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Adaptive Tracking Design of NCS with Time-varying Signals Using Fuzzy Inverse Model

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  • Intelligent Control and Applications
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Abstract

Tracking control of time-varying signal is a very challenging problem for the network environment applications. An adaptive control strategy based on the inverse of fuzzy singleton model is proposed in the paper. The fuzzy singleton model is a designed equivalent system instead of the fuzzy clustering model of the controlled process. Following an invertibility condition, a collection of predicted control actions are derived from the iterated inverse fuzzy singleton model. Thus, the data dropout and time delays in the network are compensated by means of these predicted values. To enhance control performance, the adaptive control strategy is adopted. Since the method is started from the inputs and outputs of the process, it is actually a data-based solution which is very suitable to the processes with blurred mechanism. Compared with other two control algorithms, the proposed control algorithm exhibits good accuracy, high efficiency, and fast tracking features. Simulations in the data dropout and time-delay cases have verified the effectiveness of the method.

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Author information

Authors and Affiliations

  1. College of Robotics, Beijing Union University, Beijing, 100101, China

    Shiwen Tong, Na Huang & Jiancheng Zhang

  2. Beijing Engineering Research Center of Smart Mechanical Innovation Design Service, Beijing Union University, Beijing, 100101, China

    Shiwen Tong

  3. State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Shiwen Tong

  4. School of Control and Computer Engineering, North China Electric Power University, Beijing, 102206, China

    Dianwei Qian

  5. Department of Artificial Intelligence and Automation, Wuhan University, Wuhan, 430072, China

    Guo-ping Liu

  6. Engineering Center and the Research Institute for Frontier Intellectual Technology, Beijing Union University, Beijing, 100101, China

    Guang Cheng

Authors
  1. Shiwen Tong
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  2. Dianwei Qian
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  4. Guo-ping Liu
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  5. Jiancheng Zhang
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Corresponding author

Correspondence to Shiwen Tong.

Additional information

Recommended by Associate Editor Aldo Jonathan Munoz-Vazquez under the direction of Editor-in-Chief Keum-Shik Hong.

This work is supported by the National Natural Science Foundation of China (61773144), the Science and Technology Program of Beijing Municipal Education Commission (KM201811417001,KM202011417004), the Beijing Natural Science Foundation-Beijing Municipal Education Commission Joint Fund (KZ201811417048), the Beijing Natural Science Foundation-Rail Transit Joint Fund (L191006), the open research fund of the State Key Laboratory for Management and Control of Complex Systems (20210111) and the Academic Research Projects of Beijing Union University (No.ZK70202001). Many thanks to Professor Zhonghua Pang from NCUT for his useful discussion.

Shiwen Tong received his B.E. degree in chemical engineering from the University of Petroleum (East China), Shandong, China, in 1999, an M.E. degree in control theory and control engineering from the University of Petroleum (Beijing), Beijing, China, in 2003, and a Ph.D. degree from the Institute of Automation, Chinese Academy of Sciences, Beijing, China, in 2008. He was an operator with Liaohe Oil Feild Petrochemical Refinery from 1999–2002, an Engineer with Bejjing Anwenyou Science and Technology Company, Ltd. from 2003–2005, and an instrument Senior Engineer with China Tianchen Engineering Corporation (TCC) from 2008–2012. He is currently a Professor with the College of Robotics, Beijing Union University, Beijing, China. His research interests include the intelligent control, networked control, PEM fuel cell, and their industrial applications.

Dianwei Qian received his B.E. degree from Hohai University, Nanjing, China, in 2003. In 2005 and 2008, He received an M.E. degree from North-eastern University, Shenyang, China, and a Ph.D. degree from the Institute of Automation, Chinese Academy of Sciences, Beijing, China, respectively. Currently, he is an Associate Professor at the School of Control and Computer Engineering, North China Electric Power University, Beijing, China. His research interests include theories and applications of intelligent control, nonlinear control, etc.

Na Huang graduated from Taiyuan Institute of Heavy Machinery, Shanxi, China in 2001. She received an M.E. degree from Beijing University of Aeronautics and Astronautics, China in 2009. Currently, she is a laboratory technician in Beijing Union University, China. Her research interests include application of intelligent control, intelligent building integration, etc.

Guo-ping Liu received his B.Eng. and M.Eng. degrees in automation from the Central South University, Changsha, China, in 1982 and 1985, respectively, and a Ph.D. degree in control engineering from the University of Manchester, Manchester, UK, in 1992. He is a professor with Wuhan University, China. His current research interests include networked multi-agent control systems, nonlinear system identification and control, advanced control of industrial systems, and multiobjective optimization and control. He has authored/co-authored over 300 journal papers and 10 books on control systems. Prof. Liu is IET Fellow and IEEE Fellow.

Jiancheng Zhang received his B.E. degree in mechanical manufacturing technology and equipment from Hefei University of Technology in 1994, an M.E degree in mechanical engineering from Yanshan University in 2002, and a Ph.D. degree in the academy of aeronautics and aerospace manufacturing engineering from Beijing Institute of Technology in 2009. He is a Professor and Director of Beijing Intelligent Machinery Innovation Design Service Engineering Technology Research Center, Deputy Secretary of the Party Committee and Executive Dean of the College of Robotics, Beijing Union University. His research interests include modeling and control of mechanical systems.

Guang Cheng received his B.E. degree in mechanical manufacturing technology and equipment from Beijing Aeronautical Institute Branch in 1985, an M.E. degree in mechanical engineering from Tsinghua University in 1991, and a Ph.D. degree in mechanical design and theory from the National Mechanical Science Research Institute in 2009. He is a Professor and Dean of the Engineering Center, Beijing Union University. His research interests include the modeling, control and design of mechanical systems.

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Tong, S., Qian, D., Huang, N. et al. Adaptive Tracking Design of NCS with Time-varying Signals Using Fuzzy Inverse Model. Int. J. Control Autom. Syst. 19, 3801–3811 (2021). https://doi.org/10.1007/s12555-020-0114-5

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