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Data-based predictive control for networked nonlinear systems with packet dropout and measurement noise

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Abstract

In this paper, the data-based control problem is investigated for a class of networked nonlinear systems with measurement noise as well as packet dropouts in the feedback and forward channels. The measurement noise and the number of consecutive packet dropouts in both channels are assumed to be random but bounded. A data-based networked predictive control method is proposed, in which a sequence of control increment predictions are calculated in the controller based on the measured output error, and based on the control increment predictions received by the actuator, a proper control action is obtained and applied to the plant according to the real-time number of consecutive packet dropouts at each sampling instant. Then the stability analysis is performed for the networked closedloop system. Finally, the effectiveness of the proposed method is illustrated by a numerical example.

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References

  1. Hespanha J P, Naghshtabrizi P, and Xu Y, A survey of recent results in networked control systems, Proc. IEEE, 2007, 95(1): 138–162.

    Article  Google Scholar 

  2. Gupta R A and Chow M Y, Networked control system: Overview and research trends, IEEE Trans. Ind. Electron., 2010, 57(7): 2527–2535.

    Article  Google Scholar 

  3. Zhang L, Gao H, and Kaynak O, Network-induced constraints in networked control systems — A survey, IEEE Trans. Ind. Inf., 2013, 9(1): 403–416.

    Article  Google Scholar 

  4. Xia Y, Gao Y, Yan L, et al., Recent progress in networked control systems — A survey, Int. J. Autom. Comput., 2015, 12(4): 343–367.

    Article  Google Scholar 

  5. Liu G P, Xia Y, Chen J, et al., Networked predictive control of systems with random network delays in both forward and feedback channels, IEEE Trans. Ind. Electron., 2007, 54(3): 1282–1297.

    Article  Google Scholar 

  6. Hu W, Liu G P, and Rees D, Networked predictive control over the internet using round-trip delay measurement, IEEE Trans. Instrum. Meas., 2008, 57(10): 2231–2241.

    Article  Google Scholar 

  7. Irwin G W, Chen J, McKernan A, et al., Co-design of predictive controllers for wireless network control, IET Control Theory Appl., 2010, 4(2): 186–196.

    Article  MathSciNet  Google Scholar 

  8. Ulusoy A, Gurbuz O, and Onat A, Wireless model-based predictive networked control system over cooperative wireless network, IEEE Trans. Ind. Inf., 2011, 7(1): 41–51.

    Article  Google Scholar 

  9. Onat A, Naskali T, Parlakay E, et al., Control over imperfect networks: Model-based predictive networked control systems, IEEE Trans. Ind. Electron., 2011, 58(3): 905–913.

    Article  Google Scholar 

  10. Rahmani B, Markazi A H D, and Nezhad P M, Plant input-mapping-based predictive control of systems through band-limited networks, IET Control Theory Appl., 2011, 5(2): 341–350.

    Article  MathSciNet  Google Scholar 

  11. Pin G and Parisini T, Networked predictive control of uncertain constrained nonlinear systems: Recursive feasibility and input-to-state stability analysis, IEEE Trans. Autom. Control, 2011, 56(1): 72–87.

    Article  MathSciNet  Google Scholar 

  12. Pang Z H and Liu G P, Design and implementation of secure networked predictive control systems under deception attacks, IEEE Trans. Control Syst. Technol., 2012, 20(5): 1334–1342.

    Article  Google Scholar 

  13. Liu Y M and Fong I K, Robust predictive tracking control of networked control systems with time-varying delays and data dropouts, IET Control Theory Appl., 2013, 7(5): 738–748.

    Article  MathSciNet  Google Scholar 

  14. Tang X and Ding B, Model predictive control of linear systems over networks with data quantizations and packet losses, Automatica, 2013, 49(5): 1333–1339.

    Article  MathSciNet  MATH  Google Scholar 

  15. Zhang J, Xia Y, and Shi P, Design and stability analysis of networked predictive control systems, IEEE Trans. Control Syst. Technol., 2013, 21(4): 1495–1501.

    Article  Google Scholar 

  16. Quevedo D E and Jurado I, Stability of sequence-based control with random delays and dropouts, IEEE Trans. Autom. Control, 2014, 59(5): 1296–1302.

    Article  MathSciNet  MATH  Google Scholar 

  17. Nagahara M, Quevedo D, and Ostergaard J, Sparse packetized predictive control for networked control over erasure channels, IEEE Trans. Autom. Control, 2014, 59(7): 1899–1905.

    Article  MathSciNet  MATH  Google Scholar 

  18. Sun J and Chen J, Networked predictive control for systems with unknown or partially known delay, IET Control Theory Appl., 2014, 8(18): 2282–2288.

    Article  MathSciNet  Google Scholar 

  19. Sun X, Wu D, Liu G P, et al., Input-to-state stability for networked predictive control with random delays in both feedback and forward channels, IEEE Trans. Ind. Electron., 2014, 61(7): 3519–3526.

