On The Development Of A Fuzzy Model-based Controller For Robotic Manipulators

Abstract

We proposed a fuzzy model for a robotic manipulator and used such a model to generate suitable control signals for accurate trajectory tracking application. Each of the nonlinear parameters in the manipulator dynamic equation was modeled by a set of fuzzy rules where the unknown parameters were predicted by use of a least-square identification algorithm and an optimum search algorithm. The computed torque method was then applied to design the controller, which comprises a model-based portion to compensate the effect of nonlinear dynamics and a servo portion to control overall dynamics. Computer simulation results have shown that the proposed controller indeed can improve the system performance as the position accuracy is much better than that of conventional PD control, Simulation results have also shown that the proposed controller is xry robust.