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Generalized BELBIC

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Abstract

Brain emotional learning-based intelligent controller (BELBIC) is a developed class of model-free learning controllers (MFC), which has been inspired from the MFC mechanism of human brain. BELBIC suffers from a major drawback that is related to the learning module. The learning module of BELBIC is not universal approximator and cannot be used for model-based applications. In this paper, a generalized BELBIC (G-BELBIC) is proposed which is inspired from a model-based learning controller (MBC) of brain. In contrast to BELBIC, proposed G-BELBIC applies a nonlinear learning module with universal approximation (UA) property and can be applicable in various MBC engineering applications. The UA proof and stability analysis of G-BELBIC are presented, and the novel controller is tested on single-link robot arm and continuous stirred tank reactor as case studies. Comparative results indicate the superiority of the approach in terms of higher control accuracy and robustness property.

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Notes

  1. For more simplicity, the notation of Ai and Oi applied in some references is not used in this presentation.

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Acknowledgements

We would like to thank independent reviewers for their excellent feedback on the paper. We also acknowledge the support of Azad University of Torbat-e Jam and Payam-e Noor University.

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Authors and Affiliations

  1. Department of Computer Engineering, Torbat-e Jam Branch, Islamic Azad University, Torbat-e Jam, Iran

    Ehsan Lotfi

  2. Department of Computer Engineering and Information Technology, Payam-e Noor University, P.O. BOX 19395-3697, Tehran, Iran

    Abbas Ali Rezaee

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  1. Ehsan Lotfi
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Correspondence to Ehsan Lotfi.

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Lotfi, E., Rezaee, A.A. Generalized BELBIC. Neural Comput & Applic 31, 4367–4383 (2019). https://doi.org/10.1007/s00521-018-3352-1

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