High-order Model-free Adaptive Iterative Learning Control for Velocity Tracking of Wheeled Mobile Robots

Abstract

In this paper, a data-driven high-order model-free adaptive iterative learning control (HMFAILC) is developed by a wheeled mobile robots (WMR) for trajectory tracking in the repetitive systems. The design and analysis of the controller only uses the I/O of the system and in the absence of any explicit model information. Control performance is improved by using higher-order learning control methods to obtain more control information in the iterative process. The control performance of the control scheme is proved by mathematical analysis and simulation.