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Descripción
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| New efficient approaches have been presented to improve the local and global approximation of TS fuzzy model. The main problem of TS identification method is that it can not be applied when the membership functions are overlapped by pairs. This restricts the use of the TS method because this type of membership function has been widely used during the last two decades in the stability, controller design and are popular in industrial control applications. The approaches developed here can be considered as a generalized version of TS method with optimized performance in approximating nonlinear functions. We propose a non iterative method through a weighting of parameters approach and an iterative algorithm by applying the extended Kalman filter, based on the same idea of parameters? weighting. We show that the Kalman filter is an effective tool in the identification of TS fuzzy model. An Illustrative example of an inverted pendulum has been chosen to evaluate the robustness and remarkable performance of the proposed method and the high accuracy obtained in approximating nonlinear and unstable systems locally and globally in comparison with the original TS model. Simulation results have shown the potential, simplicity and generality of the algorithm. | |
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Internacional
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Si |
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DOI
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DOI: 10.2991/978-94-6239-082-9_1 |
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Edición del Libro
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Editorial del Libro
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Atlantis (Atlantis Series on Computational Intelligent Systems) |
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ISBN
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978-94-6239-082-9 |
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Serie
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Atlantis (Atlantis Series on Computational Intelligent Systems) |
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Título del Libro
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Fuzzy Modeling and Control: Theory and Applications |
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