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Fuzzy Modeling Strategy for Control of Nonlinear Dynamical Systems

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Fuzzy Systems and Knowledge Discovery (FSKD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3613))

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Abstract

This paper presents a novel fuzzy modeling strategy using the hybrid algorithm EPPSO based on the combination of Evolutionary Programming (EP) and Particle Swarm Optimization (PSO) for control of nonlinear dynamical systems. The EPPSO is used to automatically design fuzzy controllers for nonlinear dynamical systems. In the simulation part, one multi-input multi-output (MIMO) plant control problem is performed. The performance of the suggested method is compared to that of EP, PSO and HGAPSO in the fuzzy controllers design. Simulation results demonstrate the superiority of the proposed method.

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References

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Author information

Authors and Affiliations

  1. College of Electrical Engineering, National Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, 310027, Zhejiang, China

    Bin Ye, Chengzhi Zhu, Chuangxin Guo & Yijia Cao

Authors
  1. Bin Ye
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  2. Chengzhi Zhu
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  3. Chuangxin Guo
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  4. Yijia Cao
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

    Yaochu Jin

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© 2005 Springer-Verlag Berlin Heidelberg

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Ye, B., Zhu, C., Guo, C., Cao, Y. (2005). Fuzzy Modeling Strategy for Control of Nonlinear Dynamical Systems. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_110

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  • DOI: https://doi.org/10.1007/11539506_110

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28312-6

  • Online ISBN: 978-3-540-31830-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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