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Designing Fuzzy Controller for a Class of MIMO Nonlinear Systems Using Hybrid Elite Genetic Algorithm and Tabu Search

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Nature-Inspired Computing for Control Systems

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 40))

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Abstract

This chapter presents a Hybrid Elite Genetic Algorithm and Tabu Search (HEGATS) to design optimal fuzzy controllers for multi input multi output (MIMO) nonlinear system. The principle of the proposed algorithm is to seek the elitism by GA and introduce it in the TS algorithm as initial solution in order to find the best fuzzy rule base of the fuzzy controller. The fuzzy rule base of the fuzzy controller is tuned for optimal control performance using HEGATS by minimizing the mean square error. The proposed algorithm is tested for control of a helicopter model simulator and a double inverted pendulum. Simulation results proved the effectiveness of the proposed algorithm.

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Authors and Affiliations

  1. Faculty of Sciences and Technology, Department of Electronic, Jijel University, Jijel, Algeria

    Nesrine Talbi

  2. Faculty of Engineering, Mentoury University, Constantine, Algeria

    Khaled Belarbi

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  1. Nesrine Talbi
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  2. Khaled Belarbi
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Correspondence to Nesrine Talbi .

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Editors and Affiliations

  1. Faculty of Engineering, Universidad Panamericana, Mexico City, Mexico

    Hiram Eredín Ponce Espinosa

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Talbi, N., Belarbi, K. (2016). Designing Fuzzy Controller for a Class of MIMO Nonlinear Systems Using Hybrid Elite Genetic Algorithm and Tabu Search. In: Espinosa, H. (eds) Nature-Inspired Computing for Control Systems. Studies in Systems, Decision and Control, vol 40. Springer, Cham. https://doi.org/10.1007/978-3-319-26230-7_5

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  • DOI: https://doi.org/10.1007/978-3-319-26230-7_5

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