Adaptive neural-networks-based fault detection and diagnosis using unmeasured states

IET Control Theory and Applications

Volumn 2, Issue 12, 2008, Pages 1066-1076

  Liu, C S ^a   Zhang, S J ^a   Hu, S S ^a  

^a NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTRIC FAULT CURRENTS; FAULT DETECTION; FEEDFORWARD NEURAL NETWORKS; FINITE DIFFERENCE METHOD; IMAGE CLASSIFICATION; NONLINEAR SYSTEMS; PROBABILITY DENSITY FUNCTION; RADIAL BASIS FUNCTION NETWORKS; SYSTEM STABILITY; VEGETATION;

ADAPTIVE PARAMETERS; FAULT DETECTION AND DIAGNOSES; FAULT DIAGNOSIS; GAUSSIAN; LYAPUNOV THEORIES; MODERN ENGINEERINGS; NONLINEAR STATE OBSERVERS; RADIAL BASIS FUNCTION NEURAL NETWORKS; RBF NEURAL NETWORKS; SIMULATION EXAMPLES; STABILITY ANALYSES; SYSTEM STATES; SYSTEMS MODELS;

NEURAL NETWORKS;

EID: 57349111413     PISSN: 17518644     EISSN: 17518652     Source Type: Journal    
DOI: 10.1049/iet-cta:20070216     Document Type: Article

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