Estimation and diagnosis using multi-models with application to a wastewater treatment plant |
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Authors: | A.M. Nagy-Kiss G. Schutz |
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Affiliation: | Centre de Recherche Public “Henri Tudor”, Modeling and Simulation Unit, Department of Advanced Material and Structures, Luxembourg |
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Abstract: | Process diagnosis is still considered a challenging engineering problem. Technological and also environmental systems have complex behaviors often involving nonlinear relationships. When confronted to such systems, there is a need to build systems that can operate over a wide range of operating conditions. For that it is very attractive to appeal to a decomposition of the system model into a number of simpler linear models. This paper mainly focuses on the use of multi-models for process diagnosis. It is shown how the traditional tools of the linear automatic can be wide and applied to multi-model structures. A proportional multi-integral observer is used for fault diagnosis using banks of observers to generate structured residuals. The performances of the proposed diagnosis method are highlighted through the application to a wastewater treatment plant model (WWTP), which is an uncertain nonlinear system affected by unknown inputs. |
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Keywords: | State/unknown input estimation Fault detection and identification (FDI) Multi-model (MM) Unmeasurable premise variables (UPV) Activated sludge process |
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