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Output Tracking Predictive Control of Networked Systems with Two-channel Random Communication Constraints

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  • Control Theory and Applications
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Abstract

In this paper, the output tracking control problem is investigated for a networked control system with two-channel random network delays and packet dropouts as well as stochastic noise. To actively compensate for these random communication constraints in the feedback and forward channels, a novel networked predictive control (NPC) method is proposed based on the input-output difference equation model, where the two-channel communication constraints are handled separately according to their different features. Furthermore, different from the existing NPC methods based on round-trip time delays, actual control inputs rather than the predicted ones are employed to generate future control commands. Then a delay-independent closed-loop stability condition is obtained, and a condition to guarantee a zero steady-state output tracking error is derived. Also, theoretical analysis shows that the proposed NPC method can achieve the same output tracking performance as the corresponding local control system. Finally, the effectiveness of the proposed method is evaluated by simulation and experimental results.

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Author information

Authors and Affiliations

  1. Key Laboratory of Fieldbus Technology and Automation of Bei**g, North China University of Technology, Bei**g, 100144, China

    Chuan-Dong Bai, Tong Mu & Zhong-Hua Pang

  2. State Key Laboratory of Intelligent Control and Decision of Complex Systems, School of Automation, Bei**g Institute of Technology, Bei**g, 100081, China

    Jian Sun

  3. Center for Control Science and Technology, Southern University of Science and Technology, Shenzhen, 518055, China

    Guo-** Liu

Authors
  1. Chuan-Dong Bai
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  2. Tong Mu
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  3. Zhong-Hua Pang
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  4. Jian Sun
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  5. Guo-** Liu
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Correspondence to Zhong-Hua Pang.

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This work was supported by the National Natural Science Foundation of China under Grants 62173002, 61925303, 62088101, U20B2073, and 62173255, the Bei**g Natural Science Foundation under Grant 4222045, and the National Key R&D Program of China under Grant 2018YFB1700100.

Chuan-Dong Bai received his B.Eng. and M.Eng. degrees in vehicle operation engineering from the Northeast Forestry University, China, in 1998 and 2002, respectively. He is currently an Associate Professor in the College of Mechanical and Material Engineering, North China University of Technology, China. His research interests include networked control systems and data-driven control.

Tong Mu received his B.Eng. degree in electrical engineering and automation from the Qingdao City University, China in 2017, and an M.Eng degree in control science & control engineering from the Qingdao University of Technology, China in 2020. He is currently pursuing a Ph.D. degree in control science & engineering with the North China University of Technology, China. His research interests include networked control and intelligent control.

Zhong-Hua Pang received his B.Eng. and M.Eng. degrees from the Qingdao University of Science and Technology, China, in 2002 and 2005, respectively, and a Ph.D. degree from the Institute of Automation, Chinese Academy of Sciences, China in 2011. From 2011 to 2014, he was a Postdoctoral Research Fellow with the Tsinghua University, China. As a Research Fellow, he was with the University of South Wales, UK from 2016 to 2017, and was with the Swinburne University of Technology, Australia from 2019 to 2020. Since 2014, he has been with the North China University of Technology, China first as an Associate Professor and since 2017 as a Professor. His research interests include networked control, secure control, and data-driven control. He is a senior member of IEEE, a topic editor of Symmetry, and a youth editor of Journal of Smart Environments and Green Computing.

Jian Sun received his B.Sc. degree from the Jilin Institute of Technology, China in 2001, an M.Sc. degree from the Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences (CAS), China in 2004, and a Ph.D. degree from the Institute of Automation, CAS, China in 2007. From 2008 to 2009, he was a Research Fellow with the University of Glamorgan, UK. From 2007 to 2010, he was a Postdoctoral Research Fellow with the Bei**g Institute of Technology, China. In 2010, he joined the School of Automation, Bei**g Institute of Technology, where he has been a Professor since 2013. His current research interests include networked control systems, time-delay systems, and security of cyber-physical systems. He is an Editorial Board Member of the IEEE Transactions on Systems, Man and Cybernetics: Systems, the Journal of Systems Science and Complexity, and Acta Automatica Sinica.

Guo-** Liu received his B.Eng and M.Eng degrees from the Central South University of Technology, China, in 1982 and 1985, respectively, and a Ph.D. degree from the University of Manchester, UK in 1992. He is a professor with the Southern University of Science and Technology. His research interests include networked multi-agent control, nonlinear identification and intelligent control, multi-objective optimal control and decision, and industrial advanced control applications. He was the general chair of the 2007 IEEE International Conference on Networking, Sensing and Control, the 2011 International Conference on Intelligent Control and Information Processing, and the 2012 United Kingdom Automatic Control Council (UKACC) International Conference on Control. He served as an editor-inchief of the International Journal of Automation and Computing. He is a member of the Academy of Europe and a fellow of IEEE, IET, and CAA.

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Bai, CD., Mu, T., Pang, ZH. et al. Output Tracking Predictive Control of Networked Systems with Two-channel Random Communication Constraints. Int. J. Control Autom. Syst. 21, 475–484 (2023). https://doi.org/10.1007/s12555-021-0774-9

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  • DOI: https://doi.org/10.1007/s12555-021-0774-9

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