Artificial Intelligence in Real-Time Control 1992: Selected Papers from the Ifac/Ifip/Imacs Symposium, Delft, the Netherlands, 16-18 June 1992

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ISBN: 9780080418988 | 0080418988
Cover: Hardcover
Copyright: 10/1/1993

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The symposium had two main aims, to investigate the state-of-the-art in the application of artificial intelligence techniques in real-time control, and to bring together control system specialists, artificial intelligence specialists and end-users. Many professional engineers working in industry feel that the gap between theory and practice in applying control and systems theory is widening, despite efforts to develop control algorithms. Papers presented at the meeting ranged from the theoretical aspects to the practical applications of artificial intelligence in real-time control. Themes were: the methodology of artificial intelligence techniques in control engineering; the application of artificial intelligence techniques in different areas of control; and hardware and software requirements. This symposium showed that there exist alternative possibilities for control based on artificial intelligence techniques.

Knowledge Based Control: Selecting the Right Tool for the Job	p. 1
The Functional Link Net Approach to the Learning of Real-time Optimal Control	p. 11
Neural Networks Applied to Optimal Flight Control	p. 19
Adaptive Neural Network Control of FES-induced Cyclical Lower Leg Movements	p. 25
Regularization as a Substitute for Pre-processing of Data in Neural Network Training	p. 31
Neural Network Modelling and Control of a Plant Exhibiting the Jump Phenomena	p. 37
Neural Networks (Methodologies for Process Modelling and Control)	p. 43
Parallel Nonlinear Decoupling for Process Control - A NARMAX Approach	p. 49
The Influence of Training Data Selection on Performance of Neural Networks for Control of Non-linear Systems	p. 55
Properties of the Neural Network Internal Model Controller	p. 61
A Target-directed Neurally Controlled Vehicle	p. 67
EMG Pattern Recognition by Neural Networks for Prosthetic Fingers Control	p. 73
Monitoring and Control of Power System Voltage Stability using an Artificial Neural Network	p. 81
Multi-dimensional Locally Generalizing Neural Networks for Real Time Control	p. 87
Induction of Control Rules from Human Skill	p. 97
A Knowledge Acquisition and Processing Strategy based on Formal Concept Analysis	p. 103
Implementation of a Human-friendly Systems Methodology for Intelligent Control System Modelling and Simulation	p. 109
Machine Learning using Version Spaces for a Power Distribution Network Fault Diagnostician	p. 115
Stability of Fuzzy Control Systems by using Nonlinear System Theory	p. 121
Stability of Feedback Systems with Uncertain Dynamics	p. 127
A Computational Causal Model for Process Supervision	p. 133
Design of an Intelligent Supervisor of a Ship Engine Room	p. 141
Qualitative Modelling and Simulation by Piecewise Linear Analysis	p. 147
Implementation of a Knowledge-based PID Auto-tuner	p. 153
Dimensions of Learning in a Real-time Knowledge-based Control System	p. 159
Educational Aspect of Expert Control of Technological Processes	p. 165
A Predictable Real-time Expert System for Multi-sensor Fusion	p. 171
Adaptive and Supplementary Intelligent Control of Power System Stabilizers	p. 177
Fuzzy Inference in Rule-based Real-time Control	p. 183
Laboratory Evaluation of Fuzzy Controllers	p. 189
Supervisory Control of Mode-switch Processes: Application to a Flexible Beam	p. 195
Knowledge Specification and Representation for an "Intelligent" Interface Devoted to Process Monitoring and Supervision	p. 201
Integration of Control and Error Management for a Flexible Assembly Cell, using a Cost Function	p. 207
Principles of Model-based Fault Detection	p. 213
On-line Residual Compensation in Robust Fault Diagnosis of Dynamic Systems	p. 221
