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Interval observer-based fault detectability analysis using mixed set-invariance theory and sensitivity analysis approach. (English) Zbl 1482.93221

Summary: This paper addresses the characterisation of the minimum detectable fault (MDF) by means of residual sensitivity integrated with the set-invariance theory when using an interval observer-based approach as a fault detection (FD) scheme. Uncertainties (disturbances and noise) are considered as of unknown but bounded nature (i.e. in the set-membership framework). A zonotopic-set representation towards reducing set operations to simple matrix calculations is utilised to bound the state/output estimations provided by the interval observer-based approach. In order to show the connection between sensitivity and set-invariance analyses, mathematical expressions of the MDF are derived when considering different types of faults. Finally, a simulation case study based on a quadruple-tank system is employed to both illustrate and discuss the effectiveness of the proposed approach. The interval observer-based FD scheme is used to test the MDF obtained from the integration of both residual sensitivity analysis and set-invariance theory in the considered case study.

MSC:

93B53 Observers
93C55 Discrete-time control/observation systems
93C05 Linear systems in control theory

References:

[1] Alamo, T.; Bravo, J. M.; Camacho, E. F., Guaranteed state estimation by zonotopes, Automatica, 41, 6, 1035-1043 (2005) · Zbl 1091.93038 · doi:10.1016/j.automatica.2004.12.008
[2] Artstein, Z.; Raković, S. V., Feedback and invariance under uncertainty via set-iterates, Automatica, 44, 2, 520-525 (2008) · Zbl 1283.93167 · doi:10.1016/j.automatica.2007.06.013
[3] Blanke, M.; Kinnaert, M.; Lunze, J.; Staroswiecki, M.; Schröder, J., Diagnosis and fault-tolerant control (2006), Berlin: Springer, Berlin · Zbl 1126.93004
[4] Cai, J.; Ferdowsi, H.; Sarangapani, J., Model-based fault detection, estimation, and prediction for a class of linear distributed parameter systems, Automatica, 66, 122-131 (2016) · Zbl 1335.93030 · doi:10.1016/j.automatica.2015.12.028
[5] Chai, W.; Qiao, J., Passive robust fault detection using RBF neural modeling based on set membership identification, Engineering Applications of Artificial Intelligence, 28, 1-12 (2014) · doi:10.1016/j.engappai.2013.10.005
[6] Chen, J.; Patton, R. J., Robust model-based fault diagnosis for dynamic systems (1999), New York: Kluwer Academic Press, New York · Zbl 0920.93001
[7] Combastel, C. (2003). A state bounding observer based on zonotopes. Paper presented at the European Control Conference (ECC) (pp. 2589-2594).
[8] Combastel, C., Zonotopes and Kalman observers: Gain optimality under distinct uncertainty paradigms and robust convergence, Automatica, 55, 265-273 (2015) · Zbl 1377.93161 · doi:10.1016/j.automatica.2015.03.008
[9] Ding, S., Model-based fault diagnosis techniques: Design schemes, algorithms, and tools (2008), London: Springer Science and Business Media, London
[10] Fagarasan, I.; Ploix, S.; Gentil, S., Causal fault detection and isolation based on a set-membership approach, Automatica, 40, 12, 2099-2110 (2004) · Zbl 1075.93009
[11] Gertler, J., Fault detection and diagnosis in engineering systems (1998), Boca Raton, FL: CRC Press, Boca Raton, FL
[12] Johansson, K. H., The quadruple-tank process: A multivariable laboratory process with an adjustable zero, IEEE Transactions on Control Systems Technology, 8, 3, 456-465 (2000) · doi:10.1109/87.845876
