Robustness Analysis of Iterative Learning Control for a Class of Mobile Robot Systems With Channel Noise

Abstract

This paper considers the robust tracking problem of a unicycle type mobile robot, which is controlled remotely by an iterative learning controller over the wireless network. First, taking the effect of the channel noise into account, the nonlinear system model is formulated to describe the mobile robot controlled by a differential-type iterative learning controller. After that, the relation between the input error at the controller side and the channel noise is derived. Based on this relation, the norm of output error is derived and analyzed theoretically. The analysis reveals that the effect of channel noise is accumulated in both the iteration and time domains, and is ruled simultaneously by the sampling time in the nonlinear function of the system. Due to the sampling time that is far less than one, the accumulated effect of channel noise on the robustness of the system is suppressed significantly by the sampling time, which means that the mobile robot can track the desired trajectory without any processing. Finally, the simulation results are given to corroborate the theoretical analysis.