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Improved Event-Triggered-Based Output Tracking for a Class of Delayed Networked T–S Fuzzy Systems

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Abstract

This paper examines a nonlinear Networked Control System (NCS) incorporating Takagi–Sugeno (T–S) fuzzy models to address the output tracking control problem in the presence of input state delay. The paper introduces a strategy based on an event-triggered scheme to reduce bandwidth utilization in the NCS by leveraging inherent constraints, including communication time delays and data transmission limitations. The presence of communication time delay leads to an asynchronous interaction between the designed control algorithm for T–S fuzzy systems, which utilizes novel LMI–based conditions, and the proposed T–S fuzzy controller. Additionally, this paper proposes a model of operation based on synchronous behaviour, enabling the design of a linear controller that is more easily implementable. In comparison to recent literature results, these results are obtained by using an associate Lyapunov Krasovskii Function (LKF) with fuzzy properties, in addition to different forms of integral inequalities as alternatives. A fuzzy model for NCSs is illustrated through an example of tracking control for output response.

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References

  1. Wang, Y., Chai, T., Zhang, Y.: State observer-based adaptive fuzzy output-feedback control for a class of uncertain nonlinear systems. Inf. Sci. 180(24), 5029–5040 (2010)

    Article  MathSciNet  Google Scholar 

  2. Su, X., Chen, C.P., Liu, Z.: Adaptive fuzzy control for uncertain nonlinear systems subject to full state constraints and actuator faults. Inf. Sci. 581, 553–566 (2021)

    Article  Google Scholar 

  3. Melin, P., Castillo, O.: Intelligent control of a stepping motor drive using an adaptive neuro-fuzzy inference system. Inf. Sci. 170(2–4), 133–151 (2005)

    Article  Google Scholar 

  4. Yan, H., Qian, F., Yang, F., Shi, H.: \(H_\infty \) filtering for nonlinear networked systems with randomly occurring distributed delays, missing measurements and sensor saturation. Inf. Sci. 370, 772–782 (2016)

    Article  Google Scholar 

  5. Wu, J., Peng, C., Yang, H., Wang, Y.L.: Recent advances in event-triggered security control of networked systems: a survey. Int. J. Syst. Sci. 23, 1–20 (2022)

    MathSciNet  Google Scholar 

  6. Song, J., He, X.: Model-based fault diagnosis of networked systems: a survey. Asian J. Control 24(2), 526–536 (2022)

    Article  Google Scholar 

  7. Hu, J., Zhang, H., Liu, H., Yu, X.: A survey on sliding mode control for networked control systems. Int. J. Syst. Sci. 52(6), 1129–1147 (2021)

    Article  MathSciNet  Google Scholar 

  8. Ju, Y., Tian, X., Liu, H., Ma, L.: Fault detection of networked dynamical systems: a survey of trends and techniques. Int. J. Syst. Sci. 52(16), 3390–33409 (2021)

    Article  MathSciNet  Google Scholar 

  9. Zhang, X.M., Han, Q.L., Ge, X., Ding, D., Ding, L., Yue, D., Peng, C.: Networked control systems: a survey of trends and techniques. IEEE/CAA J. Autom. Sin. 7(1), 1–17 (2019)

    MathSciNet  Google Scholar 

  10. Kwon, O.M., Park, M.J., Park, J.H., Lee, S.M.: Stability and stabilization of TS fuzzy systems with time-varying delays via augmented Lyapunov–Krasovskii functionals. Inf. Sci. 372, 1–15 (2016)

    Article  MathSciNet  Google Scholar 

  11. Xie, X., Lu, J., Yue, D.: Resilient stabilization of discrete-time Takagi–Sugeno fuzzy systems: dynamic trade-off between conservatism and complexity. Inf. Sci. 582, 181–197 (2022)

    Article  MathSciNet  Google Scholar 

  12. Tang, P., Ma, Y.: Exponential stabilization and non-fragile sampled-date dissipative control for uncertain time-varying delay TS fuzzy systems with state quantization. Inf. Sci. 545, 513–536 (2021)

    Article  MathSciNet  Google Scholar 

  13. Zheng, Q., Xu, S., Du, B.: Robust guaranteed cost control of networked Takagi–Sugeno fuzzy systems with local nonlinear parts and multiple quantizations. Inf. Sci. 625, 489–503 (2023)

  14. Aravind, R.V., Balasubramaniam, P.: Dwell-time-dependent memory based state feedback controller design for switched Takagi–Sugeno fuzzy nonlinear systems. Inf. Sci. 609, 838–854 (2022)

    Article  Google Scholar 

  15. Nagamani, G., Joo, Y.H., Soundararajan, G., Mohajerpoor, R.: Robust event-triggered reliable control for TS fuzzy uncertain systems via weighted based inequality. Inf. Sci. 512, 31–49 (2020)

