Intelligent Control For Mobile Robot Path Tracking

Mobile robot belongs to nonholonomic constraint system, and has been an important subject of Automation area in research and development, and the path tracking is an important technology of mobile robot. So the path following control research is of great practical significance. On the basis of summarizing and reference extensive literature, arounding the path tracking control problems of mobile robot, using the fuzzy control algorithm and improved PSO algorithm realize the speed and steering control of the path tracking.Firstly, on the base of deducing the mathematical model of mobile robot and mastering the principle of fuzzy algorithm, design the path tracking speed controller of mobile robot based on the theory of fuzzy algorithm and the preaiming theory. And combine with the programmable logic devices PFGA realize the speed control of mobile robot path tracking. In the speed control, mainly by simulating the artificially driving behavior, make the controller rarely dependent on the accurate mathematical model.Secondly, the mobile robot is drove by rear-wheel which has some characteristics such as nonholonomic constraint, complex model and nonlinear and time variability of steering system. In order to realize the intelligent control of system, an intelligent PID path tracking method is proposed, acquire on-line tuning information of PID parameters and the self-tuning of controller parameters based on the improved particle swarm optimization algorithm. The result indicates that the mobile robot is controlled by the proposed approach can follow various reference paths accurately and robustly. Compares to the traditional PSO method, the proposed approach possesses the advantages of high precise, great adaptability and robustness.Finally, make the simulation experiment of mobile robot speed control by the QUARTUSⅡsoftware. Use the MATLAB software simulate mobile robot tracking reference path based on the improved PSO algorithm, and compare with mobile robot tracking reference path based on the PSO algorithm. Validate the feasibility and superiority of improved PSO algorithm in mobile robot path tracking.