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Estimation and Control for Networked Systems with Packet Losses without Acknowledgement

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 77))

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Abstract

With the rapid advances in computer science, communication and control techniques, the traditional point-to-point communication architecture for the control systems, in which each components connected via wires cannot meet requirements of modern industry, such as modularity, integrated diagnostics, easy installation and maintenance, and distributed control.

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References

  1. Jin, Y., Kwak, D., Kim, K.J., Kwak, K.S.: Cyclic prefixed single carrier transmission in intra-vehicle wireless sensor networked control systems. In: 2014 IEEE 79th Vehicular Technology Conference (Vtc-Spring) (2014)

    Google Scholar 

  2. El-Farra, N.H., Mhaskar, P.: Special issue on “control of networked and complex process systems”. Comput. Chem. Eng. 32(9), 1963–1963 (2008)

    Article  Google Scholar 

  3. Sun, Y.L., El-Farra, N.H.: Resource aware quasi-decentralized control of networked process systems over wireless sensor networks. Chem. Eng. Sci. 69(1), 93–106 (2012)

    Article  Google Scholar 

  4. Liu, Y.C.: Robust synchronisation of networked lagrangian systems and its applications to multi-robot teleoperation. IET Control Theory Appl. 9(1), 129–139 (2015)

    Article  MathSciNet  Google Scholar 

  5. Casavola, A., Franze, G.: Coordination strategies for networked control systems: a power system application. In: 2008 10th International Conference on Control Automation Robotics & Vision, vols 1–4, pp. 503–508 (2008)

    Google Scholar 

  6. Park, P.: Power controlled fair access protocol for wireless networked control systems. Wirel. Netw. 21(5), 1499–1516 (2015)

    Article  Google Scholar 

  7. Teixeira, A., Sandberg, H., Johansson, K.H.: Networked control systems under cyber attacks with applications to power networks. In: 2010 American Control Conference, pp. 3690–3696 (2010)

    Google Scholar 

  8. Zhang, Y., Ma, H., Xu, F.: Study on networked control for power electronic systems. In: 2007 IEEE Power Electronics Specialists Conference, vols 1–6, pp. 833–838 (2007)

    Google Scholar 

  9. Barrero, F., Guevara, J.A., Vargas, E., Toral, S., Vargas, M.: Networked transducers in intelligent transportation systems based on the ieee 1451 standard. Comput. Stand. Interfaces 36(2), 300–311 (2014)

    Article  Google Scholar 

  10. Park, P., Khadilkar, H., Balakrishnan, H., Tomlin, C.J.: High confidence networked control for next generation air transportation systems. IEEE Trans. Autom. Control 59(12), 3357–3372 (2014)

    Article  MathSciNet  Google Scholar 

  11. Losada, M., Rubio, F., Bencomo, S.: Asynchronous Control for Networked Systems. Springer, Heidelberg (2015)

    Book  Google Scholar 

  12. Mahmoud, M.: Control and Estimation Methods Over Communication Networks. Springer, Heidelberg (2014)

    Book  Google Scholar 

  13. Peng, C., Yue, D., Han, Q.-L.: Communication and Control for Networked Complex Systems. Springer, Heidelberg (2015)

    Book  MATH  Google Scholar 

  14. Saligrama, V.: Networked Sensing Information and Control. Springer, Heidelberg (2008)

    Book  MATH  Google Scholar 

  15. Wang, F.-Y., Liu, D.: Networked Control Systems: Theory and Applications. Springer, London (2008)

    Book  Google Scholar 

  16. Bemporad, A., Heemels, M., Johansson, M.: Networked Control Systems, vol. 406. Springer, Heidelberg (2010)

    MATH  Google Scholar 

  17. You, K., Xiao, N., Xie, L.: Analysis and Design of Networked Control Systems. Springer, Heidelberg (2015)

    Book  MATH  Google Scholar 

  18. Simon, D., Song, Y.-Q., Aubrun, C.: Co-design Approaches to Dependable Networked Control Systems. Wiley, New York (2013)

    Google Scholar 

  19. Longo, S., Su, T., Herrmann, G., Barber, P.: Optimal and Robust Scheduling for Networked Control Systems. CRC Press, Boca Raton (2013)

