Tzafestas / Verbruggen Artificial Intelligence in Industrial Decision Making, Control and Automation

Erscheinungsjahr 2012
ISBN: 978-94-011-0305-3
Verlag: Springer Netherland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 14, 767 Seiten, eBook

Reihe: Intelligent Systems, Control and Automation: Science and Engineering

This book is concerned with Artificial Intelligence (AI) concepts and techniques as applied to industrial decision making, control and automation problems. The field of AI has been expanded enormously during the last years due to that solid theoretical and application results have accumulated. During the first stage of AI development most workers in the field were content with illustrations showing ideas at work on simple problems. Later, as the field matured, emphasis was turned to demonstrations that showed the capability of AI techniques to handle problems of practical value. Now, we arrived at the stage where researchers and practitioners are actually building AI systems that face real-world and industrial problems. This volume provides a set of twenty four well-selected contributions that deal with the application of AI to such real-life and industrial problems. These contributions are grouped and presented in five parts as follows: Part 1: General Issues Part 2: Intelligent Systems Part 3: Neural Networks in Modelling, Control and Scheduling Part 4: System Diagnostics Part 5: Industrial Robotic, Manufacturing and Organizational Systems Part 1 involves four chapters providing background material and dealing with general issues such as the conceptual integration of qualitative and quantitative models, the treatment of timing problems at system integration, and the investigation of correct reasoning in interactive man-robot systems.

Zielgruppe

Research

Autoren/Hrsg.

Tzafestas, S.G.

Verbruggen, H. B.

Inhaltsverzeichnis

1 General Issues.- 1 Artificial Intelligence in Industrial Decision Making, Control and Automation: An Introduction.- 2 Conceptual Integration of Qualitative and Quantitative Process Models.- 3 Timing Problems and Their Handling at System Integration.- 4 Analysis for Correct Reasoning in Interactive Man Robot Systems: Disjunctive Syllogism with Modus Ponens and Modus Tollens.- 2 Intelligent Systems.- 5 Applied Intelligent Control Systems.- 6 Intelligent Simulation in Designing Complex Dynamic Control Systems.- 7 Multiresolutional Architectures for Autonomous Systems with Incomplete and Inadequate Knowledge Representation.- 8 Distributed Intelligent Systems in Cellular Robotics.- 9 Distributed Artificial Intelligence in Manufacturing Control.- 3 Neural Networks in Modelling, Control and Scheduling.- 10 Artificial Neural Networks for Modelling.- 11 Neural Networks in Robot Control.- 12 Control Strategy of Robotic Manipulator Based on Flexible Neural Network Structure.- 13 Neuro - Fuzzy Approaches to Anticipatory Control.- 14 New Approaches to Large - Scale Scheduling Problems: Constraint Directed Programming and Neural Networks.- 4 System Diagnostics.- 15 Knowledge - Based Fault Diagnosis of Technological Systems.- 16 Model - Based Diagnosis: State Transition Events and Constraint Equations.- 17 Diagnosis with Explicit Models of Goals and Functions.- 5 Industrial Robotic, Manufacturing and Organizational Systems.- 18 Multi-Sensor Integration for Mobile Robot Navigation.- 19 Incremental Design of a Flexible Robotic Assembly Cell Using Reactive Robots.- 20 on the Comparison of AI and DAI Based Planning Techniques for Automated Manufacturing Systems.- 21 Knowledge-Based Supervision of Flexible Manufacturing Systems.- 22 A Survey of Knowledge-Based Industrial Scheduling.- 23Reactive Batch Scheduling.- 24 Applying Groupware Technologies to Support Management in Organizations.