[13] Kodakkadan, A. R., Pourasghar, M., Puig, V., Olaru, S., Ocampo-Martinez, C., & Reppa, V. (2017). Observer-based sensor fault detectability: About robust positive invariance approach and residual sensitivity. Paper prsented at the 20th world congress of the International Federation of Automatic Control (IFAC) (pp. 5041-5046). France.
[14] Kofman, E., Non-conservative ultimate bound estimation in LTI perturbed systems, Automatica, 41, 10, 1835-1838 (2005) · Zbl 1087.93048 · doi:10.1016/j.automatica.2005.04.024
[15] Kofman, E.; Haimovich, H.; Seron, M. M., A systematic method to obtain ultimate bounds for perturbed systems, International Journal of Control, 80, 2, 167-178 (2007) · Zbl 1140.93428 · doi:10.1080/00207170600611265
[16] Kolmanovsky, I.; Gilbert, E. G., Theory and computation of disturbance invariant sets for discrete-time linear systems, Mathematical Problems in Engineering, 4, 4, 317-367 (1998) · Zbl 0923.93005 · doi:10.1155/S1024123X98000866
[17] Lalami, A., & Combastel, C. (2006). Generation of set membership tests for fault diagnosis and evaluation of their worst case sensitivity. In Fault Detection, Supervision and Safety of Technical Processes (SAFEPROCESS) (pp. 569-574). Amsterdam: Elsevier.
[18] Meseguer, J.; Puig, V.; Escobet, T.; Saludes, J., Observer gain effect in linear interval observer-based fault detection, Journal of Process Control, 20, 8, 944-956 (2010) · doi:10.1016/j.jprocont.2010.06.017
[19] Ocampo-Martinez, C.; De Doná, J. A.; Seron, M., Actuator fault-tolerant control based on set separation, International Journal of Adaptive Control and Signal Processing, 24, 12, 1070-1090 (2010) · Zbl 1207.94093 · doi:10.1002/acs.1181
[20] Pan, Y.; Yang, G.-H., Event-triggered fault detection filter design for nonlinear networked systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48, 11, 1851-1862 (2018) · doi:10.1109/TSMC.2017.2719629
[21] Pourasghar, M., Puig, V., & Ocampo-Martinez, C. (2016). Characterization of the minimum detectable fault of interval observers by using set-invariance theory. Paper presented at the 3rd conference on Control and Fault-Tolerant Systems (SysTol) (pp. 79-86). Spain.
[22] Puig, V., Fault diagnosis and fault tolerant control using set-membership approaches: Application to real case studies, International Journal of Applied Mathematics and Computer Science, 20, 4, 619-635 (2010) · Zbl 1214.93061 · doi:10.2478/v10006-010-0046-y
[23] Puig, V.; Montes de Oca, S.; Blesa, J., Adaptive threshold generation in robust fault detection using interval models: time-domain and frequency-domain approaches, International Journal of Adaptive Control and Signal Processing, 27, 10, 873-901 (2013) · Zbl 1278.93061
[24] Puig, V.; Quevedo, J.; Escobet, T.; de las Heras, S., Passive robust fault detection approaches using interval models, IFAC Proceedings Volumes, 35, 1, 443-448 (2002) · doi:10.3182/20020721-6-ES-1901.00407
[25] Puig, V.; Quevedo, J.; Escobet, T.; Stancu, A., Robust fault detection using linear interval observers, IFAC Proceedings Volumes, 36, 5, 579-584 (2003) · doi:10.1016/S1474-6670(17)36554-0
[26] Raïssi, T.; Efimov, D.; Zolghadri, A., Interval state estimation for a class of nonlinear systems, IEEE Transactions on Automatic Control, 57, 1, 260-265 (2012) · Zbl 1369.93074 · doi:10.1109/TAC.2011.2164820
[27] Rakovic, S. V.; Kerrigan, E. C.; Kouramas, K. I.; Mayne, D. Q., Invariant approximations of the minimal robust positively invariant set, IEEE Transactions on Automatic Control, 50, 3, 406-410 (2005) · Zbl 1365.93122 · doi:10.1109/TAC.2005.843854