    MATH  Google Scholar 

  20. Yüksel, S., Başar, T.: Stochastic Networked Control Systems: Stabilization and Optimization Under Information Constraints. Springer Science & Business Media, Heidelberg (2013)

    Google Scholar 

  21. Xia, Y., Fu, M., Liu, G.-P.: Analysis and Synthesis of Networked Control Systems, vol. 409. Springer Science & Business Media, Heidelberg (2011)

    MATH  Google Scholar 

  22. Hespanha, J.P., Naghshtabrizi, P., Xu, Y.: A survey of recent results in networked control systems. Proc. IEEE 95(1), 138 (2007)

    Article  Google Scholar 

  23. Ke-You, Y., Li-Hua, X.: Survey of recent progress in networked control systems. Acta Autom. Sin. 39(2), 101–117 (2013)

    Article  MathSciNet  Google Scholar 

  24. Zhang, L.X., Gao, H.J., Kaynak, O.: Network-induced constraints in networked control systems-a survey. IEEE Trans. Ind. Inform. 9(1), 403–416 (2013)

    Article  Google Scholar 

  25. Qiu, J.B., Gao, H.J., Ding, S.X.: Recent advances on fuzzy-model-based nonlinear networked control systems: a survey. IEEE Trans. Ind. Electron. 63(2), 1207–1217 (2016)

    Article  Google Scholar 

  26. Garcia, A.L., Widjaja, I.: Communication Networks. McGraw Hill, New York (2000)

    Google Scholar 

  27. Sinopoli, B., Schenato, L., Franceschetti, M., Poolla, K., Sastry, S.: Optimal linear LQG control over lossy networks without packet acknowledgment. Asian J. Control 10(1), 3–13 (2008)

    Article  MathSciNet  Google Scholar 

  28. Kögel, M., Blind, R., Allgöwer, F., Findeisen, R.: Optimal and optimal-linear control over lossy, distributed networks. In: Proceedings of the 18th IFAC World Congress, pp. 13239–13244 (2011)

    Google Scholar 

  29. Garone, E., Sinopoli, B., Casavola, A.: LQG control over lossy TCP-like networks with probabilistic packet acknowledgements. Int. J. Syst., Control Commun. 2(1), 55–81 (2010)

    Article  Google Scholar 

  30. Moayedi, M., Foo, Y.K., Soh, Y.C.: Networked LQG control over unreliable channels. Int. J. Robust Nonlinear Control 23(2), 167–189 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  31. Ploplys, N.J., Kawka, P.A., Alleyne, A.G.: Closed-loop control over wireless networks. IEEE Control Syst. 24(3), 58–71 (2004)

    Article  Google Scholar 

  32. Sinopoli, B., Schenato, L., Franceschetti, M., Poolla, K., Jordan, M.I., Sastry, S.S.: Kalman filtering with intermittent observations. IEEE Trans. Autom. Control 49(9), 1453–1464 (2004)

    Article  MathSciNet  Google Scholar 

  33. You, K., Fu, M., Xie, L.: Mean square stability for Kalman filtering with Markovian packet losses. Automatica 47(12), 2647–2657 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  34. Yang, R., Shi, P., Liu, G.-P.: Filtering for discrete-time networked nonlinear systems with mixed random delays and packet dropouts. IEEE Trans. Autom. Control 56(11), 2655–2660 (2011)

    Article  MathSciNet  Google Scholar 

  35. Wang, Z., Yang, F., Ho, D.W., Liu, X.: Robust \(H_\infty \) control for networked systems with random packet losses. IEEE Trans. Syst., Man, Cybern. 37(4), 916–924 (2007)

    Article  Google Scholar 

  36. Wang, D., Wang, J., Wang, W.: \(H_\infty \) controller design of networked control systems with Markov packet dropouts. IEEE Trans. Syst., Man, Cybern. 43(3), 689–697 (2013)

    Article  Google Scholar 

  37. Silva, E.I., Pulgar, S.A.: Control of LTI plants over erasure channels. Automatica 47(8), 1729–1736 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  38. Wang, D., Wang, J., Wang, W.: Output feedback control of networked control systems with packet dropouts in both channels. Inform. Sci. 221, 544–554 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  39. Qu, F.-L., Guan, Z.-H., He, D.-X., Chi, M.: Event-triggered control for networked control systems with quantization and packet losses. J. Frankl. Inst. (2014)

