Proceedings of the 51st Annual Meeting of the ISSS - 2007, Tokyo, Japan, Papers: 51st Annual Meeting

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Fuzzy Neural Network Based Intelligent Robust Control Systems

yoshishige sato


The intelligent robust controls such as a neural network based control for mechatoronic positioning servo systems have been researched actively in recent years because the mechanism design could not cope with the advanced requirements. This paper proposes a novel fuzzy-neural network based intelligent robust control for the mechatoronic positioning servo systems that have nonlinear characteristics such as friction, backlash, variations of load and system parameters, and unknown disturbances. Computational simulation results and experimental results for one degree-of-freedom positioning system are shown to confirm the validity of the proposed controller.

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