Fuzzy Optimal Control for Robot Manipulators

Abstract

A robust FC-LQR for the control of a robotic system has been designed. The main idea is to design a supervisory fuzzy controller capable to adjust the controller parameters in order to obtain the desired axes positions under variations of the robot parameters and payload variations. The motivation behind this scheme is to combine the best features of fuzzy control and that of the optimal LQR. Both the controlled system and the fuzzy controller are represented by the affine T-S fuzzy model taking into consideration the effect of the constant term. In the case of fuzzy control, the fuzzy system is resulted from blending all the sub-systems. The blending of the independent term of each rule will no longer be a constant but a function of the variables of the system and thus affects the dynamics of the resultant system. A necessary condition has been added to deal with the independent term. In this chapter, we have demonstrated that the LQR, can be made more appropriate for actual implementation by introduction of fuzzy rules. The results obtained show a robust and stable behavior when the system is subjected to various initial conditions, moment of inertia and to disturbances.