    Google Scholar 

  40. Elia, N., Eisenbeis, J.N.: Limitations of linear remote control over packet drop networks. In: 43rd IEEE Conference on Decision and Control, vol. 5, pp. 5152–5157. IEEE (2004)

    Google Scholar 

  41. Ishii, H.: Limitations in remote stabilization over unreliable channels without acknowledgements. Automatica 45(10), 2278–2285 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  42. Gupta, V., Martins, N.C.: On stability in the presence of analog erasure channel between the controller and the actuator. IEEE Trans. Autom. Control 55(1), 175–179 (2010)

    Article  MathSciNet  Google Scholar 

  43. Bai, J., Su, H., Gao, J., Sun, T., Wu, Z.: Modeling and stabilization of a wireless network control system with packet loss and time delay. J. Frankl. Inst. 349(7), 2420–2430 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  44. Xu, Y., Su, H., Pan, Y.-J., Wu, Z.-G., Xu, W.: Stability analysis of networked control systems with round-robin scheduling and packet dropouts. J. Frankl. Inst. 350(8), 2013–2027 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  45. Jazwinski, A.H.: Stochastic Processes and Filtering Theory. Academic Press, New York (1970)

    MATH  Google Scholar 

  46. Anderson, B.D.O., Moore, J.B.: Optimal Filtering. Prentice-Hall, Englewood Cliffs (1979)

    MATH  Google Scholar 

  47. Maybeck, P.S.: Stochastic Models, Estimation, and Control. Academic press, New York (1982)

    MATH  Google Scholar 

  48. Bertsekas, D.P.: Dynamic Programming and Optimal Control, vol. 1. Athena Scientific, Belmont (1995)

    MATH  Google Scholar 

  49. Simon, D.: Optimal State Estimation : Kalman, \({H}_\infty \) and Nonlinear Approaches. Wiley-Interscience, Hoboken (2006)

    Book  Google Scholar 

  50. Lewis, F.L., Vrabie, D.L., Syrmos, V.L.: Optimal Control, 3rd edn. Wiley, Hoboken (2012)

    Book  MATH  Google Scholar 

  51. Nahi, N.E.: Optimal recursive estimation with uncertain observation. IEEE Trans. Inform. Theory 15(4), 457–462 (1969)

    Article  MathSciNet  MATH  Google Scholar 

  52. Smith, S.C., Seiler, P.: Estimation with lossy measurements: jump estimators for jump systems. IEEE Trans. Autom. Control 48(12), 2163–2171 (2003)

    Article  MathSciNet  Google Scholar 

  53. Sun, S., Xie, L., Xiao, W., Soh, Y.C.: Optimal linear estimation for systems with multiple packet dropouts. Automatica 44(5), 1333–1342 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  54. Liang, Y., Chen, T., Pan, Q.: Optimal linear state estimator with multiple packet dropouts. IEEE Trans. Autom. Control 55(6), 1428–1433 (2010)

    Article  MathSciNet  Google Scholar 

  55. Plarre, K., Bullo, F.: On Kalman filtering for detectable systems with intermittent observations. IEEE Trans. Autom. Control 54(2), 386–390 (2009)

    Article  MathSciNet  Google Scholar 

  56. Mo, Y., Sinopoli, B.: A characterization of the critical value for Kalman filtering with intermittent observations. In: 47th IEEE Conference on Decision and Control, CDC 2008, pp. 2692–2697. IEEE (2008)

    Google Scholar 

  57. Mo, Y., Sinopoli, B.: Kalman filtering with intermittent observations: tail distribution and critical value. IEEE Trans. Autom. Control 57(3), 677–689 (2012)

    Article  MathSciNet  Google Scholar 

  58. Kluge, S., Reif, K., Brokate, M.: Stochastic stability of the extended Kalman filter with intermittent observations. IEEE Trans. Autom. Control 55(2), 514–518 (2010)

