J.-P. Su, T.-E. Lee, and K.-W. Yu (Taiwan)
two-input single-output fuzzy controller, Genetic Algo rithm (GA), alpha-belta filter, sliding mode control.
Given a nonlinear tracking control problem, we define two generalized errors as inputs to form a novel two-input single-output fuzzy logic controller. For practical consider ation, a GA-based alpha-beta filter is presented in front of the fuzzy controller to suppress noise and obtain smooth in put signals. By incorporating this controller into a sliding mode control framework, we derived a simple and useful stable feedback control scheme. This control scheme is ca pable of improving significantly the tracking performance. A force-adaptive robot effector acting on various profiles of surfaces has been used as a simulative example to demon strate its effectiveness. These results strongly suggest the proposed control scheme is efficent and easy to implement.
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