Robust control and identification of robots: theory and applications

Abstract

This paper introduces innovative frameworks in nonlinear identification and robust control of robots. In order to model and control the manipulators, it is necessary to develop mathematical models and identify the unknown parameters. The paper outlines new straightforward identification and control guidelines. The identification and robust control schemes are developed and treated based on the Lyapunov theory. These techniques are feasible and efficient. An illustrative example is considered to investigate the efficiency of the reported identification algorithm and control procedure for an electromechanical robotic system with permanent-magnet DC motor. Experiments were performed to validate the outlined identification and control procedures. The experimental results demonstrate the efficiency of the identification methodology and illustrate the improved dynamic performance of the robot with robust controller.