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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For more simplicity, the notation of Ai and Oi applied in some references is not used in this presentation.
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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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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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DOI: https://doi.org/10.1007/s00521-018-3352-1