Improvement of fuzzy logic robot controllers using inverse entropy based T-operations

In this paper a theoretical approach to performance improvement of fuzzy logic robot controllers is presented. The approach is based on two new sets of T-operations introduced by the authors. The T-norms and T-conorms are defined as minimum and maximum entropy operations. Simulation has been carried out so as to compare the effects of the new and the conventional T-operators in case of a 4 DOF rigid-link flexible-joint SCARA type robot. It is concluded that by fixing the other parameters of the controller certain sets of T-operations can improve the performance of the controller