[28] Seron, M. M.; De Doná, J. A., Actuator fault tolerant multi-controller scheme using set separation based diagnosis, International Journal of Control, 83, 11, 2328-2339 (2010) · Zbl 1210.93038 · doi:10.1080/00207179.2010.520032
[29] Seron, M. M.; Zhuo, X. W.; De Doná, J. A.; Martínez, J. J., Multisensor switching control strategy with fault tolerance guarantees, Automatica, 44, 1, 88-97 (2008) · Zbl 1138.93352 · doi:10.1016/j.automatica.2007.05.024
[30] Shen, B.; Ding, S. X.; Wang, Z., Finite-horizon \(####\) fault estimation for linear discrete time-varying systems with delayed measurements, Automatica, 49, 1, 293-296 (2013) · Zbl 1257.93093 · doi:10.1016/j.automatica.2012.09.003
[31] Silvestre, D.; Rosa, P.; Hespanha, J. P.; Silvestre, C., Fault detection for LPV systems using set-valued observers: A coprime factorization approach, Systems and Control Letters, 106, 32-39 (2017) · Zbl 1376.93035 · doi:10.1016/j.sysconle.2017.05.007
[32] Stoican, F., Hovd, M., & Olaru, S. (2013). Explicit invariant approximation of the mRPI set for LTI dynamics with zonotopic disturbances. Paper presented at the 52nd Annual Conference on Decision and Control (CDC), Florence, Italy (pp. 3237-3242).
[33] Tabatabaeipour, S. M., Active fault detection and isolation of discrete-time linear time-varying systems: A set-membership approach, International Journal of Systems Science, 46, 11, 1917-1933 (2015) · Zbl 1332.94121 · doi:10.1080/00207721.2013.843213
[34] Tabatabaeipour, S. M.; Bak, T., Robust observer-based fault estimation and accommodation of discrete-time piecewise linear systems, Journal of the Franklin Institute, 351, 1, 277-295 (2014) · Zbl 1293.93725 · doi:10.1016/j.jfranklin.2013.08.021
[35] Tan, C.; Tao, G.; Qi, R., A discrete-time parameter estimation based adaptive actuator failure compensation control scheme, International Journal of Control, 86, 2, 276-289 (2013) · Zbl 1278.93253 · doi:10.1080/00207179.2012.723828
[36] Thabet, R. E. H.; Combastel, C.; Raïssi, T.; Zolghadri, A., Set-membership fault detection under noisy environment with application to the detection of abnormal aircraft control surface positions, International Journal of Control, 88, 9, 1878-1894 (2015) · Zbl 1338.93058 · doi:10.1080/00207179.2015.1023740
[37] Uusitalo, L.; Lehikoinen, A.; Helle, I.; Myrberg, K., An overview of methods to evaluate uncertainty of deterministic models in decision support, Environmental Modelling and Software, 63, 24-31 (2015) · doi:10.1016/j.envsoft.2014.09.017
[38] Xu, F.; Puig, V.; Ocampo-Martinez, C.; Olaru, S.; Stoican, F., Set-theoretic methods in robust detection and isolation of sensor faults, International Journal of Systems Science, 46, 13, 2317-2334 (2015) · Zbl 1333.93153 · doi:10.1080/00207721.2014.989293
[39] Xu, F., Stoican, F., Puig, V., Ocampo-Martinez, C., & Olaru, S. (2013). On the relationship between interval observers and invariant sets in fault detection. Paper presented at the Control and Fault-Tolerant Systems (SysTol), Nice, France (pp. 49-54).
[40] Xu, F.; Tan, J.; Wang, X.; Puig, V.; Liang, B.; Yuan, B.; Liu, H., Generalized set-theoretic unknown input observer for LPV systems with application to state estimation and robust fault detection, International Journal of Robust and Nonlinear Control, 27, 17, 3812-3832 (2017) · Zbl 1386.93058
[41] Zhong, M.; Ding, S. X.; Lam, J.; Wang, H., An LMI approach to design robust fault detection filter for uncertain LTI systems, Automatica, 39, 3, 543-550 (2003) · Zbl 1036.93061 · doi:10.1016/S0005-1098(02)00269-8
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