Skip to main content
SpringerLink
Log in

Decentralized Adaptive Event-triggered Control for Nonlinear Interconnected Systems in Strict-feedback Form

  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

The decentralized event triggered control problem is investigated for nonlinear interconnected systems in strict-feedback form subjected to parametric uncertainty. For each subsystem in the interconnected systems, the decentralized adaptive backstepping controller is designed to guarantee that the tracking error is semi-globally ultimately bounded. The control update and parameter estimate action are aperiodical executed only when the desired control specifications cannot be ensured, drastically reducing the computational burden and the transmission cost. It can be proved that zeno phenomenon is avoided as a positive lower bound on the minimal inter-sample time exists. The impulsive dynamical systems tools and Lyapunov analysis are introduced to prove the stability property for closed-loop system. Finally, a numerical simulation example is included to validate the effectiveness of the control scheme.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. C. Wang, C. Wen, Y. Lin, and W. Wang, “Decentralized adaptive tracking control for a class of interconnected nonlinear systems with input quantization,” Automatica, vol. 81, pp. 359–368, 2017.

    Article  MathSciNet  Google Scholar 

  2. G. Zong, H. Ren, and L. Hou, “Finite-time stability of interconnected impulsive switched systems,” IET Control Theory & Applications, vol. 10, no. 6, pp. 648–654, 2016.

    Article  MathSciNet  Google Scholar 

  3. X. Guo, J. Wang, F. Liao, and R. S. H. Teo, “Distributed adaptive sliding mode control strategy for vehicle-following systems with nonlinear acceleration uncertainties,” IEEE Transactions on Vehicular Technology, vol. 66, no. 2, pp. 981–991, 2017.

    Article  Google Scholar 

  4. G. Zong and D. Yang, “H∞ synchronization of switched complex networks: a switching impulsive control method,” Communications in Nonlinear Science and Numerical Simulation, vol. 77, pp. 338–348, 2019.

    Article  MathSciNet  Google Scholar 

  5. X. Guo, J. Wang, F. Liao, and R. S. H. Teo, “Distributed adaptive integrated-sliding-mode controller synthesis for string stability of vehicle platoons,” IEEE Transactions on Intelligent Transportation Systems, vol. 17, no. 9, pp. 2419–2429, 2016.

    Article  Google Scholar 

  6. B. Tian, H. Lu, Z. Zuo, and W. Yang, “Fixed-time leader-follower output feedback consensus for second-order multiagent systems,” IEEE Transactions on Cybernetics, vol. 49, no. 4, pp. 1545–1550, 2019.

    Article  Google Scholar 

  7. J. Huang and Q.-G. Wang, “Decentralized adaptive control of interconnected nonlinear systems with unknown control directions,” ISA Transactions, vol. 74, pp. 60–66, March 2018.

    Article  Google Scholar 

  8. Y.-X. Li and G.-H. Yang, “Graph-theory-based decentralized adaptive output-feedback control for a class of nonlinear interconnected systems,” IEEE Transactions on Cybernetics, vol. 49, no. 7, pp. 2444–2453, July 2019.

    Article  Google Scholar 

  9. X.-J. Li and G.-H. Yang, “Neural-network-based adaptive decentralized fault-tolerant control for a class of interconnected nonlinear systems,” IEEE Transactions on Neural Network and Learning System, vol. 29, no. 1, pp. 144–155, 2018.

    Article  MathSciNet  Google Scholar 

  10. Y. Li and S. Tong, “Adaptive neural networks decentralized FTC design for nonstrict-feedback nonlinear interconnected large-scale systems against actuator faults,” IEEE Transactions on Neural Network and Learning System, vol. 28, no. 11, pp. 2541–2554, 2017.

    Article  MathSciNet  Google Scholar 

  11. H. Ren, G. Zong, L. Hou, and Y. Yang, “Finite-time resilient decentralized control for interconnected impulsive switched systems with neutral delay,” ISA Transactions, vol. 67, pp. 19–29, 2017.

