On-line adaptive fuzzy switching controller for SCARA robot

Abstract

This paper presents the design, development and implementation of a new on-line adaptive MIMO switching controller (FSC) for real-time tracking control of an industrial SCARA robot. Two link SCARA robot is a nonlinear plant. The fuzzy control is based on the Takagi-Sugeno's type fuzzy architecture model with on-line self-tuning so that both the desired transient and steady state responses can be achieved at different operation conditions. The online real-time self-tuning is based on the gradient steepest descent method, which tunes the inputs and outputs scaling factors of the proposed fuzzy controller. This controller simplifies the Real-time control implementation and improves the control performance. Real-time controller is implemented in Matlab's xPC Real-time workshop environment. SCARA robot system identification was accomplished by using Auto Regression with external input method (ARX) to determine the discrete time transfer function necessary for the controller design. Comparison between the self-tuned fuzzy switching controller and fixed fuzzy switching controller was made to evaluate the real time tuning's performance. The comparison is based on the tracking ability subjected to large payload. Based on the real time results the performance of fuzzy switching controller with this tuning strategy was found to be superior and it matches favourably to the operating conditions.