Compensatory neuro-fuzzy control of bilateral teleoperation system

In this paper a new adaptive controller using compensatory neuro-fuzzy is presented to guarantee the position and force tracking performance between the master and the slave manipulators. The controller proposed, combines on one hand neural networks (NNs) with fuzzy logic for dynamical compensation of both structured and unstructured uncertainties, and on the other hand optimizes dynamically the adaptive fuzzy reasoning for acceleration the asymptotically convergence to zero the trajectory tracking error between the master and the slave robots. The validity of the proposed control scheme is demonstrated with a 1-DOF master/slave system. Finally the experimental results are performed to show that the proposed control method works well with robustness, so as to confirm the effectiveness of the proposed controllers.