    Article  Google Scholar 

  12. Y. Li and G. Yang, “Model-based adaptive event-triggered control of strict-feedback nonlinear systems,” IEEE Transactions on Neural Network and Learning System, vol. 29, no. 4, pp. 1033–1045, 2018.

    Article  MathSciNet  Google Scholar 

  13. C. Hua, K. Li, and X. Guan, “Decentralized event-triggered control for interconnected time-delay stochastic nonlinear systems using neural networks,” Neurocomputing, vol. 272, pp. 270–278, 2018

    Article  Google Scholar 

  14. H. Ren, G. Zong, and T. Li, “Event-triggered finite-time control for networked switched linear systems with asynchronous switching,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 48, no. 11, pp. 1874–1884, 2018.

    Article  Google Scholar 

  15. H. Ren, G. Zong, and H. R. Karimi, “Asynchronous finite-time filtering of networked switched systems and its application: an event-driven method,” IEEE Transactions on Circuits and Systems I, vol. 66, no. 1, pp. 391–402, 2019.

    Article  MathSciNet  Google Scholar 

  16. B. Tian, J. Cui, H. Lu, and Q. Zong, “Reentry attitude control for RLV based on adaptive event-triggered sliding mode,” IEEE Access, vol. 7, pp. 68429–68435, 2019.

    Article  Google Scholar 

  17. V. Narayanan and S. Jagannathan, “Event-triggered distributed control of nonlinear interconnected systems using online reinforcement learning with exploration,” IEEE Transaction on Cybernetics, vol. 48, no. 9, pp. 2510–2519, 2018.

    Article  Google Scholar 

  18. V. Narayanan and S. Jagannathan, “Event-triggered dDistributed approximate optimal state and output control of afne nonlinear interconnected systems,” IEEE Transaction on Neural Network and Learning System, vol. 29, no. 7, pp. 2846–2856, 2018.

    Google Scholar 

  19. V. Narayanan, A. Sahoo, S. Jagannathan, and K. George, “Approximate optimal distributed control of nonlinear interconnected systems using event-triggered nonzero-sum games,” IEEE Transactions on Neural Networks and Learning System, vol. 30, no. 5, pp. 1512–1522, May 2019.

    Article  MathSciNet  Google Scholar 

  20. Z. Gu, P. Shi, D. Yue, and Z. Ding, “Decentralized adaptive event-triggered H∞ filtering for a class of networked nonlinear interconnected systems,” IEEE Transaction on Cybernetics, vol. 49, no. 5, pp. 1570–1579, May 2019.

    Article  Google Scholar 

  21. S. Zheng, P. Shi, S. Wang, and Y. Shi, “Event triggered adaptive fuzzy consensus for interconnected switched multiagent systems,” IEEE Transaction on Fuzzy Systems, vol. 27, no. 1, pp. 144–158, 2019.

    Article  Google Scholar 

  22. C. Hua, K. Li, and X. Guan, “Decentralized event-triggered control for interconnected time-delay stochastic nonlinear systems using neural networks,” Neurocomputing, vol. 272, pp. 270–278, 2018.

    Article  Google Scholar 

  23. C. Wen, “Decentralized adaptive regulation,” IEEE Transactions on Automatic Control, vol. 39, no. 10, pp. 2163–2166, 1994.

    Article  MathSciNet  Google Scholar 

  24. X. Ye, “Decentralized adaptive stabilization of large-scale nonlinear time-delay systems with unknown high-frequency-gain signs,” IEEE Transactions on Automatic Control, vol. 56, no. 6, pp. 1473–1478, 2011.

    Article  MathSciNet  Google Scholar 

  25. C. Wen, J. Zhou, and W. Wang, “Decentralized adaptive backstepping stabilization of interconnected systems with dynamic input and output interactions,” Automatica, vol. 45, no. 1, pp. 55–67, 2009.

