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EnglishIn this chapter, an innovative approach to fault detection for nonlinear dynamic systems is proposed, based on the recently introduced quasi-local set membership- identification method, overcoming some relevant issues proper of the “classical” techniques. The approach is based on the direct identification from experimental data of a suitable filter and related uncertainty bounds. These bounds are used to detect when a change (e.g., a fault) has occurred in the dynamics of the system of inter- est. The main advantage of the approach compared to the existing methods is that it avoids the utilization of complex modeling and filter design procedures, since the filter/observer is directly designed from data. Other advantages are that the approach does not require to choose any threshold (as typically done in many “classical” tech- niques), and it is not affected by under-modeling problems. An experimental study regarding fault detection for a drone actuator is finally presented to demonstrate the effectiveness of the proposed approach.
Set membership fault detection for nonlinear dynamic systems / Karimshoushtari, Milad; Spagnolo, Luigi; Novara, Carlo. - (2019), pp. 239-264. [10.1049/PBCE123E_ch12]
| Titolo: | Set membership fault detection for nonlinear dynamic systems | |
| Autori: | ||
| Data di pubblicazione: | 2019 | |
| Titolo del libro: | Data-Driven Modeling, Filtering and Control: Methods and Applications | |
| Abstract: | In this chapter, an innovative approach to fault detection for nonlinear dynamic systems is propo...sed, based on the recently introduced quasi-local set membership- identification method, overcoming some relevant issues proper of the “classical” techniques. The approach is based on the direct identification from experimental data of a suitable filter and related uncertainty bounds. These bounds are used to detect when a change (e.g., a fault) has occurred in the dynamics of the system of inter- est. The main advantage of the approach compared to the existing methods is that it avoids the utilization of complex modeling and filter design procedures, since the filter/observer is directly designed from data. Other advantages are that the approach does not require to choose any threshold (as typically done in many “classical” tech- niques), and it is not affected by under-modeling problems. An experimental study regarding fault detection for a drone actuator is finally presented to demonstrate the effectiveness of the proposed approach. | |
| ISBN: | 9781785617133 | |
| Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| main.pdf | 2. Post-print / Author's Accepted Manuscript | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri | |
| Chapter12.pdf | 2a Post-print versione editoriale / Version of Record | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
http://hdl.handle.net/11583/2831720
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