PWA Dynamic Identification for Nonlinear Model Fault Detection. Simani, S. & Fantuzzi, C. In 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes , SAFEPROCESS 2006, pages 1121–1126, Beijing (China), August~29–September~1, 2006. IFAC.
abstract   bibtex   
This paper addresses the identification of non–linear dynamic systems. A wide class of these systems can be described using nonlinear time-invariant regression models, that can be approximated by means of piecewise affine prototypes with an arbitrary degree of accuracy. This work concerns the identification of piecewise affine model structure through inputoutput data acquired from a dynamic process. In order to show the effectiveness of the developed technique, when exploited also for FDI purpose, the results obtained in the identification of both a simple simulated system and a real dynamic process are reported.
@InProceedings{Simani-Fantuzzi:safeprocess:2006,
  author = 	 {Simani, Silvio and Fantuzzi, Cesare},
  title = 	 {{PWA} Dynamic Identification for Nonlinear Model Fault Detection},
  booktitle = 	 {6th IFAC Symposium on Fault Detection, Supervision
                  and Safety of Technical Processes , SAFEPROCESS
                  2006},
  year =	 2006,
  editor = {Zhang Zhang},
  pages = {1121--1126},
  address =	 {Beijing (China)},
  month	= aug # "~29--" # sep # "~1",
  publisher = {IFAC},
  href =         {\hyperbibref{2006_08_SAFEPROCESS-simani.pdf}},
  file =         {papers/2006_08_SAFEPROCESS-simani.pdf},
  ISBN = {978-3-902661-14-2},
  ID = 200608,
  keywords = {Fault diagosis, Automatic Control},
  abstract = {This paper addresses the identification of non–linear
                  dynamic systems.  A wide class of these systems can
                  be described using nonlinear time-invariant
                  regression models, that can be approximated by means
                  of piecewise affine prototypes with an arbitrary
                  degree of accuracy. This work concerns the
                  identification of piecewise affine model structure
                  through inputoutput data acquired from a dynamic
                  process. In order to show the effectiveness of the
                  developed technique, when exploited also for FDI
                  purpose, the results obtained in the identification
                  of both a simple simulated system and a real dynamic
                  process are reported.}
}

% IMECE

Downloads: 0