Robust fault detection using robust l/sub 1/ estimation and fuzzy logic

Curry, T.; Collins, Emmanuel G.; Selekwa, Majura F.

doi:10.1109/acc.2001.945985

Cited by 8 publications

(3 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Until recent work, 11,14,18,20 the relatively nonconservative mixed structured singular value (MSSV) techniques 21−24 had not been applied to robust estimation, although more conservative techniques, based on the small-gain theorem or fixed quadratic Lyapunov functions, had been used (see Refs. 15,16,[25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Robust Fault Detection and Isolation Using Robust l1 Estimation

Curry

Collins

2005

Journal of Guidance, Control, and Dynamics

View full text Add to dashboard Cite

The application of robust 1 estimation to robust fault detection and isolation (FDI) is considered. This is accomplished by developing a series, or bank, of robust estimators (full-order observers), each of which is designed such that the residual will be sensitive to a certain fault (or faults) while insensitive to the remaining faults. Robustness is incorporated by ensuring that the residual remains insensitive to exogenous disturbances as well as modeling uncertainty. Mixed structured singular value and 1 theories are used to develop the appropriate threshold logic to evaluate the outputs of the estimators used for determining the occurrence and location of a fault. A real-coded genetic algorithm is used to obtain the estimator gain matrices. This approach to FDI is successfully demonstrated using a linearized model of a jet engine. Nomenclature= ess sup t ≥ 0 z(t) 2 z(·) (∞,2), [N 0 ,N ] = ess sup t∈[N 0 T,N T ] z(t) 2 0, I = zero matrix, identity matrix

show abstract

Section: Introductionmentioning

confidence: 99%

Robust Fault Detection and Isolation Using Robust l1 Estimation

Curry

Collins

2005

Journal of Guidance, Control, and Dynamics

View full text Add to dashboard Cite

show abstract

“…In [11], T.Curry et al considered fuzzy logic as a means of determining the degree of faults, which allows the human observations to be incorporated. In their targeted aircraft flight control system, the fault detection that combining the robust parameter estimation with fuzzy logic proved to be effective in increasing the system sensitivity to minor faults while maintaining the insensitive to the disturbances.…”

Section: Fuzzy Logic Based Approachmentioning

confidence: 99%

“…11 illustrates the implementation logic of the wavelet filtering unit. In the first step, the unit takes the raw SNR time-series as input and performs the wavelet transform over the time-series.…”

mentioning

confidence: 99%