Generalized BELBIC

摘要

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.