Background for knowledge-based control: Holistic approaches in knowledge-based process control; introduction to knowledge-based systems for process control; basic theory and algorithms for fuzzy sets and logic; knowledge engineering and process control. Artificial intelligence issues: Cognitive models from subcognitive skills; a review of the approaches to the qualitative modelling of complex systems; solving process engineering problems using artificial neural networks; parallel processing architecture for real-time control.
Part 1: Background for knowledge-based controlChapter 1: Holistic approaches in knowledge-based process controlChapter 2: Introduction to knowledge-based systems for process controlChapter 3: Basic theory and algorithms for fuzzy sets and logicChapter 4: Knowledge engineering and process controlPart 2: Artificial intelligence issuesChapter 5: Cognitive models from subcognitive skillsChapter 6: A review of the approaches to the qualitative modelling of complex systemsChapter 7: Solving process engineering problems using artificial neural networksChapter 8: Parallel processing architecture for real-time controlPart 3: Applications of knowledge expertiseChapter 9: Overview of artificial intelligence toolsChapter 10: Application of fuzzy logic to control and estimation problemsChapter 11: Real-time knowledge-based systems in fermentation supervisory controlChapter 12: Machine-learned rule-based controlChapter 13: Expert systems for self-tuning controlChapter 14: Case studies in condition monitoringChapter 15: COGSYS - the real-time expert system builderChapter 16: Application of COGSYS to a small gas-processing plantPart 4: Deductive control issuesChapter 17: Expert system issues for multivariable controlChapter 18: Design of LQG and Hâ multivariable robust controllers for process control applications
Series: I E E CONTROL ENGINEERING SERIES
Number Of Pages: 356
Publisher: Institution of Engineering and Technology
Country of Publication: GB
Dimensions (cm): 22.86 x 15.24
Weight (kg): 0.66