Abstract
This paper describes a methodology for simultaneous identification of fault parame-ters and mode switching events for hybrid systems. The method is developed based on the notion of Global Analytical Redundancy Relations (GARR) from the bond graph model of the hybrid system. A unified formula with mode change time sequence and initial mode coefficients (IMC) is derived to represent the mode switching. It employs Genetic Algorithm (GA) to search for fault parameters and mode switching time stamps. Fault parameters, mode switching time stamps and all IMC are encoded into one chromosome as a potential solution of the identification process. GARRs are used as a fitness index in GA search. An electro-hydraulic system of vehicle is studied to illustrate the efficiency of the proposed algorithm.
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References
Arogeti, S., Wang, D., Low, C.B., Zhang, D.H., Zhou, J.: Mode tracking of hybrid systems in FDI framework. In: The 3rd International Conference on Robotics Automation and Mechatronics, Chengdu, China, September 21-24 (2008)
Chen, H., Sun, P.Y., Guo, K.H.: A multi-objective control design for active suspensions with hard constraints. In: Proceedings of the American Control Conference, vol. 5, pp. 4371–4376 (2003)
Chen, H., Guo, K.H.: Constrained H ∞ control of active suspensions: an LMI approach. IEEE Transactions on Control Systems Technology 13(3), 412–421 (2005)
Karnopp, D.C., Margolis, D.L., Rosenberg, R.C.: System dynamics, modeling and simulation of mechatronics systems. John Wiley & Sons Inc., New Jersey (2006)
Low, C.B., Wang, D., Arogeti, S., Zhang, J.B.: Monitoring ability and quantitative fault diagnosis using hybrid bond graph. In: The 17th IFAC World Congress, Seoul, Korea, July 6-11 (2008a)
Low, C.B., Wang, D., Arogeti, S., Zhang, J.B.: Causality assignment and modeling approximation for quantitative hybrid bond graph fault diagnosis. In: The 17th IFAC World Congress, Seoul, Korea, July 6-11 (2008b)
Luo, M., Wang, D., Pham, M., Low, C.B., Zhang, J.B.: Model-based fault diagnosis/prognosis for wheeled mobile robots: a review. In: The 31st Annual Conference of IEEE Industrial Electronics Society (IECON 2005), pp. 2267–2272 (2005)
Lo, C.H., Wong, Y.K., Rad, A.B.: Intelligent system for process supervision and fault diagnosis in dynamic physical systems. IEEE Transactions on Industrial Electronics 53(2), 581–592 (2006)
Mosterman, P.J., Biswas, G.: Behavior generation using model switching: a hybrid bond graph modeling technique. Transaction of Society for Computer Simulation 27(1), 177–182 (1995)
Mak, K.L., Wong, Y.S., Wang, X.X.: An adaptive genetic algorithm for manufacturing cell formation. International Journal of Advance Manufacture Technology 16(7), 491–497 (2000)
Merritt, H.E.: Hydraulic Control Systems. Wiley, New York (1967)
Narasimhan, S., Biswas, G.: Model-based diagnosis of hybrid systems. IEEE Transactions on System, Man and Cybernetics – Part A: Systems and Humans 37(3), 348–361 (2007)
Samantaray, A.K., Medjaher, K., Bouamama, B.O., Staroswiecki, M., Tanguy, G.D.: Diagnostic bond graphs for online fault detection and isolation. Simulation Modelling Practice and Theory 14, 237–262 (2006)
Umarikar, A.C., Umanand, L.: Modelling of switched mode power converters using bond graph. IEE-Proceedings Electric Power Applications 152(1), 51–60 (2005)
Wang, J., Wang, J.D., Daw, N.Q., Wu, H.: Identification of pneumatic cylinder friction parameters using genetic algorithms. IEEE/ASME Transactions on Mechatronics 9(1), 100–107 (2004)
Zhao, F., Koutsoukos, X., Haussecker, H., Reich, J., Cheung, P.: Monitoring and fault diagnosis of hybrid systems. IEEE Transactions on System, Man and Cybernetics– Part B: Cybernetics 35(6), 1225–1240 (2005)
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Yu, M., Luo, M., Arogeti, S., Wang, D., Zhang, X. (2009). Fault and Mode Switching Identification for Hybrid Systems with Application to Electro-Hydraulic System in Vehicles. In: Budiyono, A., Riyanto, B., Joelianto, E. (eds) Intelligent Unmanned Systems: Theory and Applications. Studies in Computational Intelligence, vol 192. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00264-9_17
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DOI: https://doi.org/10.1007/978-3-642-00264-9_17
Publisher Name: Springer, Berlin, Heidelberg
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