Artificial Intelligence in Real-Time Control 1992

Section headings and selected papers: Plenary Papers. Knowledge based control: selecting the right tool for the job (R. Leitch). The Methodology of Artificial Intelligence Techniques in Control Systems. Neural Net Control. Neural networks applied to optimal flight control (T. McKelvey). The influence of training data selection on performance of neural networks for control of non-linear systems (A.B. Bendtsen, N. Jensen). Knowledge-Based Control. Induction of control rules from human skill (K.J. Hunt, Y.M. Han). Dimensions of learning in a real-time knowledge-based control system (N.V. Findler). Fuzzy Control. Fuzzy inference in rule-based real-time control (R. Jager et al.). Monitoring and Fault Diagnosis. Supervisory control of mode-switch processes: application to a flexible beam (R.A. Hilhorst et al.). Supervision and control of an exothermic batch process (R. Perne). Genetic Algorithms and Learning. An adaptive system for process control using genetic algorithms (C.L. Karr). Qualitative Reasoning. On representations for continuous dynamic systems (E.A. Woods). The Application of Artificial Intelligence Techniques in Different Areas of Control. Process Control. Real-time supervisory control for industrial processes (D.A. Linkens, M.F. Abbod). Biotechnology. Pattern recognition for bioprocess control (B. Sonnleitner, G. Locher). Hardware and Software Requirements. Temporal Reasoning. A temporal blackboard structure for process control (F. Barber et al.). New Paradigms for Real-Time Control. Reinforcement learning and recruitment mechanism for adaptive distributed control (H. Bersini). Real-Time Environments for Intelligent Control. DICE: a real-time toolbox (A.J. Krijgsman, R. Jager). Development of Real-Time AI Systems. An execution environment for real-time model-based supervisory control and diagnostic systems (Z. Papp et al.). Author index. Keyword index.
Numerous illus., 4 half-tones.