28th Iranian Conference on Electrical Engineering , 2020-08-04

Title : ( Adaptive Emotional Neuro Control for a Class of Uncertain Affine Nonlinear Systems )

Authors: Fahimeh Baghbani , Mohammad Reza Akbarzadeh Totonchi ,

Citation: BibTeX | EndNote

Abstract

Emotional neural networks provide promising characteristics such as fast response, learning ability, and approximation property. They are thus expected to handle the uncertainties and complexities when applied to the uncertain nonlinear systems. This paper employs the Radial Basis Emotional Neural Network (RBENN) in an indirect adaptive control design for approximating the unknown dynamics of a class of uncertain affine nonlinear systems. The proposed method adaptively updates the parameters of the radial basis functions in Thalamus nodes in addition to the adaptive weights of the Amygdala and the orbitofrontal cortex. The overall stability of the system is also verified according to the Lyapunov stability theory. Simulation results show the superiority of the proposed controller in considerably lower tracking error using slightly lower control energy compared to the RBENN with nonadaptive parameters of the radial basis functions.

Keywords

Emotional Neural Networks; Lyapunov Stability Theory; Nonlinear Adaptive Control; Radial Basis Functions
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@inproceedings{paperid:1083123,
author = {Baghbani, Fahimeh and Akbarzadeh Totonchi, Mohammad Reza},
title = {Adaptive Emotional Neuro Control for a Class of Uncertain Affine Nonlinear Systems},
booktitle = {28th Iranian Conference on Electrical Engineering},
year = {2020},
location = {تبریز, IRAN},
keywords = {Emotional Neural Networks; Lyapunov Stability Theory; Nonlinear Adaptive Control; Radial Basis Functions},
}

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%0 Conference Proceedings
%T Adaptive Emotional Neuro Control for a Class of Uncertain Affine Nonlinear Systems
%A Baghbani, Fahimeh
%A Akbarzadeh Totonchi, Mohammad Reza
%J 28th Iranian Conference on Electrical Engineering
%D 2020

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