Fault Tolerant Control for Manufacturing Discrete Systems by Filter and Diagnoser Interactions
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Abstract
The paper deals with an online safety mechanism to define interactions between a diagnoser and a control filter for fault tolerant control of manufacturing discrete systems. The diagnoser observes the plant behavior whereas the control filter ensures the safety from the controller. This online interaction is based by events communication where the control law is never reconfigured. The proposed approach is applied to CISPI platform from the CRAN laboratory (Research Center for Automatic Control of Nancy).
How to Cite
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diagnosis, Fault tolerant control, discrete event system
Brown D.W. and Vachtsevanos G.J. (2011). A Prognostic Health Management Based Framework for Fault- Tolerant Control. Annual Conference of the Prognostics and Health Management Society (PHM’11), Montreal, Quebec, Canada.
Cassandras C.G., Lafortune S. (1999). Introduction to discrete event systems. Kluwer Academic Publishers, Dordrecht.
Debouk R., Lafortune S. et Teneketzis D. (2000). Coordinated decentralized protocols for failure diagnosis of discrete events systems. In Journal of Discrete Event Dynamical System : Theory and Application. pp.33-86.
Faure J-M., Lesage J-J. (2001). Methods for safe control systems design and implementations. 10th IFAC Symposium on Information Control Problems in
Manufacturing, INCOM'2001, Vienna, Austria. IEC/EN 62061. Safety of machinery: Functional safety of electrical, electronic and programmable electronic control systems. (2005).
ISO13849-1. Safety of machinery. Safety-related parts of control systems. General principles for design. (2006).
Kan John P., Grastien A. and Pencolé Y. (2010). Synthesis of a Distributed and Accurate Diagnoser. 21st International Workshop on the Principles of Diagnosis (DX’10), Portland, Oregon, USA.
Lin F. (1994). Diagnosability of Discrete Event Systems and its Applications. In Discrete Event Dynamic Systems, 4,Kluwer Academic Publishers, Boston, USA.
Marangé P. (2008). Synthèse et filtrage robuste de la commande pour des systèmes manufacturiers surs de fonctionnement. PhD of the University of Reims
Champagne-Ardenne.
Nke Y., Lunze J. (2011). Online control reconfiguration for a faulty manufacturing process. 3rd International Workshop on Dependable Control of Discrete Systems (DCDS'11), Saarbrücken, Germany.
Paoli A., Sartini M. and Lafortune S. (2011). Active fault tolerant control of discrete event systems using online diagnostics. Automatica, Vol. 47, pp.639-649.
Philippot A. and Carré-Ménétrier. V. (2011). Methodology to obtain local discrete diagnosers. 3rd International Workshop on Dependable Control of Discrete Systems (DCDS'11), Saarbrücken, Germany.
Qiu W. (2005). Decentralized/distributed failure diagnosis and supervisory control of discrete event systems, PhD of the Iowa State University, USA.
Ramadge G., Wonham W. M. (1989). The control of discrete event systems, Proc. IEEE, Special issue on DEDSs, 77, pp.81-98.
Riera B., Annebicque D., Gellot F., Philippot A., Benlorhfar R. (2012). Control synthesis based on logical constraints for safe manufacturing systems. 14th IFAC Symposium on INformation COntrol problems in Manufacturing (INCOM 2012), Bucarest, Romania.
Riera B., Coupat R., Philippot A., Gellot F. and Annebicque D. (2014). Control design pattern based on safety Boolean guards for manufacturing systems: application to a palletizer. 12th IFAC-IEEE International Workshop On Discrete Event Systems (WODES'14), France.
Roussel J.M. and Faure J.M. (2002). An algebraic approach for PLC programs verification. In Proceedings of 6th international Workshop On Discrete Event Systems, Zaragoza, Spain,
pp.303–308.
Sampath M. (1995). A Discrete Event Systems Approach to Failure Diagnosis. PhD of the University of Michigan, Michigan, USA.
Wang, Y., Yoo, T. S., & Lafortune, S. (2007). Diagnosis of discrete event systems using decentralized architectures. Discrete Event Dynamic Systems, Vol.17(2), pp233-263.
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