Geometric Tools for an Observer-based Approach to Residual Generation	p. 229
Examples for Fault Detection in Closed Loops	p. 235
A Method for Fault Detection using Parameter and State Estimation	p. 241
Supervision and Control of an Exothermic Batch Process	p. 247
Markovian Reliability Analysis of State-estimator-based Instrument Fault Detection Schemes	p. 253
Neural Network Models and Statistical Tests as Flexible Base for Intelligent Fault Diagnosis	p. 259
Multivalued Logic Voting Scheme for Residual Evaluation in Failure Detection and Isolation Systems	p. 267
Knowledge-based Diagnosis in Information Poor Plants: A Materials Accountancy Application	p. 273
Logic-based Process Diagnosis Utilising the Causal Structure of Dynamical Systems	p. 279
Knowledge Based Sensor Fault Detection for Gas Turbines under Consideration of Model Based Methods	p. 287
Towards a General Multi-model-based Methodology for Diagnosis Systems	p. 293
An Adaptive Decision System using Pattern Recognition	p. 299
Intelligent Real-time Control of a Multifingered Robot Gripper by Learning Incremental Actions	p. 303
Synthesis of Optimal Control using Neural Network with Mixed Structure	p. 311
Learning to Avoid Collisions: A Reinforcement Learning Paradigm for Mobile Robot Navigation	p. 317
Genetic Algorithms for Process Control: A Survey	p. 323
An Adaptive System for Process Control using Genetic Algorithms	p. 329
Real-time Acquisition of Fuzzy Rules using Genetic Algorithms	p. 335
Automated Synthesis of Control for Nonlinear Dynamic Systems	p. 341
On Representations for Continuous Dynamic Systems	p. 347
Process Knowledge Acquisition and Control by Quantitative and Qualitative Complementarity	p. 353
Model-based Diagnosis - State Transition Events and Constraint Equations	p. 359
Multiple Models Based on Fuzzy Qualitative Modelling	p. 365
Architectures and Techniques of Artificial Intelligence in Process Control	p. 371
Real-time Supervisory Control for Industrial Processes	p. 377
The Development of an Intelligent Monitoring and Control System for a Solvent Extraction Process	p. 383
Knowledge-based Systems for Real-time Process Control: The MIP Project	p. 391
Using GRATE to Build Cooperating Agents for Industrial Control	p. 397
Intelligent Tuning of P+I Controllers for Bioprocess Application	p. 403
Fault Detection and Emergency Control in Power Systems	p. 409
Model-based Diagnosis for Continuous Process Supervision: The ALEXIP Experience	p. 415
Reactive Process Control using a Blackboard Architecture	p. 423
Pattern Recognition for Bioprocess Control	p. 431
Enhancing Fermentation Development Procedures via Artificial Neural Networks	p. 435
Artificial Intelligence in the Control of a Class of Fermentation Processes	p. 441
A Task Decomposition Approach to using Neural Networks for the Interpretation of Bioprocess Data	p. 447
Top-down Design of Embedded Real-time AI Systems	p. 453
A Temporal Blackboard Structure for Process Control	p. 459
Reinforcement Learning and Recruitment Mechanism for Adaptive Distributed Control	p. 467
Using Neural-net Computing to Formulate Real-time Control Strategies	p. 475
A Survey of Commercial Real-time Expert System Environments	p. 483
Designing Real-time Knowledge Based Systems with PERFECT	p. 491
RIGAS: An Expert Server Task in Real-time Environments	p. 497
DICE: A Real-time Toolbox	p. 503
Low-Cost Environment for Analysis and Design of Knowledge-based Control Algorithms	p. 509
Predicting and Improving Response-times of Perfect-models	p. 515
An Execution Environment for Real-time Model-based Supervisory Control and Diagnostic Systems	p. 521
Author Index	p. 527
Keyword Index	p. 529
Table of Contents provided by Blackwell. All Rights Reserved.

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Artificial Intelligence in Real-Time Control 1992: Selected Papers from the Ifac/Ifip/Imacs Symposium, Delft, the Netherlands, 16-18 June 1992

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