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Output-based event-triggered tracking control for networked pneumatic muscle actuators system with packet disorders

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Abstract

In this paper, output-based event-triggered tracking control for a networked pneumatic muscle actuators system with packet disorders is investigated. An output-based event-triggered strategy is adopted to avoid the transmission of abundantly redundant data and alleviate the network congestion. Meanwhile, packet disorders frequently occur in the data transmission process in the network environment, which will damage the tracking performance of the networked pneumatic muscle actuator system. A packet reordering method is proposed to deal with the packet disorders and to select the latest control voltage signal, considering the control voltage signal update period is variable under the output-based event-triggered strategy. Besides, an active disturbance rejection controller is designed to observe and compensate the lumped disturbance composed of the nonlinear flow characteristics of the pressure proportional valves and the disturbance caused by the mechanical mechanism. Then a sufficient condition is given to ensure input-to-state stability of the closed-loop system. Finally, extensive experiments are carried out to verify the applicability of the proposed packet reordering method and the tracking performance of the system.

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References

  1. Azahar, M.I.P., Irawan, A., Ismail, R.M.T.R.: Self-tuning hybrid fuzzy sliding surface control for pneumatic servo system positioning. Control Eng. Pract. 113, 104838 (2021)

    Article  Google Scholar 

  2. Kalita, B., Dwivedy, S.K.: Dynamic analysis of pneumatic artificial muscle (PAM) actuator for rehabilitation with principal parametric resonance condition. Nonlinear Dyn. 97, 2271–2289 (2019)

    Article  Google Scholar 

  3. Zhao, L., Cheng, H., Zhang, J., Xia, Y.: Adaptive control for a motion mechanism with pneumatic artificial muscles subject to dead-zones. Mech. Syst. Signal Process. 148, 107155 (2021)

    Article  Google Scholar 

  4. Carvalho, A.D.D., Karanth, N., Desai, V.: Design and characterization of a pneumatic muscle actuator with novel end-fittings for medical assistive applications. Sens. Actuator A Phys. 331, 112877 (2021)

    Article  Google Scholar 

  5. Cao, Y., Huang, J., Xiong, C.: Single-layer learning-based predictive control with echo state network for pneumatic-muscle-actuators-driven exoskeleton. IEEE Trans. Cogn. Develop. Syst. 13, 80–90 (2017)

    Article  Google Scholar 

  6. Franco, E., Ayatullah, T., Sugiharto, A., Garriga-Casanovas, A., Virdyawan, V.: Nonlinear energy-based control of soft continuum pneumatic manipulators. Nonlinear Dyn. 106(1), 229–253 (2021)

    Article  Google Scholar 

  7. Liang, D., Sun, N., Wu, Y., Chen, Y., Fang, Y., Liu, L.: Energy-based motion control for pneumatic artificial muscle actuated robots with experiments. IEEE Trans. Ind. Electron. 69(7), 7295–7306 (2022)

    Article  Google Scholar 

  8. Cao, J., Xie, S., Das, R.: MIMO sliding mode controller for gait exoskeleton driven by pneumatic muscles. IEEE Trans. Control Syst. Technol. 26(1), 274–281 (2018)

    Article  Google Scholar 

  9. Huang, J., Cao, Y., Wang, Y.: Adaptive proxy-based sliding mode control for a class of second-order nonlinear systems and its application to pneumatic muscle actuators. ISA Trans. 124, 395–402 (2020)

    Article  Google Scholar 

  10. Huang, J., Cao, Y., Xiong, C., Zhang, H.: An echo state gaussian pprocess-based nonlinear model predictive control for pneumatic muscle actuators. IEEE Trans. Autom. Sci. Eng. 16(3), 1071–1084 (2019)

    Article  Google Scholar 

  11. Sun, N., Liang, D., Wu, Y., Chen, Y., Qin, Y., Fang, Y.: Adaptive control for pneumatic artificial muscle systems with parametric uncertainties and unidirectional input constraints. IEEE Trans. Industr. Inform. 16(2), 969–979 (2020)

    Article  Google Scholar 

  12. Andrikopoulos, G., Nikolakopoulos, G., Manesis, S.: Advanced nonlinear PID-based antagonistic control for pneumatic muscle actuators. IEEE Trans. Ind. Electron. 61(12), 6926–6937 (2014)

    Article  Google Scholar 

  13. Nuchkrua, T., Leephakpreeda, T.: Fuzzy self-tuning PID control of hydrogen-driven pneumatic artificial muscle actuator. J. Bionic Eng. 10(3), 329–340 (2019)

    Article  Google Scholar 

  14. Liu, P., Chen, S., Zhao, Z.: On active disturbance rejection control for lower-triangular systems with mismatched nonlinear uncertainties and unknown time-varying control coefficients. Nonlinear Dyn. 106(3), 2377–2400 (2021)

    Article  Google Scholar 

  15. Zhao, L., Cheng, H., Xia, Y., Liu, B.: Angle tracking adaptive backstepping control for a mechanism of pneumatic muscle actuators via an AESO. IEEE Trans. Ind. Electron. 66(6), 4566–4576 (2019)