    Article  MathSciNet  Google Scholar 

  59. Li, L., Xia, Y.: Stochastic stability of the unscented Kalman filter with intermittent observations. Automatica 48(5), 978–981 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  60. Hu, J., Wang, Z., Gao, H., Stergioulas, L.K.: Extended Kalman filtering with stochastic nonlinearities and multiple missing measurements. Automatica 48(9), 2007–2015 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  61. Censi, A.: Kalman filtering with intermittent observations: convergence for semi-Markov chains and an intrinsic performance measure. IEEE Trans. Autom. Control 56(2), 376–381 (2011)

    Article  MathSciNet  Google Scholar 

  62. Kar, S., Sinopoli, B., Moura, J.M.: Kalman filtering with intermittent observations: weak convergence to a stationary distribution. IEEE Trans. Autom. Control 57(2), 405–420 (2012)

    Article  MathSciNet  Google Scholar 

  63. Huang, M., Dey, S.: Stability of Kalman filtering with Markovian packet losses. Automatica 43(4), 598–607 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  64. Imer, O.C., Yüksel, S., Başar, T.: Optimal control of LTI systems over unreliable communication links. Automatica 42(9), 1429–1439 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  65. Schenato, L., Sinopoli, B., Franceschetti, M., Poolla, K., Sastry, S.S.: Foundations of control and estimation over lossy networks. Proc. IEEE 95(1), 163–187 (2007)

    Article  Google Scholar 

  66. Garone, E., Sinopoli, B., Goldsmith, A., Casavola, A.: LQG control for MIMO systems over multiple erasure channels with perfect acknowledgment. IEEE Trans. Autom. Control 57(2), 450–456 (2012)

    Article  MathSciNet  Google Scholar 

  67. Basin, M., Calderon-Alvarez, D.: Optimal LQG controller for linear stochastic systems with unknown parameters. J. Frankl. Inst. 345(3), 293–302 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  68. Xu, H., Jagannathan, S., Lewis, F.L.: Stochastic optimal control of unknown linear networked control system in the presence of random delays and packet losses. Automatica 48(6), 1017–1030 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  69. Mo, Y., Garone, E., Sinopoli, B.: LQG control with Markovian packet loss. In: 2013 European Conference on Control (ECC), pp. 2380–2385. IEEE (2013)

    Google Scholar 

  70. Cappe, O., Moulines, E., Ryden, T.: Inference in Hidden Markov Models. Springer Series in Statistics. Springer, New York (2005)

    MATH  Google Scholar 

  71. Costa, O.L.V., Fragoso, M.D., Marques, R.P.: Discrete-Time Markov Jump Linear Systems. Springer, Heidelberg (2006)

    MATH  Google Scholar 

  72. Li, X.R., Bar-Shalom, Y.: Performance prediction of the interacting multiple model algorithm. IEEE Trans. Aerosp. Electron. Syst. 29(3), 755–771 (1993)

    Article  Google Scholar 

  73. Wolfinger, R., O’connell, M.: Generalized linear mixed models a pseudo-likelihood approach. J. Stat. Comput. Simul. 48(3–4), 233–243 (1993)

    Google Scholar 

  74. Blom, H.A., Bar-Shalom, Y.: The interacting multiple model algorithm for systems with Markovian switching coefficients. IEEE Trans. Autom. Control 33(8), 780–783 (1988)

    Article  MATH  Google Scholar 

  75. Vo, B.-N., Ma, W.-K.: The Gaussian mixture probability hypothesis density filter. IEEE Trans. Signal Process. 54(11), 4091–4104 (2006)

    Article  Google Scholar 

  76. Costa, O.L.V.: Linear minimum mean square error estimation for discrete-time Markovian jump linear systems. IEEE Trans. Autom. Control 39(8), 1685–1689 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  77. Costa, O.L.V., Guerra, S.: Stationary filter for linear minimum mean square error estimator of discrete-time Markovian jump systems. IEEE Trans. Autom. Control 47(8), 1351–1356 (2002)

    Article  MathSciNet  Google Scholar 

  78. M. Epstein, L. Shi, and R. M. Murray. Estimation schemes for networked control systems using UDP-like communication. In: 46th IEEE Conference on Decision and Control, pp. 3945–3951. IEEE (2007)

    Google Scholar 

  79. Epstein, M., Shi, L., Murray, R.M.: An estimation algorithm for a class of networked control systems using udp-like communication schemes. In: 45th IEEE Conference on Decision and Control, pp. 5597–5603. IEEE (2006)

