H/sub ∞/ optimization of Luenberger state observers and its application to fault detection filter design

Ibaraki, Soichi; Suryanarayanan, Shashikanth; Tomizuka, Masayoshi

doi:10.1109/cdc.2001.981015

Cited by 10 publications

(1 citation statement)

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“…A very interesting application of H ∞ estimation algorithms to aircraft inflight ice detection was given in literature [1]. An approach in which the Luenenberger observer gains from a bank of dedicated Kalman filters are optimized for fault detection using H ∞ optimization was proposed [2]. An application of the approach to a simplified longitudinal flight control system (i.e.…”

Section: Introductionmentioning

confidence: 99%

Design of Fault Diagnosis System for the Parameter-Depended Control System

Zhou¹

2011

AMR

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A robust parameter-depended reduced order(RPRO) fault detection filter(FDF) is designed. Contrary to the parameter-depended uncertainty system, the order of the linear matrix inequalities is reduced, then the RPRO fault detection and fault isolated filters are constructed. Then a RPRO fault isolation filter is designed for occurrence of both actuator fault and sensor fault in the aerocraft’s closed-loop control system, and fault diagnosis system is structured based on the fault isolation filters. Through the output of the fault diagnosis system, we can alarm the fault timely and the advantages of this approach are highlighted.

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Section: Introductionmentioning

confidence: 99%