Advanced information processing in automatic control: selected papers from the IFAC/IMACS/IFORS Symposium (AIPAC '89), Nancy, France, 3-5 July 1989
Raoul Husson, International Federation of Automatic Control, International Association for Mathematics and Computers in Simulation, International Federation of Operation Research Societies
Published for the International Federation of Automatic Control by Pergamon Press, Jul 9, 1990 - Technology & Engineering - 553 pages
Information Processing is a key area of research and development and the symposium presented state-of-the-art reports on some of the areas which are of relevance in automatic control: fault diagnosis and system reliability. Papers also covered the role of expert systems and other knowledge based systems, which are needed, to cope with the vast quantities of data generated by large scale systems. This volume should be considered essential reading for anyone involved in this rapidly developing area.
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Evaluation of Analytical Redundancy for Fault Diagnosis in Dynamic Systems
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actuator adaptive control algorithm analysis analytical redundancy application approach approximation Artificial Intelligence Automatic Control behaviour bond graph calculation changes complex components considered constraints control system corresponding covariance covariance matrix decision defined density described distributed dynamic system eigenvalues eigenvectors elements Engineering entropy equation error example expert system failure detection fault detection fault diagnosis Figure France fuzzy control fuzzy sets fuzzy sets theory given identification IEEE implemented inference inference engine interval Kalman filter knowledge base linear matrix measurement method module Nancy noise object observer obtained on-line operation optimal output parameter estimation pattern recognition pattern vector performance physical possible prediction presented problem Proc procedure Processing in Automatic proposed qualitative recursive representation represented residual robot robust RTEX rules sample signal simulation solution step structure techniques theory tion transfer function unknown inputs values variables vector