    Google Scholar 

  80. Blind, R., Allgower, F.: Estimating the fates of the control packets for networked control systems with loss of control and measurement packets. In: Proceedings of the 48th IEEE Conference on CDC/CCC 2009, pp. 2687–2692. IEEE (2009)

    Google Scholar 

  81. Anderson, B.D., Moore, J.B.: Optimal Control: Linear Quadratic Methods. Courier Corporation, Chelmsford (2007)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China

    Hong Lin

  2. Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, Zhejiang, China

    Hongye Su & Zheng-Guang Wu

  3. College of Engineering and Science, Victoria University, Melbourne, VIC, Australia

    Peng Shi

  4. Faculty of Engineering and the Environment, University of Southampton, Southampton, UK

    Zhan Shu

Authors
  1. Hong Lin
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  2. Hongye Su
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  3. Peng Shi
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  5. Zheng-Guang Wu
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Corresponding author

Correspondence to Hong Lin .

Appendix

Appendix

In this section, we list the aforementioned results on the optimal or suboptimal estimators and LQG controllers for the traditional, TCP-like, UDP-like, and Quasi-TCP-like systems. We show the main framework of these formulas. For the details, please see the corresponding references.

A. Optimal Estimator and Control for the Traditional Control Systems

Consider the following discrete-time system with the traditional point-to-point communication architecture as in Fig. 1.1:

$$\begin{aligned} x_{k+1} = {}&Ax_{k}+ B u_k +\omega _k \\ y_k = {}&Cx_{k} + \upsilon _k \end{aligned}$$

where \(x_k\) is the system state, \(u_k\) is the control input, and \(y_k\) is the observation. \(\omega _k\) and \(\upsilon _k\) are i.i.d. zero-mean Gaussian noises with covariance \(Q \ge 0\) and \(R >0\), respectively.

The optimal estimator and LQG controller for the traditional systems are given in Algorithms 1.1 and 1.2, respectively.

figure a
figure b

B. Optimal Estimator and Control for the TCP-Like NCSs

Consider the following discrete-time system with the TCP-like communication architecture as in Fig. 1.3:

$$\begin{aligned} \begin{aligned} x_{k+1}&= Ax_{k}+ \nu _k B u_k +\omega _k \\ y_k&= \left\{ \begin{array}{ll} Cx_{k} + \upsilon _k, &{} \hbox {for } \gamma _k = 1 \\ \phi , &{} \hbox {for } \gamma _k = 0 \end{array} \right. \end{aligned} \end{aligned}$$
(1.1)

where \(\nu _k\) and \(\gamma _k\) are random variables, taking values 0 or 1, and they are used to describe the packet losses in the communication channels. \(\phi \) denotes empty set. The remaining parameters and symbols are the same as those in the traditional systems.

The optimal estimator and LQG controller for the TCP-like systems are given in Algorithms 1.3 and 1.4, respectively.

figure c
figure d

C. Suboptimal Estimator and Control for the UDP-Like NCSs

Consider the discrete-time system with the UDP-like communication architecture as in Fig. 1.4, i.e., the UDP-like system, whose system and observation equations are the same as that of the TCP-like system in (1.1). For such system, the optimal estimator and LQG controller will be studied in Chap. 2. The suboptimal solutions on the state estimation and LQG controller developed in the literature mentioned above are formulated in the following algorithms.

figure e
figure f
figure g

D. Suboptimal Control of the Quasi-TCP-Like NCSs

Consider the discrete-time system taking the same system and observation equations as that of the TCP-like system in (1.1) but with the communication architecture as in Fig. 1.5 (i.e., the Quasi-TCP-like system), where \(\tau _k\), a random variable taking values 0 or 1 describes the packet losses in the acknowledgment communication channels. For such system, the optimal estimator and LQG controller will be studied in Chap. 8. The suboptimal LQG controllers mentioned in the above literature are given in the following algorithms.

figure h
figure i

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Lin, H., Su, H., Shi, P., Shu, Z., Wu, ZG. (2017). Introduction. In: Estimation and Control for Networked Systems with Packet Losses without Acknowledgement. Studies in Systems, Decision and Control, vol 77. Springer, Cham. https://doi.org/10.1007/978-3-319-44212-9_1

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