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2016 | 26 | 4 | 827-840
Tytuł artykułu

Switching time estimation and active mode recognition using a data projection method

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper proposes a data projection method (DPM) to detect a mode switching and recognize the current mode in a switching system. The main feature of this method is that the precise knowledge of the system model, i.e., the parameter values, is not needed. One direct application of this technique is fault detection and identification (FDI) when a fault produces a change in the system dynamics. Mode detection and recognition correspond to fault detection and identification, and switching time estimation to fault occurrence time estimation. The general principle of the DPM is to generate mode indicators, namely, residuals, using matrix projection techniques, where matrices are composed of input and output measured data. The DPM is presented in detail, and properties of switching detectability (fault detectability) and discernability between modes (fault identifiability) are characterized and discussed. The great advantage of this method, compared with other techniques in the literature, is that it does not need the model parameter values and thus can be applied to systems of the same type without identifying their parameters. This is particularly interesting in the design of generic embedded fault diagnosis algorithms.
Rocznik
Tom
26
Numer
4
Strony
827-840
Opis fizyczny
Daty
wydano
2016
otrzymano
2015-07-11
poprawiono
2016-03-01
poprawiono
2016-06-06
zaakceptowano
2016-06-11
Twórcy
autor
  • CRIStAL-Research Center in Computer Science, Signals and Automatic Control of Lille, UMR 9189, CNRS, University of Lille, F-59000 Lille, France
  • CRIStAL-Research Center in Computer Science, Signals and Automatic Control of Lille, UMR 9189, CNRS, University of Lille, F-59000 Lille, France
  • CRIStAL-Research Center in Computer Science, Signals and Automatic Control of Lille, UMR 9189, CNRS, University of Lille, F-59000 Lille, France
Bibliografia
  • Akhenak, A., Bako, L., Duviella, E., Pekpe, K.M. and Lecoeuche, S. (2008). Fault diagnosis for switching system using observer Kalman filter identification, Proceedings of the 17th IFAC World Congress, Seoul, Korea, pp. 10142-10147.
  • Anderson, B.D.O., Brinsmead, T., Liberzon, D. and Morse, A.S. (2001). Multiple model adaptive control with safe switching, International Journal of Adaptive Control and Signal Processing 15(5): 445-470, DOI:10.1002/acs.684.
  • Antsaklis, P.J. (2000). A brief introduction to the theory and applications of hybrid systems, Proceedings of the IEEE 88(7): 887-897.
  • Bayoudh, M. and Travé Massuyès, L. (2014). Diagnosability analysis of hybrid systems cast in a discrete-event framework, Discrete Event Dynamic Systems 24(3): 309-338.
  • Belkhiat, D.E.C. (2011). Diagnosis of a Class of Switching Linear Systems: Robust Observer Based Approach, Ph.D. thesis, University of Reims Champagne Ardenne, Reims.
  • Cocquempot, V., El Mezyani, T. and Staroswiecki, M. (2004). Fault detection and isolation for hybrid systems using structured parity residuals, IEEE/IFAC-ASCC, 5th Asian Control Conference, Melbourne, Victoria, Australia, pp. 1204-1212, DOI:10.1109/ASCC.2004.18502.
  • Daizhan, C. (2007). Controlability of switched systems, IFAC Proceedings Volumes 40(12): 194-201.
  • Domlan, E.A., Ragot, J. and Maquin, D. (2007a). Active mode estimation for switching systems, American Control Conference, New York City, NY, USA, pp. 1143-1148.
  • Domlan, E.A., Ragot, J. and Maquin, D. (2007b). Switching systems: Active mode recognition, identification of the switching law, Journal of Control Science and Engineering 2007: 1-11, Article ID: 50796, DOI:10.1155/2007/50796.
  • El Mezyani, T. (2005). Methodology for Fault Detection and Isolation in Hybrid Dynamic Systems, Ph.D. thesis, Université Lille1, Lille, France.
