Modeling Control and Forecasting Nonlinear Systems Based on Grey Signal Theory
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1.
Guangdong University of Petrochemical Technology
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2.
California Institute of Technology
Abstract
Based on this article, a fuzzy NN (neural network) based on the EBA (evolved bat algorithm) was developed to devise adaptive control with gray signal prediction to provide asymptomatic stability and increased driving comfort. The method is used to assess plant nonlinearity and to perform structural tracking of the signal. The set of Gray’s differential equations is applied to Gray’s model (GM) (n, h), which has been an active system model. In the model, n is the order of the Gray’s differential equation and h is the number of variables considered. In this paper, a GM(2.1) has been utilised to achieve advanced nonlinear motion of a system, allowing the controller to demonstrate the efficiency and stability of the whole system in a Lyapunov-like expression. The controller design standard for a MEW (mechanical elastic wheel) is presented, creating a realistic framework in mathematical for practical engineering applications.
Copyright and License
© 2023 World Scientific Publishing Company.
Acknowledgement
The authors are grateful for the research grants given to Yahui Meng from the Provincial key platforms and major scienti c research projects of universities in Guangdong Province, Peoples R China under Grant No. 2017GXJK116, and the research grants given to ZY Chen from the Projects of Talents Recruitment of GDUPT (No. 2021rc002) in Guangdong Province, Peoples R China, RY Wang from the Projects of Talents Recruitment of GDUPT (No. 2019rc098), and Guangdong Provincial Key Lab. of Petrochemical Equipment and Fault Diagnosis, School of Science, Guangdong University of Petrochemical Technology, Maoming, Guangdong 525000, China as well as to the anonymous reviewers for constructive suggestions.
Ethics
The author declares that there are no con icts of interest regarding the publication of this paper. All analyzed data during this study are included in this article.
Additional details
Funding
- universities in Guangdong Province
- 2017GXJK116
- Guangdong University of Petrochemical Technology
- 2021rc002
- Guangdong University of Petrochemical Technology
- 2019rc098