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Stabilization of NCSs by random allocation of transmission power to sensors

传感器发送功率随机分配下的网络控制系统的镇定问题

Abstract

This study investigates networked control systems (NCSs), whose sensors communicate with remote controllers via a wireless fading channel. The sensor can choose different power levels at which it can transmit its measurement to the controller. The transmission power is selected according to a given probability distribution. The level of transmission power determines the probability of packet loss. The objective of this study is to find an appropriate transmission power probability distribution and a system controller jointly such that NCSs can be exponentially stabilized within a given energy budget. By the average dwell time technique, sufficient conditions for almost sure stability and an optimal sensor power probability distribution maximizing the stability margin are obtained. The effectiveness of the results is demonstrated by numerical simulations.

创新点

本文以线性离散时不变网络控制系统为研究对象,讨论传感器和执行器通信信道之间的无线衰落问题。在任意时刻,传感器可以根据需要选择不同的发送功率将数据发送给远处的控制器,其中,发送功率的大小决定了丢包率的高低。本文考虑一种随机性的发送功率选择策略,旨在设计发送功率概率分配策略和状态反馈控制器,使得网络控制系统能够在有限的发送能量下指数镇定。通过使用平均驻留时间技术,得到了系统几乎必然稳定的充分条件,并且找到了一组最优的分布概率使得系统的稳定裕度最大。

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References

  1. 1

    Gaid M E M B, Cela A, Hamam Y. Optimal integrated control and scheduling of networked control systems with communication constraints: application to a car suspension system. IEEE Trans Control Syst Tech, 2006, 14: 779–787

  2. 2

    Ding S X, Zhang P, Yin S, et al. An integrated design framework of fault-tolerant wireless networked control systems for industrial automatic control applications. IEEE Trans Ind Informat, 2013, 9: 462–471

  3. 3

    Appadwedula S, Veeravalli V V, Jones D L. Energy-efficient detection in sensor networks. IEEE J Sel Areas Commun, 2005, 23: 693–702

  4. 4

    Ren Z, Cheng P, Chen J, et al. Optimal periodic sensor schedule for steady-state estimation under average transmission energy constraint. IEEE Trans Autom Control, 2013, 58: 3265–3271

  5. 5

    Shi L, Cheng P, Chen J. Sensor data scheduling for optimal state estimation with communication energy constraint. Automatica, 2011, 47: 1693–1698

  6. 6

    Shi L, Xie L. Optimal sensor power scheduling for state estimation of Gauss-Markov systems over a packet-dropping network. IEEE Trans Signal Process, 2012, 60: 2701–2705

  7. 7

    Han D, Cheng P, Chen J, et al. An online sensor power schedule for remote state estimation with communication energy constraint. IEEE Trans Autom Control, 2014, 59: 1942–1947

  8. 8

    Li Y Z, Quevedo D E, Lau V, et al. Online sensor transmission power schedule for remote state estimation. In: Proceeding of the 52nd IEEE Conference on Decision and Control, Firenze, 2013. 10–13

  9. 9

    Guo G, Wang L Y. Control over medium-constrained vehicular networks with fading channels and random access protocol: a networked systems approach. IEEE Trans Veh Tech, 2015, 64: 3347–3358

  10. 10

    Pappi K N, Lioumpas A S, Karagiannidis G K. θ-QAM: a parametric quadrature amplitude modulation family and its performance in AWGN and fading channels. IEEE Trans Commun, 2010, 58: 1014–1019

  11. 11

    Li Y, Quevedo D E, Lau V, et al. Optimal periodic transmission power schedules for remote estimation of ARMA processes. IEEE Trans Signal Process, 2013, 61: 6164–6174

  12. 12

    Marques A G, Wang X, Giannakis G B. Minimizing transmit power for coherent communications in wireless sensor networks with finite-rate feedback. IEEE Trans Signal Process, 2008, 56: 4446–4457

  13. 13

    Shiryayev A N. Probability. New York: Springer-Verlag, 1984. 100–110

  14. 14

    Elia N, Eisenbeis J N. Limitations of linear control over packet drop networks. IEEE Trans Autom Control, 2011, 56: 826–841

  15. 15

    Bolzern P, Colaneri P, Nicolao G D. Almost sure stability of Markov jump linear systems with deterministic switching. IEEE Trans Autom Control, 2013, 58: 209–214

  16. 16

    Dai S L, Lin H, Ge S S. Scheduling-and-control co-design for a collection of networked control systems with uncertain delays. IEEE Trans Control Syst Tech, 2010, 18: 66–78

  17. 17

    Guo Y F, Li S Y. Transmission probability condition for stabilisability of networked control systems. IET Control Theory Appl, 2008, 4: 672–682

  18. 18

    Zhai G, Hou B, Yasuda K, et al. Stability analysis of switched systems with stable and unstable subsystem: an average dwell time approach. In: Proceedings of American Control Conference, Chicago, 2010. 200–204

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Correspondence to Ge Guo.

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Wang, L., Guo, G. & Zhuang, Y. Stabilization of NCSs by random allocation of transmission power to sensors. Sci. China Inf. Sci. 59, 067201 (2016). https://doi.org/10.1007/s11432-016-5563-3

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Keywords

  • networked control systems
  • power allocation
  • packet dropout
  • almost sure stability
  • transmission energy constraint

关键词

  • 网络控制系统
  • 功率分配
  • 丢包
  • 几乎必然稳定
  • 发送能量约束