  • Engell, S., Kowalewski, S., Schulz, C. and Strusberg, O. (2000). Continuous discrete interactions in chemical processing plants, Proceedings of the IEEE 88(7): 1050-1068.
  • Goebel, R., Ricardo Sanfelice, G. and Andrew Teel, R. (2012). Hybrid Dynamical Systems: Modeling, Stability, and Robustness, Princeton University Press, Princeton, NJ.
  • Heemels, W.P.M.H., De Schutter, B. and Bemporad, A. (2001). Equivalence of hybrid dynamical models, Automatica 37(7), 1085-1091, DOI: 10.1016/S0005-1098(01)00059-0.
  • Hespanha, J.P. and Morse, A.S. (1999). Stability of switched systems with average dwell-time, 38th IEEE Conference on Decision and Control, Phoenix, AZ, USA, Vol. 3, pp. 2655-2660.
  • Hofbaur, M., Travé-Massuyès, L., Rienmüller, T. and Bayoudh, M. (2010). Overcoming non-discernibility through mode-sequence analytic redundancy relations in hybrid diagnosis and estimation, 21st International Workshop on Principles of Diagnosis DX-10, Portland, OR, USA, pp. 1-7.
  • Kailath, T. (1980). Linear Systems, Englewood Cliffs, NJ.
  • Liberzon, D. (2005). Switched Systems, Birkhauser, Boston, MA.
  • Lin, H. and Antsaklis, J.P. (2009). Stability and stabilizability of switched linear systems: A survey of recent results, IEEE Transactions on Automatic Control 54(2): 308-322.
  • Livadas, C., Lygeros, J. and Lynch, N.A. (2000). High-level modeling and analysis of the traffic alert and collision avoidance system (TCAS), Proceedings of the IEEE, 88(7): 926-948.
  • Ma, Y., Kawakami, H. and Tse, C.K. (2004). Bifurcation analysis of switched dynamical systems with periodically moving borders, IEEE Transactions on Circuits and Systems 51(6): 1184-1193.
  • Mitsubori, K. and Saito, T. (1997). Dependent switched capacitor chaos generator and its synchronization, IEEE Transactions on Circuits and Systems 44(12): 1122-1128.
  • Narasimhan, S. and Biswas, G. (2007). Model-based diagnosis of hybrid systems, IEEE Transaction on Systems, Man, and Cybernetics A: Systems and Humans 37(3): 348-361, DOI:10.1109/TSMCA.2007.893487.
  • Pekpe, K.M., Mourot, G. and Ragot, J. (2006). Subspace method for sensor fault detection and isolation-application to grinding circuit monitoring, 11th IFAC Symposium on automation in Mining, Mineral and Metal Processing, Nancy, France, pp. 47-52.
  • Petroff, B.N. (2007). Biomimetic Sensing for Robotic Manipulation, Ph.D. thesis, Graduate School of the University of Notre Dame, Notre Dame, IN.
  • Torikai, H. and Saito, T. (1998), Synchronization of chaos and its itinerancy from a network by occasional linear connection, IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 45(4): 464-472.
  • Van Overschee, P. and De Moor, B. (1996), Subspace Identification for Linear Systems Theory: Implementation and Applications, Kluwer Academic Publishers, Boston, MA.
  • Williams, S.M. and Hoft, R.G. (1991), Adaptive frequency domain control of ppm switched power line conditioner, IEEE Transactions on Power Electronics 6(4): 665-670.
  • Yang, H., Jiang, B. and Cocquempot, V. (2010), Fault tolerant control and hybrid systems, in H. Yang et al. (Eds.), Fault Tolerant Control Design for Hybrid Systems, Springer Verlag, Berlin/Heidelberg.
  • Zhang, W., Hu, J. and Lu, Y.H. (2007), Optimal power modes scheduling using hybrid systems, Proceedings of the American Control Conference, New York City, NY, USA, pp. 2781-2786.
Typ dokumentu
Bibliografia
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