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Tytuł artykułu

State filtering for networked control systems subject to switching disturbances

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
State estimation of stochastic discrete-time linear systems subject to unknown inputs has been widely studied, but few works take into account disturbances switching between unknown inputs and constant biases. We show that such disturbances affect a networked control system subject to deception attacks on the control signals transmitted by the controller to the plant via unreliable networks. This paper proposes to estimate the switching disturbance from an augmented state version of the intermittent unknown input Kalman filter. The sufficient stochastic stability conditions of the obtained filter are established when the arrival binary sequence of data losses follows a Bernoulli random process.
Rocznik
Strony
473--482
Opis fizyczny
Bibliogr. 38 poz., rys., wykr.
Twórcy
autor
  • MACS Laboratory: Modeling, Analysis and Control of Systems, National Engineering School of Gabes (ENIG), University of Gabes, 6029 Gabes, Tunisia
autor
  • MACS Laboratory: Modeling, Analysis and Control of Systems, National Engineering School of Gabes (ENIG), University of Gabes, 6029 Gabes, Tunisia
autor
  • Research Center for Automatic Control of Nancy, Lorraine University, CRAN UMR 7039, BP 70239, Vandeouvre les Nancy, France
autor
  • Research Center for Automatic Control of Nancy, Lorraine University, CRAN UMR 7039, BP 70239, Vandeouvre les Nancy, France
Bibliografia
  • [1] Alouani, A., Rice, T. and Blair, W. (1992). A two-stage filter for state estimation in the presence of dynamical stochastic bias, Proceedings of the American Control Conference, Chicago, IL, USA, pp. 1784–1788.
  • [2] Amin, S., Cárdenas, A.A. and Sastry, S.S. (2009). Safe and secure networked control systems under denial-of-service attacks, Proceedings of the 12th International Conference on HSCC ’09, San Francisco, CA, USA, pp. 31–45.
  • [3] Ben Hmida, F., Khémiri, K., Ragot, J. and Gossa, M. (2010). Robust filtering for state and fault estimation of linear stochastic systems with unknown disturbance, Mathematical Problems in Engineering 2010, Article ID: 591639.
  • [4] Bixiang, T., Alvergue, L. and Guoxiang, G. (2015). Secure networked control systems against replay attacks without injecting authentication noise, Proceedings of the American Control Conference, Chicago, IL, USA, pp. 6028–6033.
  • [5] Blanke, M., Kinnaert, M., Lunze, J., Staroswiecki, M. and Schröder, J. (2006). Diagnosis and Fault-Tolerant Control, Springer, New York, NY.
  • [6] Censi, A. (2011). Kalman filtering with intermittent observations: Convergence for semi-Markov chains and an intrinsic performance measure, IEEE Transactions on Automatic Control 56(2): 376–381.
  • [7] Chabir, K., Sauter, D., Al-Salami, I.-M. and Abdelkrim, M.-N. (2010). Two-stage Kalman filter for simultaneous fault and delay estimation in networked control systems, Proceedings of the 18th Mediterranean Conference on Control and Automation, Marrakech, Morocco, pp. 249–254.
  • [8] Chabir, K., Sauter, D., Ben Gayed, M.-K. and Abdelkrim, M.-N. (2008). Design of an adaptive Kalman filter for fault detection of networked control systems, Proceedings of the 16th Mediterranean Conference on Control and Automation, Ajaccio, France, pp. 1124–1129.
  • [9] Chabir, K., Sid, M.A. and Sauter, D. (2014). Fault diagnosis in a networked control system under communication constraints: A quadrotor application, International Journal of Applied Mathematics and Computer Science 24(4): 809–820, DOI: 10.2478/amcs-2014-0060.
  • [10] Chen, J. and Patton R.J. (1996). Optimal filtering and robust fault diagnosis of stochastic systems with unknown disturbances, IEE Proceedings—Control Theory and Applications 143(1): 31–36.
  • [11] Darouach, M. and Zasadzinski, M. (1997). Unbiased minimum variance estimation for systems with unknown exogenous inputs, Automatica 33(4): 717–719.
  • [12] Darouach, M., Zasadzinski, M. and Keller, J. (1992). State estimation for discrete systems with unknown inputs using state estimation of singular systems, Proceedings of the American Control Conference, Chicago, IL, USA, pp. 3014–3015.
  • [13] Fang, H., Shi, Y. and Yi, J. (2011). On stable simultaneous input and state estimation for discrete-time linear systems, International Journal of Adaptive Control and Signal Processing 25(8): 671–686.
  • [14] Friedland, B. (1969). Treatment of bias in recursive filtering, IEEE Transactions on Automatic Control 14(4): 359–367.
  • [15] Gillijns, S. and De Moor, B. (2007). Unbiased minimum-variance input and state estimation for linear discrete-time systems with direct feedthrough, Automatica 43(5): 934–937.
