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Fuzzy Adaptive Finite Time Command Filter Backstepping Control of Power System

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  • Intelligent Control and Applications
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Abstract

In this article, an adaptive fuzzy finite time command filter control scheme is first proposed for a single machine infinite power system with static VAR compensator (SVC). The unknown external interference is taken into account in the controller design, and the incomplete single machine infinite SVC power system is formulated in terms of fuzzy logic system. The devised adaptive backstepping control scheme employs command filter technology and finite time control theory. Further more, it is proven that the designed controller ensures the rotor power angle in the power system converge to the expected value and all variables of the control systems are semi-global practical finite-time stable (SGPFS). Finally, simulation results are presented to show the effectiveness of the proposed control scheme.

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Author information

Authors and Affiliations

  1. School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, 215009, China

    Wangyao Xu, Ze Li, Guozeng Cui, Chengxi Wang & Fuyuan Hu

  2. Suzhou Institute of Intelligent City, Suzhou University of Science and Technology, Suzhou, 215009, China

    Wangyao Xu, Ze Li, Guozeng Cui, Chengxi Wang & Fuyuan Hu

  3. Jiangsu Province Key Laboratory of Intelligent Building Energy Efficiency, Suzhou, 215009, China

    Wangyao Xu, Ze Li, Guozeng Cui, Chengxi Wang & Fuyuan Hu

Authors
  1. Wangyao Xu
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  2. Ze Li
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  3. Guozeng Cui
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  4. Chengxi Wang
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  5. Fuyuan Hu
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Corresponding authors

Correspondence to Ze Li or Guozeng Cui.

Additional information

Recommended by Associate Editor Zhijia Zhao under the direction of Editor Euntai Kim

This work was supported in part by the National Natural Science Foundation of China under Grants 61703059, 61873144, 61876121, by the China Post-Doctoral Science Foundation under Grant 2018 632621, by the Natural Science Foundation of Jiangsu Province under Grant BK20170291, by the Science and Technology Development Plan Project of Suzhou City under Grant SS202024, and by the key Reaearch and development plan of Jiangsu Provinceunder Grant BE2017663.

Wangyao Xu received his Bachelor’s degree in electric and information engineering from Suzhou University of Science and Technology in 2019. His research interests include adaptive fuzzy control and nonlinear systems.

Ze Li received her Bachelor’s degree and Ph.D. degree in the School of Automation, Nanjing University of Science and Technology, in 2005 and 2010, respectively. She is now an Associate Professor in the School of Electronic and Information Engineering, Suzhou University of Science and Technology, associated with the Intelligent Control and Information Processing Group. Her research interests lie in the fields of control and filtering problem for fuzzy system, stochastic system and unmanned surface vehicle.

Guozeng Cui received his B.Sc. degree in applied mathematics from the Shandong University of Technology, Zibo, China, in 2009, and an M.Sc. degree in applied mathematics from Qufu Normal University, Qufu, China, in 2012, and a Ph.D. degree in control science and engineering from the Nanjing University of Science and Technology, Nanjing, China, in 2016. He is currently a Lecturer with the School of Electronic and Information Engineering, Suzhou University of Science and Technology. His current research interests include adaptive control, intelligent control for nonlinear systems, and multi-agent systems.

Chengxi Wang received his Bachelor degree in electric and information engineering from Suzhou University of Science and Technology in 2019. His research interests include model predictive control and nonlinear systems.

Fuyuan Hu received his Ph.D. degree in Northwest Polytechnic University in 2007. He is now a Professor in the School of Electronic and Information Engineering, Suzhou University of Science and Technology. His research interests are machine learning and computer vision.

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Xu, W., Li, Z., Cui, G. et al. Fuzzy Adaptive Finite Time Command Filter Backstepping Control of Power System. Int. J. Control Autom. Syst. 19, 3812–3822 (2021). https://doi.org/10.1007/s12555-020-0466-x

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  • DOI: https://doi.org/10.1007/s12555-020-0466-x

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