Combined indirect & direct adaptive fuzzy decentralised control of large-scale systems with strong interconnection and its application

Abstract

To achieve better adaptation properties, the proposed controller is a weighted combination of indirect and direct adaptive fuzzy controls such that both fuzzy descriptions and control rules can be incorporated under a united controller design at the same time. By using fuzzy systems and robust control technique, the interconnections between subsystems are extended to general unknown nonlinear functions. No a priori knowledge of lower and upper bounds on lumped uncertainties is required to construct each local controller. The resulting closed-loop large-scale system is proved to be asymptotically stable. The controller design is applicable to an automated highway system, and simulation results confirm its practical usefulness.

KEYWORDS:

• Large-scale system
• hybrid adaptive fuzzy control
• decentralised control
• strong interconnection
• robust control

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This project was supported by the Natural Science Foundation of Hunan Province of China (2018JJ2444), the Scientific Research Fund of Hunan Provincial Education Department of China (16A007), the National Natural Science Foundation of China (51678075) and the Open Fund of Engineering Research Center of Catastrophic Prophylaxis and Treatment of Road & Traffic Safety (Changsha University of Science & Technology) Ministry of Education (kfj140401).

Notes on contributors

Yi-Shao Huang

Yi-Shao Huang received his master degree from the Department of Automation, North University of China in 2005 and the Ph.D. degree from Institution of Systems Engineering, Nanjing University of Aeronautics and Astronautics in 2009. Now he is an associate professor in School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha, China, and his research interests include nonlinear control, intelligent traffic control theory and industrial applications. Dr Huang has published more than 20 journal papers and a monographs in the above areas.

Lei Han

Lei Han received the M.S. degree in traffic engineering from Changsha University of Science and Technology, Changsha, China, in 2019.

Zhengwu Wang

Zhengwu Wang received the Ph.D. degree of traffic information engineering and control from the School of Information Science and Engineering, Central South University, Changsha, China in 2007. During 2009–2011, he did his excellent postdoctoral research at the Control Science and Engineering Postdoctoral Mobile Station of Central South University. Now he is a professor in School of Traffic and Transportation Engineering, Changsha University of Science and Technology. He was designated as the training object of the excellent young backbone teachers in 2009 and into the New Century ‘121 talent Project’ in 2010 of Hunan province of China. Dr Wang has got several science and technology awards and finished many national or provincial research projects. He has authored or coauthored over 30 journals and refereed conference papers, a monographs, and co-invented several patents in the above areas. His research interests include traffic control theory, urban planning methods, and their engineering applications.