    Article  Google Scholar 

  20. Pang Z H, Liu G P, Zhou D H, et al., Output tracking control for networked systems: A modelbased prediction approach, IEEE Trans. Ind. Electron., 2014, 61(9): 4867–4877.

    Article  Google Scholar 

  21. Li H and Shi Y, Network-based predictive control for constrained nonlinear systems with twochannel packet dropouts, IEEE Trans. Ind. Electron., 2014, 61(3): 1574–1582.

    Article  Google Scholar 

  22. Du S L, Wang R, Shi P, et al., Input-to-state stability for networked control system with predictive scheme, J. Franklin Inst., 2015, 352(10): 4565–4578.

    Article  MathSciNet  Google Scholar 

  23. Pang Z H, Liu G P, Zhou D H, et al., Two-channel false data injection attacks against output tracking control of networked systems, IEEE Trans. Ind. Electron., 2016, 63(5): 3242–3251.

    Article  Google Scholar 

  24. Pang Z H, Liu G P, and Zhou D H, Design and performance analysis of incremental networked predictive control systems, IEEE Trans. Cybern., 2016, 46(6): 1400–1410.

    Article  Google Scholar 

  25. Wahab N A, Katebi R, Balderud J, et al., Data-driven adaptive model-based predictive control with application in wastewater systems, IET Control Theory Appl., 2011, 5(6): 803–812.

    Article  MathSciNet  Google Scholar 

  26. Ge S S, Li Z, and Yang H, Data driven adaptive predictive control for holonomic constrained under-actuated biped robots, IEEE Trans. Control Syst. Technol., 2012, 20(3): 787–795.

    Article  Google Scholar 

  27. Formentin S, Filippi D F, Corno M, et al., Data-driven design of braking control systems, IEEE Trans. Control Syst. Technol., 2013, 21(1): 186–193.

    Article  Google Scholar 

  28. Janssens P, Pipeleers G, and Swevers J, A data-driven constrained norm-optimal iterative learning control framework for LTI systems, IEEE Trans. Control Syst. Technol., 2013, 21(2): 546–551.

    Article  Google Scholar 

  29. Hou Z and Wang Z, From model-based control to data-driven control: Survey, classification and perspective, Inf. Sci., 2013, 235: 3–35.

    Article  MathSciNet  MATH  Google Scholar 

  30. Yin S, Li X, Gao H, et al., Data-based techniques focused on modern industry: An overview, IEEE Trans. Ind. Electron., 2015, 62(1): 657–667.

    Article  Google Scholar 

  31. Xia Y, Xie W, Liu B, et al., Data-driven predictive control for networked control systems, Inf. Sci., 2013, 235: 45–54.

    Article  MathSciNet  MATH  Google Scholar 

  32. Bu X, Yu F, Hou Z, et al., Model-free adaptive control algorithm with data dropout compensation, Math. Prob. Eng., 2012, 2012(4): 199–210.

    MathSciNet  MATH  Google Scholar 

  33. Pang Z H, Liu G P, Zhou D H, et al., Data-based predictive control for networked non-linear systems with two-channel packet dropouts, IET Control Theory Appl., 2015, 9(7): 1154–1161.

    Article  MathSciNet  Google Scholar 

  34. Pang Z H, Liu G P, Zhou D H, et al., Data-based predictive control for networked nonlinear systems with network-induced delay and packet dropout, IEEE Trans. Ind. Electron., 2016, 63(2): 1249–1256.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Key Laboratory of Fieldbus Technology and Automation of Beijing, North China University of Technology, Beijing, 100144, China

    Zhonghua Pang & Dehui Sun

  2. School of Engineering, University of South Wales, Pontypridd, CF37 1DL, UK

    Guoping Liu

  3. CTGT Center, Harbin Institute of Technology, Harbin, 150001, China

    Guoping Liu

  4. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, 266590, China

    Donghua Zhou

  5. Department of Automation, Tsinghua University, Beijing, 100084, China

    Donghua Zhou

Authors
  1. Zhonghua Pang
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  2. Guoping Liu
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  3. Donghua Zhou
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  4. Dehui Sun
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Corresponding author

Correspondence to Zhonghua Pang.

Additional information

This research was supported in part by the National Natural Science Foundation of China under Grant Nos. 61673023, 61203230, 61273104, 61333003, 61210012, and 61490701, the Beijing Municipal Natural Science Foundation under Grant No. 4152014, the GreatWall Scholar Candidate Training Program of North China University of Technology (NCUT), the Excellent Youth Scholar Nurturing Program of NCUT, the Outstanding Young Scientist Award Foundation of Shandong Province of China under Grant No. BS2013DX015, and the Research Fund for the Taishan Scholar Project of Shandong Province of China.

This paper was recommended for publication by Editor SUN Jian.

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Pang, Z., Liu, G., Zhou, D. et al. Data-based predictive control for networked nonlinear systems with packet dropout and measurement noise. J Syst Sci Complex 30, 1072–1083 (2017). https://doi.org/10.1007/s11424-017-5308-4

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  • DOI: https://doi.org/10.1007/s11424-017-5308-4

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