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oai:recercat.cat:2117/828062026-02-09T09:08:13Zcom_2072_1033col_2072_452950

Robust neural-network-based fault detection with sequential D-optimum bounded-error input design Akielaszek-Witczak, Anna Mrugalska, Beata Puig Cayuela, Vicenç Wyrwicka, Magdalena Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control Àrees temàtiques de la UPC::Informàtica Neural networks (Computer science) Robust control Neural networks system identification optimum experiment design fault detection robustness bounded disturbances Xarxes neuronals (Informàtica) Control de robustesa A growing demand for technologically advanced systems has contributed to the increase of the awareness of systems safety and reliability. Such a situation requires the development of novel methods of robust fault diagnosis. The application of the analytical redundancy based methods for system fault detection causes that theIr effectiveness depends on model quality. In this paper, a new Methodology for the improvement of the neural model with a D-optimum sequential experimental design technique combined with outer bounding ellipsoid algorithm is proposed. Moreover, a novel method of robust fault detection against neural model uncertainty and disturbances is developed. Such an approach is used for modelling and robust fault detection of the three-screw spindle oil pump. Postprint (author's final draft) 2015 Conference report Akielaszek-Witczak, A., Mrugalska, B., Puig, V., Wyrwicka, M. Robust neural-network-based fault detection with sequential D-optimum bounded-error input design. A: IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes. "IFAC-PapersOnLine (volume 48, issue 21, Pages 1-1496): 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2015 Paris, 2–4 September 2015". París: International Federation of Automatic Control (IFAC), 2015, p. 434-439. 2405-8963 https://hdl.handle.net/2117/82806 10.1016/j.ifacol.2015.09.565 eng Restricted access - publisher's policy 6 p. application/pdf International Federation of Automatic Control (IFAC)