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Takagi–Sugeno fuzzy generalized predictive control for a class of nonlinear systems

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Abstract

In this paper, a fuzzy generalized predictive control method for a class of nonlinear systems is studied. Firstly, based on the Takagi–Sugeno fuzzy model, a class of nonlinear systems and its fuzzy predictive model are presented. Next, based on the controlled autoregressive integrating moving average model transformed by the Takagi–Sugeno fuzzy model of the nonlinear systems, a novel fuzzy generalized predictive control method is proposed for the nonlinear systems, which combines fuzzy techniques and generalized predictive control theory. Lastly, two typical examples, the three-dimensional Lorenz nonlinear system and the four-dimensional Chen nonlinear system, are employed to verify the effectiveness and superiority of the proposed scheme. It also provides a reference for relevant control of nonlinear even chaotic systems.

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Acknowledgements

This work was supported by the scientific research foundation of the National Natural Science Foundation (Numbers 51509210 and 51479173), Shaanxi province science and technology plan (No. 2016KTZDNY-01-01), the Science and Technology Project of Shaanxi Provincial Water Resources Department (No. 2015slkj-11), the International Cooperation Project of Ministry of Science and Technology (No. 2014DFG72150) and the 111 Project from the Ministry of Education of China (No. B12007).

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Authors and Affiliations

  1. Department of Electrical Engineering, Institute of Water Resources and Hydropower Research, Northwest A&F University, Yangling, 712100, Shaanxi, China

    Ke Shi, Bin Wang, Lan Yang, Shikang Jian & Jikai Bi

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  1. Ke Shi
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  2. Bin Wang
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  3. Lan Yang
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Correspondence to Bin Wang.

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Shi, K., Wang, B., Yang, L. et al. Takagi–Sugeno fuzzy generalized predictive control for a class of nonlinear systems. Nonlinear Dyn 89, 169–177 (2017). https://doi.org/10.1007/s11071-017-3443-z

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  • DOI: https://doi.org/10.1007/s11071-017-3443-z

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