Modeling for Fuzzy Logic Control of Deformable Manipulators

Abstract

In this paper a control law which consists of a fuzzy logic controller plus a nonlinear effects negotiator for a flexible robot manipulator is presented. The nonlinear effects negotiator is used to enhance the control system's ability in dealing with the uncertainty of the mathematical model. The control algorithm is simple and easy to tune as opposed to conventional control law which requires time consuming gains selections. To obtain fuzzy control rules, an error response plane method is proposed. This method is mainly based on mathematical reasoning. In addition, the degree of overlap of membership functions for fuzzy rules is investigated. The optimal overlap of membership functions that results in the best performance of the robot is obtained. Moreover, the nonlinear effects of a typical robot motion, such as friction, backlash and external disturbances, are simulated by a sine function with randonmized amplitude and phase in the motion simulation. The results show that the proposed control scheme is robust in that it can cope with modeling uncertainty, nonlinearity, and disturbances due to payload variations simultaneously.