    Article  MathSciNet  Google Scholar 

  16. Mani, P., Joo, Y.H.: Fuzzy-logic-based event-triggered \(H_\infty \) control for networked systems and its application to wind turbine systems. Inf. Sci. 585, 144–161 (2022)

    Article  Google Scholar 

  17. Datta, R., Dey, R., Adhikari, N., Gu, J., Farooq, U., Asad, M.U.: \(H_{\infty }\) control for T-S fuzzy system via delayed state feedback: application to two-link robotic system. IFAC-PapersOnLine 55(1), 777–782 (2022)

    Article  Google Scholar 

  18. Xu, S., Wen, H., Wang, X.: Observer-based robust fuzzy control of nonlinear networked systems with actuator saturation. ISA Trans. 123, 122–135 (2022)

    Article  Google Scholar 

  19. Aslam, M.S., Tiwari, P., Pandey, H.M., Band, S.S.: Observer-based control for a new stochastic maximum power point tracking for photovoltaic systems with networked control system. IEEE Trans. Fuzzy Syst. 31(6), 1870–1884 (2023)

    Article  Google Scholar 

  20. Xie, Z., Wang, D., Wong, P.K., Li, W., Zhao, J.: Dynamic-output-feedback based interval type-2 fuzzy control for nonlinear active suspension systems with actuator saturation and delay. Inf. Sci. 607, 1174–1194 (2022)

    Article  Google Scholar 

  21. Pan, Y., Yang, G.H.: Event-triggered fuzzy control for nonlinear networked control systems. Fuzzy Sets Syst. 329, 91–107 (2017)

    Article  MathSciNet  Google Scholar 

  22. Tong, S., Wang, W., Qu, L.: Decentralized robust control for uncertain T-S fuzzy large-scale systems with time-delay. Int. J. Innov. Comput. Inf. Control 3, 657–672 (2007)

    Google Scholar 

  23. Seuret, A., Gouaisbaut, F.: Wirtinger-based integral inequality: application to time-delay systems. Automatica 49(9), 2860–2866 (2013)

    Article  MathSciNet  Google Scholar 

  24. Su, M.Y., Che, W.W.: Model-free adaptive tracking control for networked control systems under DoS attacks and RTT delays. Int. J. Control Autom. Syst. 20, 2222–2230 (2022)

    Article  Google Scholar 

  25. Du, Z., Kao, Y., Park, J.H., Zhao, X., Sun, J.A.: Fuzzy event-triggered control for nonlinear networked control systems. J. Frankl. Inst. 359(6), 2593–2607 (2022)

    Article  MathSciNet  Google Scholar 

  26. Li, Z.M., Chang, X.H., Xiong, J.: Event-based fuzzy tracking control for nonlinear networked systems subject to dynamic quantization. IEEE Trans. Fuzzy Syst. (2022). https://doi.org/10.1109/TFUZZ.2022.3193445

    Article  Google Scholar 

  27. Sau, N.H., Hong, D.T., Huyen, N.T., Huong, B.V., Thuan, M.V.: Delay-dependent and order-dependent \(H_ {\infty }\) control for fractional-order neural networks with time-varying delay. Differ. Equ. Dyn. Syst. 29(4), 825–839 (2021)

    Article  MathSciNet  Google Scholar 

  28. Lu, X., Li, H.: Prescribed finite-time \(H_ {\infty }\) control for nonlinear descriptor systems. IEEE Trans. Circuits Syst. II: Express Briefs 68(8), 2917–2921 (2021)

    Google Scholar 

  29. Bilal, H., Yin, B., Aslam, M.S., Anjam, Z., Rohra, A., Wang, Y.: A practical study of active disturbance rejection control for rotary flexible joint robot manipulator. Soft Comput. 27, 4987–5001 (2023). https://doi.org/10.1007/s00500-023-08026-x

    Article  Google Scholar 

  30. Xing, X., Yang, H., Liu, J., Wang, S.: LMI-based robust adaptive neural network control for Euler–Bernoulli beam with uncertain parameters and disturbances. Int. J. Control 95(1), 1–10 (2022)

    Article  MathSciNet  Google Scholar 

  31. Chen, Z., Zhang, Y., Kong, Q., Fang, T., Wang, J.: Observer-based \(H_ {\infty }\) control for persistent dwell-time switched networked nonlinear systems under packet dropout. Appl. Math. Comput. 415, 126679 (2022)

    Google Scholar 

  32. Aslam, M.S., Tiwari, P., Pandey, H.M., Band, S.S.: Robust stability analysis for class of Takagi–Sugeno (T–S) fuzzy with stochastic process for sustainable hypersonic vehicles. Inf. Sci. 641, 119044 (2023)

