Position control of a robot manipulator using continuous gain scheduling

Abstract

A new approach for designing controllers for nonlinear systems in general and for robot manipulators in particular is proposed. The proposed approach is based on fitting a set of gains to continuous functions of the states of the system using Taylor series expansion. The gains are obtained using LQR design on a fine set of linearized versions of the system. This scheme is systematic and can be utilized in any nonlinear autonomous system. Unlike the approaches based on the conventional gain scheduling, our approach imposes no limitation on the speed of variation in the system. Consequently, the stability of the proposed system is better than that of the classical gain scheduling. Simulation results prove the effectiveness of the proposed approach and the robustness of the controller in the presence of significant actuators' noise.