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ABSTRACT
Unfalsified Adaptive Switching Supervisory Control (UASSC) is a performance-based data-driven methodology to control uncertain systems with the least possible plant assumptions. There are a set of pre-designed controllers in the controller bank, and the goal is to select the best controller at each time instance. The Multi-Model UASSC (MMUASSC) uses the UASSC concept, but it also benefits from a set of pre-specified models in the model bank. This paper introduces a method to improve the performance of the UASSC and MMUASSC by cost function manipulations and fuzzy logic concepts. To achieve this, fuzzy UASSC and fuzzy MMUASSC methods are introduced. In these methods, a time-varying coefficient, which is the output of a fuzzy system, is used along with the conventional cost functions. The input of this fuzzy system is chosen to properly reflect the performance of the corresponding controller in the controller bank. Using this method, the performance of the outside loop controllers is accurately evaluated, and closed-loop stability proof is provided. Also, as the existence of non-minimum phase controllers is problematic, a solution is provided to handle such cases. Finally, simulation results are used to show the effectiveness of the introduced methods.
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No potential conflict of interest was reported by the authors.
Additional information
Notes on contributors
S. I. Habibi
Seyed Iman Habibi received his B.Sc. and M.Sc. degrees in electrical engineering from K. N. Toosi University of Technology, Tehran, Iran, in 2015 and 2018. He is currently a Ph.D. student in the University of New Mexico. His main research areas include smart grid, supervisory control, switching control, adaptive systems.
A. Khaki-Sedigh
Ali Khaki Sedigh is currently a professor of control systems with the Department of Electrical and Computer Engineering, K. N. Toosi University of Technology, Tehran, Iran. He obtained an honours degree in mathematics in 1983, a master's degree in control systems in 1985 and a Ph.D. in control systems in 1988, all in the UK. He is the author and co-author of about 90 journal papers, 170 international conference papers and has published 14 books in the area of control systems. His main research interests are adaptive and robust multivariable control systems, complex systems and chaos control, research ethics and the history of control.
M. N. Manzar
Mojtaba Nouri Manzar received the B.Sc. degree in electrical engineering from University of Science and Technology, Tehran, Iran, in 2010, the M.Sc. in electrical engineering from University of Tehran, Tehran, Iran, in 2012 and the Ph.D. degree in electrical engineering from K. N. Toosi University of Technology, Tehran, Iran, in 2017. He is currently an Assistant Professor with the control department in the electrical engineering faculty, University of Shahid Beheshti, Tehran, Iran. His main research areas include supervisory control, switching control, adaptive systems, fault detection, and fault-tolerant control.