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ADVANCED INFORMATION PROCESSING IN AUTOMATIC CONTROL
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.
Section headings and selected papers: Survey Papers. AI and complex systems techniques in manufacturing management and control, M G Singh & K S Hindi. Fault Detection and Diagnosis. Identification of continuous-time process for failure detection and diagnosis, L Homssi et al . Data Validation Using Models. Pattern Recognition. Pattern recognition using neural networks. Comparison to the nearest neighbour rule, R Lengelle et al . Fuzzy Systems. On-line fuzzy rule set generator, G Lambert/Torres & D Mukhedkar. Qualitative Reasoning Methods. Expert Systems. Real-time expert systems and their applications, A R De Feyter. Computational Methods. Systolic array information processing strategy for real-time automatic control, Y Li & E Rogers. Bond Graph. Signal Processing and Times Series Analysis. Image Processing. Edge detection using the fuzzy sets theory, E Levrat et al . Intelligent Sensors Systems. Optimizing the process of analog-to-digital conversion in signal transmission, J Sawicki. Generalized Flow Networks. Biomedical Engineeering. A long-range adaptive controller with input constraints, T F Mendonca & J M Lemos. Applications. Predictive control for AC-drives, D Schroder. Author index. Keyword index.