    Article  MathSciNet  Google Scholar 

  26. L. Liu and X. Xie, “Decentralized adaptive stabilization for interconnected systems with dynamic input-output and nonlinear interactions,” Automatica, vol. 46, no. 6, pp. 1060–1067, 2010.

    Article  MathSciNet  Google Scholar 

  27. S. J. Yoo, J. B. Park, and Y. H. Choi, “Decentralized adaptive stabilization of interconnected nonlinear systems with unknown nonsymmetric dead-zone inputs,” Automatica, vol. 45, no. 2, pp. 436–443, 2009.

    Article  MathSciNet  Google Scholar 

  28. B. Niu, Y. Liu, G. Zong, Z. Han, and J. Fu, “Command filter-based adaptive neural tracking controller design for uncertain switched nonlinear output-constrained systems,” IEEE Transactions on Cybernetics, vol. 47, no. 10, pp. 3160–3171, 2017.

    Article  Google Scholar 

  29. L. Cao, H. Ma, Q. Zhou, and H. Li, “Adaptive decentralized control for large-scale nonlinear systems with event-triggered mechanism and actuator failures,” Youth Academic Annual Conference of Chinese Association of Automation, Nanjing, China, pp. 743–748, 2018.

  30. Y. Li and G. Yang, “Event-triggered adaptive backstepping control for parametric strict-feedback nonlinear systems,” International Journal of Robust and Nonlinear Control, vol. 28, pp. 976–1000, 2018.

    Article  MathSciNet  Google Scholar 

  31. C. Wang, C. Wen, and Y. Lin, “Decentrialized adaptive backstepping control for a class of interconnected nonlinear systems with unknown actuator failures,” Journal of the Franklin Institute, vol. 352, no. 3, pp. 835–850, 2015.

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electrical and Electronic Engineering, and Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems, Tianjin University of Technology, Tianjin City, P. R. China

    Yuehui Ji

  2. Tianjin Institute of Metrological Supervision and Testing (TIMST), Tianjin City, P. R. China

    Hailiang Zhou

  3. School of Electrical and Information Engineering, Tianjin University, Tianjin City, P. R. China

    Qun Zong

Authors
  1. Yuehui Ji
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hailiang Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qun Zong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuehui Ji.

Additional information

Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Recommended by Associate Editor Guangdeng Zong under the direction of Editor Hamid Reza Karimi. This study was funded by National Natural Science Foundation of China (Grant No. 61603274), Research Project of Tianjin Municipal Education Commission(Grant No.2017KJ249), National Natural Science Foundation of China (Grant No. 61673294), and Natural Science Foundation of Tianjin City (Grant No. 18JCQNJC74600).

Yuehui Ji received her B.S. and Ph.D. degrees from School of Electrical Engineering and Automation at Tianjin University, China, in 2009 and 2012, respectively. She is currently working as a lecturer in School of Electrical and Electronic Engineering, Tianjin University of Technology, China. Her research interests include nonlinear adaptive control, decentralized control for interconnected systems.

Hailiang Zhou received his B.S. and Ph.D. degrees from School of Electrical Engineering and Automation at Tianjin University, China, in 2009 and 2012, respectively. He is currently working as a Senior Engineer in Tianjin Institute of Metrological Supervision and Testing(TIMST), China. His research interests include nonlinear control, tracking control for quadrotor.

Qun Zong received his B.S. and Ph.D. degrees from School of Electrical Engineering and Automation at Tianjin University, China, in 1988 and 2003, respectively. He is currently working as a Professor in School of Electrical and Information Engineering, Tianjin University, China. His research interests include guidance control and simulation for aircraft, formation and coordination control for multi-agent systems, fault diagnosis and fault-tolerant control.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ji, Y., Zhou, H. & Zong, Q. Decentralized Adaptive Event-triggered Control for Nonlinear Interconnected Systems in Strict-feedback Form. Int. J. Control Autom. Syst. 18, 980–990 (2020). https://doi.org/10.1007/s12555-019-0461-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-019-0461-2

Keywords

Search

Navigation