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Steel and Composite Structures
  Volume 47, Number 4, May25 2023 , pages 513-521
DOI: https://doi.org/10.12989/scs.2023.47.4.513
 


GWO-based fuzzy modeling for nonlinear composite systems
ZY Chen, Yahui Meng, Ruei-Yuan Wang and Timothy Chen

 
Abstract
    The goal of this work is to create a new and improved GWO (Grey Wolf Optimizer), the so-called Robot GWO (RGWO), for dynamic and static target tracking involving multiple robots in unknown environmental conditions. From applying ourselves with the Gray Wolf Optimization Algorithm (GWO) and how it works, as the name suggests, it is a nature-inspired metaheuristic based on the behavior of wolf packs. Like other nature-inspired metaheuristics such as genetic algorithms and firefly algorithms, we explore the search space to find the optimal solution. The results also show that the improved optimal control method can provide superior power characteristics even when operating conditions and design parameters are changed.
 
Key Words
    feedback and feedforward; fuzzy LMI control; improved optimal control performance; linearization method
 
Address
ZY Chen and Ruei-Yuan Wang:School of Science, Guangdong University of Petrochemical Technology, Maoming 525000, Guangdong, China

Yahui Meng:1)School of Science, Guangdong University of Petrochemical Technology, Maoming 525000, Guangdong, China
2)InterNetworks Research Laboratory School of Computing (SOC) University Utara Malaysia 06010 UUM Sintok, Malaysia

Timothy Chen:California Institute of Technology, Pasadena, CA 91125, USA
 

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