Robust Adaptive Control of Manipulators in the Task Space by Dynamical Partitioning Approach

Abstract

In this paper, robust adaptive control of manipulators in the task space is developed based on dynamical partitioning approach. This novel approach of manipulators tracking in the task space can overcome on both parametric uncertainties and unstructured uncertainties such as friction, disturbance and un-modeled dynamics using adaptive and robust capabilities, respectively. The feedback linearization method is applied to cancel certain nonlinearities by using of dynamical partitioning approach. The proposed control scheme is more robust than model based adaptive control. The global asymptotic stability of the closed loop system is verified by Lyapunov method. To show the performance of the control system, a case of study is carried out on a two-links elbow robot by simulations.