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Observer-Based Hybrid-Triggered Control for Nonlinear Networked Control Systems with Disturbances

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Abstract

In this paper, the hybrid-triggered control (HTC) problem for nonlinear networked control systems with external disturbance is investigated by employing Takagi–Sugeno (T–S) fuzzy model. First of all, the observers are constructed to estimate system state and disturbance, respectively. With the help of disturbance estimation and attenuation (DEA) technique, the influence of external disturbance is attenuated effectively. Next, the HTC strategy is proposed to save the limited network resource while maintaining the desirable system performance. Then sufficient condition is proposed to ensure the exponential stability of the resultant closed-loop system, and the observer-based fuzzy controller is designed by solving an optimization problem. Finally, the effectiveness of the developed method is verified by a practical example.

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References

  1. Laghrouche, S., Liu, J., Ahmed, F.S., Harmouche, M., Wack, M.: Adaptive second-order sliding mode observer-based fault reconstruction for PEM fuel cell air-feed system. IEEE Trans. Control Syst. Technol. 23(3), 1098–1109 (2015)

    Article  Google Scholar 

  2. He, W., Chen, Y., Yin, Z.: Adaptive neural network control of an uncertain robot with full-state constraints. IEEE Trans. Cybern. 46(3), 620–629 (2016)

    Article  Google Scholar 

  3. Zhou, Q., Shi, P., Tian, Y., Wang, M.: Approximation-based adaptive tracking control for MIMO nonlinear systems with input saturation. IEEE Trans. Cybern. 45(10), 2119–2128 (2015)

    Article  Google Scholar 

  4. Wang, N., Gao, Y., Zhang, X.: Data-driven performance-prescribed reinforcement learning control of an unmanned surface vehicle. IEEE Trans. Neural Netw. Learn. Syst. 32(12), 5456–5467 (2021)

    Article  MathSciNet  Google Scholar 

  5. Wang, N., Gao, Y., Zhao, H., Ahn, C.K.: Reinforcement learning-based optimal tracking control of an unknown unmanned surface vehicle. IEEE Trans. Neural Netw. Learn. Syst. 32(7), 3034–3045 (2021)

    Article  MathSciNet  Google Scholar 

  6. Wang, N., Zhang, Y., Ahn, C.K., Xu, Q.: Autonomous pilot of unmanned surface vehicles: bridging path planning and tracking. IEEE Trans. Veh. Technol. 71(3), 2358–2374 (2022)

    Article  Google Scholar 

  7. Wang, N., Ahn, C.K.: Coordinated trajectory-tracking control of a marine aerial-surface heterogeneous system. IEEE/ASME Trans. Mechatron. 26(6), 3198–3210 (2021)

    Article  Google Scholar 

  8. Lu, R., Cheng, H., Bai, J.: Fuzzy-model-based quantized guaranteed cost control of nonlinear networked systems. IEEE Trans. Fuzzy Syst. 23(3), 567–575 (2015)

    Article  Google Scholar 

  9. Yi, Y., Zheng, W.X., Sun, C., Guo, L.: DOB fuzzy controller design for non-Gaussian stochastic distribution systems using two-step fuzzy identification. IEEE Trans. Fuzzy Syst. 24(2), 401–418 (2016)

    Article  Google Scholar 

  10. Xu, C., Zhang, Q., Wu, Y.: Existence and exponential stability of periodic solution to fuzzy cellular neural networks with distributed delays. Int. J. Fuzzy Syst. 18, 41–51 (2016)

    Article  MathSciNet  Google Scholar 

  11. Liu, J., et al.: Sliding mode control of grid-connected neutral-point-clamped converters via high-gain observer. IEEE Trans. Ind. Electron. 69(4), 4010–4021 (2022)

    Article  Google Scholar 

  12. Liu, J., Wu, L., Wu, C., Luo, W., Franquelo, L.G.: Event-triggering dissipative control of switched stochastic systems via sliding mode. Automatica 103, 261–273 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  13. Shi, P., Liu, M., Zhang, L.: Fault-tolerant sliding-mode-observer synthesis of Markovian jump systems using quantized measurements. IEEE Trans. Ind. Electron. 62(9), 5910–5918 (2015)

    Article  Google Scholar 

  14. Wu, L., Su, X., Shi, P.: Sliding mode control with bounded \(L_{2}\) gain performance of Markovian jump singular time-delay systems. Automatica 48(8), 1929–1933 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  15. Lin, Y., Nguyen, H.L.T.: Adaptive neuro-fuzzy predictor-based control for cooperative adaptive cruise control system. IEEE Trans. Intell. Transp. Syst. 21(3), 1054–1063 (2020)

    Article  Google Scholar 

  16. Chiu, C., Ouyang, Y.: Robust maximum power tracking control of uncertain photovoltaic systems: a unified T–S fuzzy model-based approach. IEEE Trans. Control Syst. Technol. 19(6), 1516–1526 (2011)

