Path-tracking of mobile robot using feedback-aided P-type iterative learning control against initial state error

Abstract

In this paper, we present an iterative learning control (ILC) frameworks for robust path-tracking problem of nonholonomic mobile robots in the presence of initial shifts. The major difficulties are owning to the simultaneous existence of state disturbances and biased initial state in the mobile robot kinematic system. To design ILC strategy for such problem, a new ILC scheme is proposed as a combination of an initial rectifying term and a feedback-aided P-type learning algorithm. Sufficient conditions of convergence of this approach are given and the global convergence is proved. Simulation results also verify the effectiveness of the proposed scheme.