  • [16] Hespanha, J.P., Naghshtabrizi, P. and Xu, Y. (2007). A survey of recent results in networked control systems, Proceedings of the IEEE 95(1): 138.
  • [17] Hou, M. and Patton, R. (1998). Optimal filtering for systems with unknown inputs, IEEE Transactions on Automatic Control 43(3): 445–449.
  • [18] Hsieh, C.-S. and Chen, F.-C. (1999). Optimal solution of the two-stage Kalman estimator, IEEE Transactions on Automatic Control 44(1): 194–199.
  • [19] Kailath, T., Sayed, A.H. and Hassibi, B. (2000). Linear Estimation, Prentice-Hall, Englewood Cliffs, NJ.
  • [20] Keller, J.-Y., Chabir, K. and Sauter, D. (2016). Input reconstruction for networked control systems subject to deception attacks and data losses on control signals, International Journal of Systems Science 47(4): 814–820.
  • [21] Keller, J.-Y. and Sauter, D. (2011). Restricted diagonal detection filter and updating strategy for multiple fault detection and isolation, International Journal of Adaptive Control and Signal Processing 25(1): 68–87.
  • [22] Keller, J.-Y. and Sauter, D. (2013). Kalman filter for discrete-time stochastic linear systems subject to intermittent unknown inputs, IEEE Transactions on Automatic Control 58(7): 1882–1887.
  • [23] Kim, K.H., Lee, J.G. and Park, C.G. (2006). Adaptive two-stage Kalman filter in the presence of unknown random bias, International Journal of Adaptive Control and Signal Processing 20(7): 305–319.
  • [24] Kim, Y. and Park, J. (2003). Noise response of detection filters: Relation between detection space and completion space, IEE Proceedings—Control Theory and Applications 150(4): 443–447.
  • [25] Kitanidis, P. K. (1987). Unbiased minimum-variance linear state estimation, Automatica 23(6): 775–778.
  • [26] Liu, X. and Goldsmith, A. (2004). Kalman filtering with partial observation losses, Proceedings of the 43rd IEEE Conference on Decision and Control, Nassau, The Bahamas, Vol. 4, pp. 4180–4186.
  • [27] Liu, Y., Ning, P. and Reiter, M.K. (2009). False data injection attacks against state estimation in electric power grids, Proceedings of the 16th ACM Conference on Computer and Communications Security, New York, NY, USA, pp. 21–32.
  • [28] Mo, Y. and Sinopoli, B. (2009). Secure control against replay attacks, Proceedings of the 47th Annual Allerton Conference on Communication, Control, and Computing, Monticello, IL, USA, pp. 911–918.
  • [29] Park, J., Halevi, Y. and Rizzoni, G. (1994). A new interpretation of the fault-detection filter. Part 2: The optimal detection filter, International Journal of Control 60(6): 1339–1351.
  • [30] Patton, R.J. and Chen, J. (1999). Robust Model-Based Fault Diagnosis for Dynamic Systems, Kluwer Academic Publishers, Boston, MA/London.
  • [31] Sandberg, H., Amin, S. and Johansson, K. (2015). Cyberphysical security in networked control systems: An introduction to the issue, IEEE Control Systems Magazine 35(1): 20–23.
  • [32] Sandberg, H., Amin, S. and Johansson, K. (2016). Detection of intermittent faults for linear stochastic systems subject to time-varying parametric perturbations, IET Control Theory and Applications 10(8): 903–910.
  • [33] Schenato, L., Sinopoli, B., Franceschetti, M., Poolla, K. and Sastry, S.S. (2007). Foundations of control and estimation over lossy networks, Proceedings of the IEEE 95(1): 163–187.
  • [34] Simon, D. (2006). Optimal State Estimation: Kalman, Hinfinity, and Nonlinear Approaches, Wiley, Hoboken, NJ.
  • [35] Sinopoli, B., Schenato, L., Franceschetti, M., Poolla, K., Jordan, M.I. and Sastry, S.S. (2004). Kalman filtering with intermittent observations, IEEE Transactions on Automatic Control 49(9): 1453–1464.
  • [36] Smith, R.S. (2011). A decoupled feedback structure for covertly appropriating networked control systems, Proceedings of the IFAC World Congress, Milan, Italy, pp. 90–95.
  • [37] Teixeira, A., Sandberg, H. and Johansson, K.H. (2010). Networked control systems under cyber attacks with applications to power networks, Proceedings of the American Control Conference, Baltimore, MD, USA, pp. 3690–3696.
  • [38] Zhou, D.-H., Shi, J. and He, X. (2014). Review of intermittent fault diagnosis techniques for dynamic systems, Acta Automica Sinica 40(2): 161–171.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-521e22eb-16af-4ccd-bfe1-76fcabb212be
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