A model-based fault-detection and prediction scheme for nonlinear multivariable discrete-time systems with asymptotic stability guarantees

IEEE Transactions on Neural Networks

Volumn 21, Issue 3, 2010, Pages 404-423

  Thumati, Balaje T ^a   Jagannathan, S ^a  

^a University of Missouri Rolla   (United States)

Author keywords

Asymptotic stability; Fault detection (FD); Multiple input multiple output (MIMO) nonlinear discrete time system; Prognostics

Indexed keywords

DISCRETE TIME; DISCRETE TIME SYSTEM; FAULT DIAGNOSIS SCHEMES; FAULT DYNAMICS; FOURTH-ORDER; INPUT AND OUTPUTS; MEASURED SYSTEM; MODEL-BASED; MULTI VARIABLES; MULTIPLE-INPUT-MULTIPLE-OUTPUT; NONLINEAR DISCRETE-TIME SYSTEMS; ON-LINE APPROXIMATOR; OUTPUT FAULTS; PARAMETER UPDATE LAW; PREDICTION SCHEMES; PROGNOSTICS; ROBUST ADAPTIVE; SATELLITE SYSTEM; TIME TO FAILURE; UNIFIED MODEL;

ANALOG TO DIGITAL CONVERSION; ASYMPTOTIC ANALYSIS; ASYMPTOTIC STABILITY; DIGITAL CONTROL SYSTEMS; DISCRETE TIME CONTROL SYSTEMS; FAILURE ANALYSIS; FINITE DIFFERENCE METHOD; SYSTEM STABILITY; TELECOMMUNICATION REPEATERS; VIBRATION MEASUREMENT;

FAULT DETECTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; COMPUTER SIMULATION; HUMAN; NONLINEAR SYSTEM; PREDICTION AND FORECASTING; SIGNAL PROCESSING; TIME;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; HUMANS; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; PREDICTIVE VALUE OF TESTS; SIGNAL PROCESSING, COMPUTER-ASSISTED; TIME FACTORS;

EID: 77649273670     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2009.2037498     Document Type: Article

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