|
| << vorige | volgende >> |
Tijdschrift beschrijving
Alle jaargangen van het bijbehorende tijdschrift
Alle afleveringen van het bijbehorende jaargang
Alle artikelen van de bijbehorende aflevering
Details van artikel 7 van 12 gevonden artikelen
| Titel: |
Online learning neural architectures and cross-correlation analysis for actuator failure detection and identification |
| Auteur: |
Napolitano, Marcello R. Casdorph, Van Neppach, Charles Naylor, Steve Innocenti, Mario Silvestri, Giovanni |
| Verschenen in: |
International journal of control |
| Paginering: | Jaargang 63 (1996) nr. 3 pagina's 433-455 |
| Jaar: |
1996-02-01 |
| Inhoud: |
This paper describes a study related to the testing and validation of a neural-network based approach for the problem of actuator failure detection and identification following battle damage to an aircraft control surface. Online learning neural architectures, trained with the Extended Back-Propagation algorithm, have been tested under nonlinear conditions in the presence of sensor noise. In addition, a parametric study has been conducted that addresses the selection of 'near optimal' neural architectures for online state estimation purposes. The Failure Detect-ability/False Alarm Rate ratio problem has also been considered in this study. The testing of the approach is illustrated through typical highly nonlinear dynamic simulations of a high performance aircraft. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 7 van 12 gevonden artikelen
| << vorige | volgende >> |