Extended State Observer-Based Motion Control of Robot Manipulators in Presence of Uncertainties and Disturbances

Robotic manipulators are complex mechanical systems that exhibit highly nonlinear dynamics and subject to various forms of disturbances such as friction, external forces and other unmodelled dynamics. Mathematical models representing robot dynamics are extensively used for design, simulation and control purposes, and can be derived through analytical and experimental methods. Dynamic behaviours predicted by mathematical models often deviate from the observed dynamics of robot manipulators because of external disturbances, parametric uncertainties, and unmodelled dynamics. The observer-based control that eliminates the need for highly accurate system modelling is an appealing approach for robot control. This paper introduces an extended state observer-based structure that can be either utilized as a stand-alone controller or implemented within a model-based adaptive control scheme. The proposed control scheme allows the implementation of extended state observers independently of the availability and quality of the dynamic model. The stability of the proposed controllers in presence of model uncertainties and generalized disturbances is investigated through the Lyapunov analysis. The experiments performed on a six-DoF industrial robot validate the theoretical stability results. Evaluation of performances of the proposed controllers in various operating conditions are presented in a comparative manner. Experimental results show that the extended state observer-based controller outperforms the adaptive controller in trajectory tracking performances.