Intelligent wavelet fuzzy brain emotional controller using dual function-link network for uncertain nonlinear control systems

Tuan Tu Huynh, Chih Min Lin, Nguyen Quoc Khanh Le, Mai The Vu, Ngoc Phi Nguyen, Fei Chao

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This study aims to propose a more efficient hybrid algorithm to achieve favorable control performance for uncertain nonlinear systems. The proposed algorithm comprises a dual function-link network-based multilayer wavelet fuzzy brain emotional controller and a sign(.) functional compensator. The proposed algorithm estimates the judgment and emotion of a brain that includes two fuzzy inference systems for the amygdala network and the prefrontal cortex network via using a dual-function-link network and three sub-structures. Three sub-structures are a dual-function-link network, an amygdala network, and a prefrontal cortex network. Particularly, the dual-function-link network is used to adjust the amygdala and orbitofrontal weights separately so that the proposed algorithm can efficiently reduce the tracking error, follow the reference signal well, and achieve good performance. A Lyapunov stability function is used to determine the adaptive laws, which are used to efficiently tune the system parameters online. Simulation and experimental studies for an antilock braking system and a magnetic levitation system are presented to verify the effectiveness and advantage of the proposed algorithm.

Original languageEnglish
Pages (from-to)2720-2744
Number of pages25
JournalApplied Intelligence
Volume52
Issue number3
DOIs
Publication statusPublished - Feb 2022

Keywords

  • Antilock braking system
  • Brain emotional learning controller
  • Dual function-link network
  • Fuzzy inference system
  • Magnetic levitation system
  • Wavelet membership function

ASJC Scopus subject areas

  • Artificial Intelligence

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