    Article  Google Scholar 

  33. Zhang, D., Shi, P., Wang, Q.G., Yu, L.: Analysis and synthesis of networked control systems: a survey of recent advances and challenges. ISA Trans. 66, 376–392 (2017)

    Article  Google Scholar 

  34. Lin, C., Wang, Q.G., Lee, T.H., He, Y.: Fuzzy weighting-dependent approach to \(H_{\infty }\) filter design for time-delay fuzzy systems. IEEE Trans. Signal Process. 55(6), 2746–2751 (2007)

    Article  MathSciNet  Google Scholar 

  35. Han, Q., Jia, X.: Network-based output tracking control for Takagi–Sugeno fuzzy systems using an event-triggered communication scheme. Fuzzy Sets Syst. 273, 26–48 (2015)

    Article  Google Scholar 

  36. Zhang, D., Han, Q., Jia, X.: Network-based output tracking control for Takagi–Sugeno fuzzy systems using an event-triggered communication scheme. Fuzzy Sets Syst. 273, 26–48 (2015)

    Article  Google Scholar 

  37. de Oliveira, T.G., Palhares, R.M., Campos, V.C.S.: Output tracking control for networked control systems. In: Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics, Lisbon Portugal, pp. 255–260 (2016)

  38. Yue, D., Tian, E., Han, Q.: A delay system method for designing event-triggered controllers of networked control systems. IEEE Trans. Autom. Control 58(2), 475–481 (2013)

    Article  MathSciNet  Google Scholar 

  39. Sun, S.X., Zhang, H.G., Qin, Z.C., Xi, R.P.: Delay-dependent \(H_{\infty }\) guaranteed cost control for uncertain switched T–S fuzzy systems with multiple interval time-varying delays. IEEE Trans. Fuzzy Syst. (2020). https://doi.org/10.1109/TFUZZ.2020.2968877

    Article  Google Scholar 

  40. Wu, Y., Dong, J.X.: Local stabilization of continuous-time T–S fuzzy systems with partly measurable premise variables and time-varying delay. IEEE Trans. Syst. Man Cybern.: Syst. (2018). https://doi.org/10.1109/TSMC.2018.2871100

  41. Wang, Y.C., Zhang, H.G., Wang, X.Y., et al.: Networked synchronization control of coupled dynamic networks with time-varying delay. IEEE Trans. Cybern. 40(6), 1468–1479 (2010)

    Article  Google Scholar 

  42. Min, H.F., Xu, S.Y., Zhang, B.Y., Ma, Q.: Output feedback control for stochastic nonlinear systems subject to input saturation and time-varying delay. IEEE Trans. Autom. Control 64(1), 359–364 (2019)

    Article  MathSciNet  Google Scholar 

  43. Wu, Z.G., Lam, J., Su, H., Chu, J.: Stability and dissipativity analysis of static neural networks with time delay. IEEE Trans. Neural Netw. Learn. Syst. 23(2), 199–210 (2012)

    Article  Google Scholar 

  44. Lin, C., Wang, Q.G., Lee, T.H., He, Y.: Fuzzy weighting-dependent approach to \(H_{\infty }\) filter design for time-delay fuzzy systems. IEEE Trans. Signal Process. 55(6), 2746–2751 (2007)

    Article  MathSciNet  Google Scholar 

  45. Zhang, D., Han, Q., Jia, X.: Network-based output tracking control for Takagi–Sugeno fuzzy systems using an event-triggered communication scheme. Fuzzy Sets Syst. 273, 26–48 (2015)

    Article  Google Scholar 

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Authors and Affiliations

  1. Artificial Intelligence Research Institute, China University of Mining and Technology, Xuzhou, 2211106, People’s Republic of China

    Muhammad Shamrooz Aslam

  2. Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, 632 014, India

    Thirunavukkarasu Radhika & Arunachalam Chandrasekar

  3. MOE-LCSM, School of Mathematical Sciences and Statistics, Hunan Normal University, Changsha, 410081, People’s Republic of China

    Quanxin Zhu

Authors
  1. Muhammad Shamrooz Aslam
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  2. Thirunavukkarasu Radhika
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  3. Arunachalam Chandrasekar
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  4. Quanxin Zhu
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Correspondence to Thirunavukkarasu Radhika or Quanxin Zhu.

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Aslam, M.S., Radhika, T., Chandrasekar, A. et al. Improved Event-Triggered-Based Output Tracking for a Class of Delayed Networked T–S Fuzzy Systems. Int. J. Fuzzy Syst. 26, 1247–1260 (2024). https://doi.org/10.1007/s40815-023-01664-1

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  • DOI: https://doi.org/10.1007/s40815-023-01664-1

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