A minimal polynomial basis solution to residual generation for fault diagnosis in linear systems

Automatica - Tập 37 - Trang 1417-1424 - 2001
Erik Frisk1, Mattias Nyberg1
1Department of Electrical Engineering, Linköping University, Linköping, Sweden

Tài liệu tham khảo

Chen, 1984 Chen, 1999 Chow, 1984, Analytical redundancy and the design of robust failure detection systems, IEEE Transactions on Automatic Control, 29, 603, 10.1109/TAC.1984.1103593 Ding, 1990, Fault detection via factorization approach, Systems and Control Letters, 14, 431, 10.1016/0167-6911(90)90094-B Ding, 1999, A characterization of parity space and its application to robust fault detection, IEEE Transactions on Automatic Control, 44, 337, 10.1109/9.746262 Forney, 1975, Minimal bases of rational vector spaces, with applications to multivariable linear systems, SIAM Journal of Control, 13, 493, 10.1137/0313029 Frank, 1990, Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results, Automatica, 26, 459, 10.1016/0005-1098(90)90018-D Frank, 1994, Frequency domain approach to optimally robust residual generation and evaluation for model-based fault diagnosis, Automatica, 30, 789, 10.1016/0005-1098(94)90169-4 Frisk, E. (1998). Residual generation for fault diagnosis: Nominal and robust design. Licentiate thesis LIU-TEK-LIC-1998:74, Linköping University. Frisk, E. (2000). Order of residual generators—bounds and algorithms. SAFEPROCESS’2000, Budapest, Hungary, pp. 599–604. Frisk, E., & Nyberg, M. (1999). Using minimal polynomial bases for fault diagnosis, European Control Conference, Karlsruhe, Germany. Gertler, J. (1991). Analytical redundancy methods in fault detection and isolation; survey and synthesis, IFAC Fault Detection, Supervision and Safety for Technical Processes, Baden-Baden, Germany, pp. 9–21. Gertler, 1990, Detection and diagnosis of plant failures: the orthogonal parity equation approach, Control and Dynamic Systems, 37, 159, 10.1016/B978-0-12-012737-5.50010-4 Kailath, T. (1980). Linear systems. Englewood Cliffs, NJ: Prentice-Hall, ISBN 0-13-536961-4. Maciejowski, 1989 Magni, 1994, On residual generation by observer and parity space approaches, IEEE Transactions on Automatic Control, 39, 441, 10.1109/9.272354 Massoumnia, 1989, Failure detection and identification, IEEE Transactions on Automatic Control, AC-34, 316, 10.1109/9.16422 Mironovskii, 1980, Functional diagnosis of linear dynamic systems, Automation and Remote Control, 40, 1198 Nikoukhah, 1994, Innovations generation in the presence of unknown inputs: Application to robust failure detection, Automatica, 30, 1851, 10.1016/0005-1098(94)90047-7 Nyberg, M. (1999). Model based fault diagnosis: methods, theory, and automotive engine applications. Ph.D. thesis, Linköping University. Nyberg, M., & Frisk, E. (2000). A derivation of the minimal polynomial basis approach to linear residual generation, Technical report, ISY, Linköping, Sweden. Nyberg, 2000, A universal Chow–Willsky scheme and detectability criteria, IEEE Transactions on Automatic Control, 45, 152, 10.1109/9.827374 The Polynomial Toolbox 2.0 for Matlab 5. Polyx, Czech Republic. URL: http://www.polyx.com, 1998. Strijbos, R. C. W. (1996). Calculation of right matrix fraction descriptions; an algorithm. Proceedings of the Fourth IEEE Mediterranean symposium on new directions in control and automation, Maleme, Krete, Greece, pp. 478–482. Viswanadham, 1987, A frequency-domain approach to failure detection and isolation with application to GE-21 turbine engine control systems, Control—Theory and Advanced Technology, 3, 45 Wünnenberg, J. (1990). Observer-based fault detection in dynamic systems, Ph.D. thesis, University of Duisburg.