Steel and Composite Structures

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GWO-based fuzzy modeling for nonlinear composite systems

  • ZY Chen (School of Science, Guangdong University of Petrochemical Technology) ;
  • Yahui Meng (School of Science, Guangdong University of Petrochemical Technology) ;
  • Ruei-Yuan Wang (School of Science, Guangdong University of Petrochemical Technology) ;
  • Timothy Chen (California Institute of Technology)
  • Received : 2021.10.31
  • Accepted : 2023.04.24
  • Published : 2023.05.25
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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.

Keywords

Acknowledgement

The authors are grateful for the research grants given to Ruei-Yuan Wang from the Projects of Talents Recruitment of GDUPT, Peoples R China under Grant NO. 2019rc098, and the research grants given to ZY Chen from the Projects of Talents Recruitment of GDUPT (NO. 2021rc002) in Guangdong Province, Peoples R China. as well as to the anonymous reviewers for constructive suggestions.

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