Velocity tracking control of wheeled mobile robots by fuzzy adaptive iterative learning control

摘要

In this paper, a fuzzy adaptive iterative learning control (FAILC) strategy is proposed to resolve the trajectory tracking problem of wheeled mobile robots (WMR) based on the dynamic model of WMR and its actuator. In the previous study of WMR trajectory tracking, ILC was usually applied to the WMR kinematical model with the assumption that desired velocity can be tracked immediately. However, this assumption can not be realized in the real world at all. The kinematics model and dynamic model of WMR are deduced in this paper, and a novel iterative learning controller which contains a fuzzy iterative learning component and a feedback component is presented. The controller can work on MIMO systems with variable initial errors. In order to analysis the convergence of the algorithm, the method of Lyapunov-like approach which shows the adjustable parameters of fuzzy system are bounded and tracking errors can converge to zero after initial time as iterative times goes to infinity. Simulation results show the effectiveness of FAILC in the WMR trajectory tracking problem.