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A robust controller design for networked hydraulic pressure control system based on CPR

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Abstract

The hydraulic CPR (Common Pressure Rail) system has some advantages (i.e. modularization and energy saving), which can be integrated with the characteristics of networked control system (NCS) to enhance the control performance. However, the strong nonlinearity and parameter uncertainty issues of the CPR system based on HT (hydraulic transformer) must be addressed. Moreover, the time-varying time delay and packet loss induced by NCS should be solved at the same time. In the paper, an adaptive fuzzy sliding mode controller based on Pi-sigma fuzzy neural network combining with Pade approximation is proposed to solve these problems. By constructing an appropriate Lyapunov function, the stability of the controller is proved. Finally, the simulation is proceeded to show the proposed controller can guarantee the robustness and compensate the input delay and packet loss in presence of external disturbance and parameter uncertainty.

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References

  1. Zhu Y, Zhang L, Zheng WX (2016) Distributed H-infinity filtering for a class of discrete-time Markov jump Lur’e systems with redundant channels. IEEE Trans Ind Electron 63(3):1876–1885

    Article  Google Scholar 

  2. Liu M, Zhang L, Shi P, Zhao Y (2017) Sliding mode control of continuous-time Markovian jump systems with digital data transmission. Automatica, Regular paper 80:200–209

    Article  MathSciNet  Google Scholar 

  3. Liu M, Zhang L, Zheng W (2017) Fault reconstruction for stochastic hybrid systems with adaptive discontinuous observer and non-homogeneous differentiator. Automatica 85:339–348

    Article  MathSciNet  Google Scholar 

  4. Shen W, Su X (2016) Controller design for network-based Markovian jump systems with unreliable communication links[J]. Complexity 21(S2):623–634

    Article  MathSciNet  Google Scholar 

  5. Shen W, Huang H, Pang Y et al (2017) Review of the energy saving hydraulic system based on common pressure rail[J]. IEEE Access 5:655–669

    Article  Google Scholar 

  6. Shen W, Pang Y, Jiang J (2018) Robust controller design of the integrated direct drive volume control architecture for steering systems[J]. ISA Trans 78(7):116–129

    Article  Google Scholar 

  7. Probst A, Magana ME, Sawodny O (2010) Using a Kalman filter and a Pade approximation to estimate random time delays in a networked feedback control system[J]. IET Control Theor Applic 4(11):2263–2272

    Article  MathSciNet  Google Scholar 

  8. Dong C, Xu L, Chen Y et al (2009) Networked flexible spacecraft attitude maneuver based on adaptive fuzzy sliding mode control[J]. Acta Astronautica 65(11–12):1561–1570 MLA

    Article  Google Scholar 

  9. Khanesar MA, Kaynak O, Yin S et al (2015) Adaptive indirect fuzzy sliding mode controller for networked control systems subject to time-varying network-induced time delay[J]. IEEE Trans Fuzzy Syst 23(1):205–214 MLA

    Article  Google Scholar 

  10. Zhu Y, Zhong Z, Basin MV, Zhou D (2018) A descriptor system approach to stability and stabilization of discrete-time switched PWA systems. IEEE Trans Autom Control 63(10):3456–3463

    Article  MathSciNet  Google Scholar 

  11. Zhu Y, Zhong Z, Zheng WX, Zhou D (2017) HMM-based H-infinity filtering for discrete-time Markov jump LPV systems over unreliable communication channels. IEEE Trans Syst Man Cybernet: Syst. https://doi.org/10.1109/TSMC.2017.2723038

  12. Hamdy M, Abd-Elhaleem S, Fkirin MA (2017) Design of adaptive fuzzy control for a class of networked nonlinear systems[J]. J Dyn Syst Meas Control 139(3):031008

    Article  Google Scholar 

  13. Hamdy M, Abd-Elhaleem S, Fkirin MA (2017) Time-varying delay compensation for a class of nonlinear control systems over network via H∞ adaptive fuzzy controller[J]. IEEE Trans Syst Man Cybernet: Syst 47(8):2114–2124

    Article  Google Scholar 

  14. Yao J, Jiao Z, Ma D (2015) A Practical Nonlinear Adaptive Control of Hydraulic Servomechanisms With Periodic-Like Disturbances[J]. IEEE/ASME Transactions on Mechatronics:1–9

  15. Meng D, Jia Y, Du J et al (2010) Learning control for time-delay systems with iteration-varying uncertainty: a smith predictor-based approach[J]. IET Contrl Theor Applic 4(12):2707–2718

    Article  MathSciNet  Google Scholar 

  16. Hamdy M, Abd-Elhaleem S, Fkirin MA (2018) Adaptive fuzzy predictive controller for a class of networked nonlinear systems with time-varying delay[J]. IEEE Trans Fuzzy Syst 26(4):2135–2144

    Article  Google Scholar 

  17. Wang Y, Yang X, Yan H (2019) Reliable fuzzy tracking control of near-space hypersonic vehicle using aperiodic measurement information[J]. IEEE Trans Ind Electron

  18. Wang Y, Karimi HR, Lam HK et al (2018) An improved result on exponential stabilization of sampled-data fuzzy systems[J]. IEEE Trans Fuzzy Syst 26(6):3875–3883

    Article  Google Scholar 

  19. Shen W, Su X, Pang Y et al (2018) Robust controller design for the excavator swing system under the active regulating common pressure rail[J]. Trans Inst Meas Control 40(11):3323–3332

    Article  Google Scholar 

  20. Shen W, Mai Y, Su X et al (2016) A new electric hydraulic actuator adopted the variable displacement pump[J]. Asian J Contrl 18(1):178–191

    Article  MathSciNet  Google Scholar 

  21. Shen W, Huang H, Wang J (2019) Robust Backstepping sliding mode controller investigation for a port plate position servo system based on an extended states observer[J]. Asian J Contrl 21(1):1–10

    Article  MathSciNet  Google Scholar 

  22. Xu R, Zhou M (2018) A self-adaption compensation control for hysteresis nonlinearity in piezo-actuated stages based on pi-sigma fuzzy neural network[J]. Smart Mater Struct 27(4):045002

    Article  Google Scholar 

  23. Li M, Chen D, Xiong A et al (2002) An adaptive prediction model of grain size for the forging of Ti–6Al–4V alloy based on fuzzy neural networks[J]. J Mater Process Technol 123(3):377–381

    Article  Google Scholar 

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Acknowledgements

The authors acknowledge the contribution of the National Natural Science Foundation of China (51505289) and Open Foundation of the State Key Laboratory of Fluid Power and Mechatronic Systems (GZKF-201708).

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Authors and Affiliations

  1. Department of Mechatronics Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Wei Shen & Jiehao Wang

  2. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, 310000, China

    Wei Shen

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  1. Wei Shen
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  2. Jiehao Wang
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Correspondence to Wei Shen.

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This article is part of the Topical Collection: Special Issue on Networked Cyber-Physical Systems Guest Editors: Heng Zhang, Mohammed Chadli, Zhiguo Shi, Yanzheng Zhu, and Zhaojian Li

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Shen, W., Wang, J. A robust controller design for networked hydraulic pressure control system based on CPR. Peer-to-Peer Netw. Appl. 12, 1651–1661 (2019). https://doi.org/10.1007/s12083-019-00760-0

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