Smart Structures and Systems

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A novel smart criterion of grey-prediction control for practical applications

  • Z.Y. Chen (School of Science, Guangdong University of Petrochemical Technology) ;
  • Ruei-yuan Wang (School of Science, Guangdong University of Petrochemical Technology) ;
  • Yahui Meng (School of Science, Guangdong University of Petrochemical Technology) ;
  • Timothy Chen (California Institute of Technology)
  • Received : 2022.03.27
  • Accepted : 2022.09.02
  • Published : 2023.01.25
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Abstract

The purpose of this paper is to develop a scalable grey predictive controller with unavoidable random delays. Grey prediction is proposed to solve problems caused by incorrect parameter selection and to eliminate the effects of dynamic coupling between degrees of freedom (DOFs) in nonlinear systems. To address the stability problem, this study develops an improved gray-predictive adaptive fuzzy controller, which can not only solve the implementation problem by determining the stability of the system, but also apply the Linear Matrix Inequality (LMI) law to calculate Fuzzy change parameters. Fuzzy logic controllers manipulate robotic systems to improve their control performance. The stability is proved using Lyapunov stability theorem. In this article, the authors compare different controllers and the proposed predictive controller can significantly reduce the vibration of offshore platforms while keeping the required control force within an ideal small range. This paper presents a robust fuzzy control design that uses a model-based approach to overcome the effects of modeling errors. To guarantee the asymptotic stability of large nonlinear systems with multiple lags, the stability criterion is derived from the direct Lyapunov method. Based on this criterion and a distributed control system, a set of model-based fuzzy controllers is synthesized to stabilize large-scale nonlinear systems with multiple delays.

Keywords

Acknowledgement

The authors are grateful for the research grants given to Ruei Yuan Wang from GDUPT talent introduction, Peoples R China under Grant No. 702 519208, the Projects of Talents Recruitment of GDUPT (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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