve algorithm can improve the stability of the platform and reduce the impact of the robot platform under acceleration and deceleration.(3)Using the built-in physical platform,the results of optimizing PID parameters based on fuzzy neural network algorithm are applied to the platform,and compared with the trajectory effect of traditional PID algorithm,it is verified that the control effect of fuzzy neural network PID algorithm is better.Traditional PID control.