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Tytuł artykułu

On some ways to implement state-multiplicative fault detection in discrete-time linear systems

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
New design conditions on the observer based residual filter design for the linear discrete-time linear systems with zoned system parameter faults are presented. With respect to time evolution of residual signals and with a guarantee of their robustness, the design task is stated in terms of linear matrix inequalities, while the recursive implementation of algorithms is motivated by the platform existence for real-time processing. A major objective is to analyze the configuration required and, in particular, a new characterization of the norm boundaries of the multiplicative zonal parametric faults to be projected onto the structure of the set of linear matrix inequalities.
Rocznik
Strony
229--240
Opis fizyczny
Bibliogr. 32 poz., wykr.
Twórcy
  • Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Letná, 04200 Košice, Slovakia
  • Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Letná, 04200 Košice, Slovakia
Bibliografia
  • [1] Baïkeche, H., Marx, B., Maquin, D., and Ragot, J. (2006). On parametric and nonparametric fault detection in linear closed-loop systems, 4th Workshop on Advanced Control and Diagnosis, Nancy, France, pp. 1–6.
  • [2] Borutzky, W. (2021). Bond Graph Modelling for Control, Fault Diagnosis and Failure Prognosis, Springer, Cham.
  • [3] Chen, W., Khan, A.Q., Abid, M., and Ding, S.X. (2011). Integrated design of observer based fault detection for a class of uncertain nonlinear systems, International Journal of Applied Mathematics and Computer Science 21(3): 423–430, DOI: 10.2478/v10006-011-0031-0.
  • [4] Chiang, L.H., Russell, E.L., and Braatz, R.D. (2001). Fault Detection and Diagnosis in Industrial Systems, Springer, London.
  • [5] De Oliveira, M.C., Geromel, J.C., and Bernussou, J. (2002). Extended H2 and H∞ norm characterizations and controller parametrizations for discrete-time systems, International Journal of Control 75(9): 666–679.
  • [6] Ding, S. (2021). Advanced Methods for Fault Diagnosis and Fault-tolerant Control, Springer, Cham.
  • [7] Doraiswami, R. and Cheded, L. (2012). Kalman filter for parametric fault detection. An internal model principle-based approach, IET Control Theory and Applications 6(5): 715–725.
  • [8] Döhler, M., Mevel, L., and Zhang, Q. (2016) Fault detection, isolation and quantification from Gaussian residuals with application to structural damage diagnosis, Annual Reviews in Control 42(C): 244–256.
  • [9] Ellis, G. (2002). Observers in Control Systems: A Practical Guide, Academic Press, San Diego.
  • [10] Felicio, P.A.S.A. and Lourtie, P.M.G. (2006). Applicability of standard formulation parametric fault detection methods, 14th Mediterranean Conference on Control and Automation, Ancona, Italy, pp. 1–6.
  • [11] Ferdowsi, H., Jagannathan, S. (2011). Unified model-based fault diagnosis scheme for nonlinear discrete-time systems with additive and multiplicative faults, 50th IEEE Conference on Decision and Control and European Control Conference, Orlando, USA, pp. 1570–1575.
  • [12] Filasová, A., Krokavec, D., and Liššinský, P. (2016). Conditions with D-stability circle area in design of observer-based fault estimation, Applied Mathematical Sciences 10(35): 1705–1717.
  • [13] Gao, Z. (2015). Fault estimation and fault-tolerant control for discrete-time dynamic systems, IEEE Transactions on Industrial Electronics 62(4): 3874–3884.
  • [14] Gao, C. and Duan, G. (2012). Robust adaptive fault estimation for a class of nonlinear systems subject to multiplicative faults, Circuits, Systems, and Signal Processing 31(6): 2035–2046.
  • [15] Gershon, E., Shaked, U., and Yaesh, I. (2005). H∞ Control and Estimation of State-multiplicative Linear Systems, Springer, London.
  • [16] Gertler, J. (1998). Fault Detection and Diagnosis in Engineering Systems, CRC Press, Boca Raton.
  • [17] Gil, P., Santos, F., Palma, L., and Cardoso, A. (2015). Recursive subspace system identification for parametric fault detection in nonlinear systems, Applied Soft Computing 37(C): 444–455.
  • [18] Hamdi, H., Rodrigues, M., Rabaoui, B., and Benhadj Braiek, N. (2021). A fault estimation and fault–tolerant control based sliding mode observer for LPV descriptor systems with time delay, International Journal of Applied Mathematics and Computer Science 31(2): 247–258, DOI: 10.34768/amcs-2021-0017.
  • [19] Hogben, L. (2007), Handbook of Linear Algebra, Chapman & Hall/CRC, Boca Raton.
  • [20] Huang, L., Ren, H., Chai, Y., and Qu, J. (2021). A fault detection method based on stacking the SAE-SRBM for nonstationary and stationary hybrid processes, International Journal of Applied Mathematics and Computer Science 31(1): 29–43, DOI: 10.34768/amcs-2021-0003.
  • [21] Khargonekar, P.P. and Petersen, I.R. (1990). Robust stabilization of uncertain linear systems: Quadratic stabilizability and H∞ control theory, IEEE Transactions on Automatic Control 35(3): 356–361.
  • [22] Kim, K.S. and Rew, K.H. (2013). Reduced order disturbance observer for discrete-time linear systems, Automatica 49(4): 968–975.
  • [23] Korovin, S.K. and Fomichev, V.V. (2009). State Observers for Linear Systems with Uncertainty, De Gruyter, Berlin.
  • [24] Krokavec, D. and Filasová, A. (2019a). H∞ norm principle in residual filter design for discrete-time linear positive systems, European Journal of Control 45: 17–29.
  • [25] Krokavec, D. and Filasová, A. (2019b). On fault detection for discrete-time linear state-multiplicative systems with uncorrelated multiplicative faults, 6th International Conference on Control, Decision and Information Technologies, Paris, France, pp. 894-899.
  • [26] Krokavec, D. and Filasová, A. (2020). Detection of state-multiplicative faults in discrete-time linear systems, in A. Bartoszewicz et al. (Eds), Advances in Intelligent Systems and Computing, Springer, Cham, pp. 1424–1433.
  • [27] Krokavec, D. and Filasová, A. (2021). Quadratic stabilization of linear uncertain positive discrete-time systems, Symmetry 13(9): 1–20.
  • [28] Luenberger, D.G. (1979). Introduction to Dynamic Systems: Theory, Models and Applications, Wiley, New York.
  • [29] Park, Y.J., Fan, S.K.S., and Hsu, C.Y. (2020). A review on fault detection and process diagnostics in industrial processes, Processes 8(9): 1–26.
  • [30] Sun, Z. and Yang, Z. (2014). Joint parametric fault diagnosis and state estimation using KF-ML method, IFAC Proceedings Volumes 47(3): 8293–8298.
  • [31] Wu, C., Qi, J., Song, D., Qi, X., and Han, J. (2015). Simultaneous state and parameter estimation based actuator fault detection and diagnosis for an unmanned helicopter, International Journal of Applied Mathematics and Computer Science 25(1): 175–187, DOI: 10.1515/amcs-2015-0013.
  • [32] Zhong, M., Ma, C., and Ding, S.X. (2005). Design of parametric fault detection systems: An H-infinity optimization approach, Journal of Control Theory and Applications 2(1): 35–41.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b13e927a-79a8-4b2a-8416-ee136e822f79
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