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Taylor & Francis
Systems Science & Control Engineering
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This paper presents a novel fuzzy control design of discrete-time nonlinear systems with multiple performance criteria. The purpose behind this work is to improve the traditional fuzzy controller performance to satisfy several performance criteria simultaneously to secure quadratic optimality with an inherent stability property together with a dissipativity type of disturbance reduction. The Takagi–Sugeno-type fuzzy model is used in our control system design. By solving a linear matrix inequality at each time step, the optimal control solution can be found to satisfy mixed performance criteria. The effectiveness of the proposed technique is demonstrated by simulation of the control of the inverted pendulum system on a cart.
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Wang, Xin and Yaz, Edwin E., "Robust Multi-Criteria Optimal Fuzzy Control of Discrete-Time Nonlinear Systems" (2016). Electrical and Computer Engineering Faculty Research and Publications. 271.