Approximate Optimal Sliding Mode Tracking Control for Modular Reconfigurable Robots Based on Critic-only Structure

Abstract

In this paper, an approximate optimal sliding mode tracking control (SMTC) strategy is investigated for modular reconfigurable robots (MRRs) through critic-only structure-based adaptive dynamic programming (ADP) scheme. The SMTC is achieved by three parts, i.e., the optimal control of the nominal system, the sliding mode-based iterative control and an adaptive robust term. The sliding mode-based iterative controller suppresses the error caused by the trajectory tracking, and the adaptive robust term is employed to ensure the reachable condition of sliding mode surface. By solving the Hamilton-Jacobi-Bellman equation with the critic neural network only, the sliding mode-based iterative control can be derived. The SMTC strategy can drive the MRR to present achieve a faster control action based on the approximate optimal control. The closed-loop MRR system is guaranteed to be asymptotically stable under the developed SMTC policy. At last, the effectiveness of the presented strategy was validated via the comparative simulation.