This paper develops a method for decentralized neural network control design with continuous sliding modes in which robustness is inherent. Neural network control is formulated to become a class of ...variable structure system control. Sliding modes are used to determine best values for parameters in neural network learning rules, thereby robustness in learning control can be improved. Derived equations of decetralized adaptive neural network sliding-mode controller (DNNSMC) were verified on a real direct-drive 3. D.O.F. PUMA mechanism. The new decentralized neural network continuous sliding-mode controller was successfully testedfor adaptation capability of the algorithm for sudden changes in the manipulator dynamics (load).
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