    Article  Google Scholar 

  16. Yang, H., Yu, Y., Zhang, J.: Angle tracking of a pneumatic muscle actuator mechanism under varying load conditions. Control. Eng. Pract. 61, 1–10 (2017)

    Article  Google Scholar 

  17. Yuan, Y., Yu, Y., Guo, L.: Nonlinear active disturbance rejection control for the pneumatic muscle actuators with discrete-time measurements. IEEE Trans. Ind. Electron. 66(3), 2044–2053 (2019)

    Article  Google Scholar 

  18. Wang, X., Lemmon, M.D.: Event-triggering in distributed networked control systems. IEEE Trans. Automat. Contr. 56(3), 586–601 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  19. Yu, Y., Yuan, Y.: Event-triggered active disturbance rejection control for nonlinear network control systems subject to DoS and physical attacks. ISA Trans. 104, 73–83 (2020)

    Article  Google Scholar 

  20. Cui, K., Tang, S., Huang, Y., Yu, H., Shi, D.: Event-triggered active disturbance rejection control for a class of networked systems with unmatched uncertainties: Theoretic and experimental results. Control Eng. Pract. 115, 104907 (2021)

    Article  Google Scholar 

  21. Xiao, X., Park, J.H., Zhou, L., Lu, G.: Event-triggered control of discrete-time switched linear systems with network transmission delays. Automatica 111, 108585 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  22. Niu, Y., Sheng, L., Gao, M., Zhou, D.: Dynamic event-triggered state estimation for continuous-time polynomial nonlinear systems with external disturbances. IEEE Trans. Industr. Inform. 17(6), 3962–3970 (2021)

    Article  Google Scholar 

  23. Deng, C., Che, W., Wu, Z.: A dynamic periodic event-triggered approach to consensus of heterogeneous linear multiagent systems with time-varying communication delays. IEEE Trans. Cybern. 51(4), 1812–1821 (2021)

    Article  Google Scholar 

  24. Peng, C., Zhang, J., Yan, H.: Adaptive event-triggering \(H\infty \) load frequency control for network-based power systems. IEEE Trans. Ind. Electron. 65(2), 1685–1694 (2018)

    Article  Google Scholar 

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

    Article  Google Scholar 

  26. Zhao, Y., Kim, J., Liu, G., Rees, D.: Compensation and stochastic modeling of discrete-time networked control systems with data packet disorder. Int. J. Control Autom. Syst. 10(5), 1055–1063 (2012)

    Article  Google Scholar 

  27. Zhao, Y., Liu, G., Rees, D.: Actively compensating for data packet disorder in networked control systems. IEEE Trans. Circuits Syst. II Express Briefs 57(11), 913–917 (2010)

    Google Scholar 

  28. Zhang, F., Zhang, Q., Li, J.: Networked control for T-S fuzzy descriptor systems with network-induced delay and packet disordering. Neurocomputing 275, 2264–2312 (2018)

    Article  Google Scholar 

  29. Lian, B., Zhang, Q., Li, J.: Sliding mode control and sampling rate strategy for networked control systems with packet disordering via markov chain prediction. ISA Trans. 83, 1–12 (2018)

    Article  Google Scholar 

  30. Lian, B., Zhang, Q., Li, J.: Integrated sliding mode control and neural networks based packet disordering prediction for nonlinear networked control systems. IEEE Trans. Neural Netw. Learn. Syst. 30(8), 2324–2335 (2019)

    Article  MathSciNet  Google Scholar 

  31. Liu, A., Zhang, W., Yu, L., Liu, S., Chen, M.Z.Q.: New results on stabilization of networked control systems with packet disordering. Automatica 52, 255–259 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  32. Han, J.: From PID to active disturbance rejection control. IEEE Trans. Ind. Electron. 66(3), 900–906 (2009)

    Article  Google Scholar 

  33. Jiang, Z., Wang, Y.: Input-to-state stability for discrete-time nonlinear systems. Automatica 37(6), 857–869 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  34. Zhang, H., Xiao, G., Yu, X., Xie, Y.: On convergence performance of discrete-time optimal control based tracking differentiator. IEEE Trans. Ind. Electron. 68(4), 3359–3369 (2021)

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank the anonymous reviewers for their detailed comments that helped to improve the quality of the paper.

Funding

The work was supported by the National Natural Science Foundation of China (61773334, 62073238), the Natural Science Foundation of Hebei Provincial (F2020203079, F2022208007), and the Key projects of Natural Science Foundation of Hebei Province (F2021203054).

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Authors and Affiliations

  1. School of Electrical Engineering, Yanshan University, Qinhuangdao, 066004, China

    Li Li & Yipeng Cao

  2. State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin, 300072, China

    Ling Zhao

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  1. Li Li
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  2. Yipeng Cao
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Correspondence to Ling Zhao.

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Li, L., Cao, Y. & Zhao, L. Output-based event-triggered tracking control for networked pneumatic muscle actuators system with packet disorders. Nonlinear Dyn 111, 6363–6378 (2023). https://doi.org/10.1007/s11071-022-08143-6

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