    Article  Google Scholar 

  17. Hagras, H.A.: A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots. IEEE Trans. Fuzzy Syst. 12(4), 524–539 (2004)

    Article  Google Scholar 

  18. Shanmugam, L., Joo, Y.H.: Stability and stabilization for T–S fuzzy large-scale interconnected power system with wind farm via sampled-data control. IEEE Trans. Syst. Man Cybern. Syst. 51(4), 2134–2144 (2021)

    Article  Google Scholar 

  19. An, H., Liu, J., Wang, C., Wu, L.: Disturbance observer-based antiwindup control for air-breathing hypersonic vehicles. IEEE Trans. Ind. Electron. 63(5), 3038–3049 (2016)

    Article  Google Scholar 

  20. Yang, J., Sun, J., Zheng, W.X., Li, S.: Periodic event-triggered robust output feedback control for nonlinear uncertain systems with time-varying disturbance. Automatica 94, 324–333 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  21. Wang, C., Zuo, Z., Qi, Z., Ding, Z.: Predictor-based extended state observer design for consensus of mass with delays and disturbances. IEEE Trans. Cybern. 49(4), 1259–1269 (2019)

    Article  Google Scholar 

  22. He, W., Zhang, S., Ge, S.S.: Boundary output-feedback stabilization of a Timoshenko beam using disturbance observer. IEEE Trans. Ind. Electron. 60(11), 5186–5194 (2013)

    Article  Google Scholar 

  23. Zhang, J., Zheng, W.X., Xu, H., Xia, Y.: Observer-based event-driven control for discrete-time systems with disturbance rejection. IEEE Trans. Cybern. 51(4), 2120–2130 (2021)

    Article  Google Scholar 

  24. Guo, B.Z., Zhao, Z.L.: On convergence of the nonlinear active disturbance rejection control for MIMO systems. SIAM J. Control Optim. 51(2), 1727–1757 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  25. Xiao, F., Shi, Y., Chen, T.: Robust stability of networked linear control systems with asynchronous continuous and discrete time event-triggering schemes. IEEE Trans. Autom. Control 66(2), 932–939 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  26. Liu, C., Li, H., Shi, Y., Xu, D.: Distributed event-triggered gradient method for constrained convex minimization. IEEE Trans. Autom. Control 65(2), 778–785 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  27. Peng, C., Sun, H.: Switching-like event-triggered control for networked control systems under malicious denial of service attacks. IEEE Trans. Autom. Control 65(9), 3943–3949 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  28. Garcia, A., Wang, L., Huang, J., Hong, L.: Distributed networked real-time learning. IEEE Trans. Control Netw. Syst. 8(1), 28–38 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  29. Liu, J., Yin, Y., Luo, W., Vazquez, S., Franquelo, L.G., Wu, L.: Sliding mode control of a three-phase AC/DC voltage source converter under unknown load conditions: industry applications. IEEE Trans. Syst. Man Cybern. Syst. 48(10), 1771–1780 (2018)

    Article  Google Scholar 

  30. Liu, J., Zha, L., Cao, J., Fei, S.: Hybrid-driven-based stabilization for networked control systems. IET Control Theory Appl. 10(17), 2279–2285 (2016)

    Article  MathSciNet  Google Scholar 

  31. Liu, J., Xia, J., Tian, E., Fei, S.: Hybrid-driven-based \(H_{\infty}\) filter design for neural networks subject to deception attacks. Appl. Math. Comput. 320, 158–174 (2018)

    MathSciNet  MATH  Google Scholar 

  32. Liu, J., Gu, Y., Xie, X., Yue, D., Park, J.H.: Hybrid-driven-based \({\cal{H}}_{\infty}\) control for networked cascade control systems with actuator saturations and stochastic cyber attacks. IEEE Trans. Syst. Man Cybern. Syst. 49(12), 2452–2463 (2019)

    Article  Google Scholar 

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (61873147), the Foundation for Innovative Research Groups of National Natural Science Foundation of China (61821004), the Youth Innovation Group Project of Shandong University (2020QNQT016), and the Qilu Youth Scholar Project from Shandong University.

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  1. Guitong Li and Rongni Yang have contributed equally to this work.

Authors and Affiliations

  1. School of Control Science and Engineering, Shandong University, Jinan, 250061, Shandong, China

    Guitong Li & Rongni Yang

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  1. Guitong Li
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  2. Rongni Yang
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Correspondence to Rongni Yang.

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Li, G., Yang, R. Observer-Based Hybrid-Triggered Control for Nonlinear Networked Control Systems with Disturbances. Int. J. Fuzzy Syst. 25, 316–325 (2023). https://doi.org/10.1007/s40815-022-01336-6

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  • DOI: https://doi.org/10.1007/s40815-022-01336-6

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