Type-2 Fuzzy Neural Network Synchronization of Teleoperation Systems with Delay and Uncertainties

This paper concerns the problem of uncertainties and time-delays in teleoperation systems. Human operators at the master side and partially unknown environments in the remote workspace introduces extreme uncertainties to the teleoperation process. Outstanding capability of type-2 fuzzy methodologies in dealing with uncertainties motivated us to apply this method in the design of a controller for teleoperation systems. Moreover, employing artificial neural networks, we propose an online learning approach that adaptively tunes the type-2 fuzzy-based control strategy. Asymptotic convergence of the learning methodology, and subsequently, the stability of the system is verified by Lyapunov-Krasovskii approach. Furthermore, experimental evaluations justify the performance of the developed control scheme.

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