Decentralized adaptive super-twisting control for modular and reconfigurable robots with uncertain environment contact

Abstract

This paper presents a decentralized adaptive super-twisting control method for modular and reconfigurable robots (MRRs) with uncertain environment contact. Unlike conventional methods that rely on robot-environment contact model or force/torque sensing, this paper addresses the problem of controlling MRRs in contact with uncertain environment that using only local dynamic information of each joint module. The dynamic model of MRR is formulated as a synthesis of interconnected subsystems. Based on the integral sliding mode control (ISMC) technique and the adaptive super-twisting algorithm (ASTA), the decentralized controller is designed to compensate the model uncertainty in which the up-bound is unknown. The stability of the MRR system is proved by using the Lyapunov theory. At last, simulations are conducted for 2-DOF MRRs with different configurations under the situations of dynamic contact and collision to investigate the advantage of the proposed approach.