Modelling plant control strategies and their applications into a knowledge-based system |
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| Affiliation: | 1. CSIRO Computational Informatics, Postal Bag 33, South Clayton VIC 3169, Australia;2. CSIRO Computational Informatics, GPO Box 664, Canberra ACT 2601, Australia;1. State Key Laboratory of Software Development Environment, Beihang University, Beijing, PR China;2. School of Computer Science and Engineering, Beihang University, Beijing, PR China;3. IRIT-CNRS, Université de Toulouse, Toulouse, France;4. School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, USA;1. CAS Key Laboratory of Mechanical Behavior and Design of Materials, University of Science and Technology of China, Hefei, China;2. Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon, Hong Kong Special Administrative Region;3. College of Information Technology, Shanghai Ocean University, Shanghai 201306, China;4. City University of Hong Kong Shenzhen Research Institute Building, Shenzhen Hi-Tech Industrial Park, Nanshan District, Shenzhen, China;1. DeVry University, Chicago Campus, 3300 North Campbell Avenue, Chicago 60618, USA;2. ICube, University of Strasbourg, CNRS, UMR 7537, 300 Boulevard Sébastien Brant, BP 10413, 67412 Illkirch Cedex, France;1. Department of Computer Science, University of Cape Town, Rondebosch, 7700, South Africa;2. Rhodes Centre for Radio Astronomy Techniques and Technologies, Rhodes University, Grahamstown, 6140, South Africa;3. Department of Physics & Astronomy, University of the Western Cape, Private Bag X17, Bellville, 7535, South Africa;4. Department of Astronomy, University of Cape Town, Rondebosch, 7700, South Africa;5. Department of Physics and Electronics, Rhodes University, PO Box 94, Grahamstown, 6140, South Africa;6. GEPI, Observatoire de Paris, CNRS, Université Paris Diderot, 5 place Jules Janssen, 92190 Meudon, France;7. SKA South Africa, 3rd Floor, The Park, Park Road, Pinelands, 7405, South Africa |
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| Abstract: | The high complexity of a plant control system related structuring the domain expert knowledge into a knowledge base could decrease task. This paper presents a strategy adopted to model the application of control strategies employed in surveyed companies. Control engineering plays an important part in any industrial plant. Good control and optimisation of correct control strategies is therefore very crucial for the effective running of a control task related establishment of any kind. The control strategy approaches, must be followed right from system identification, modelling, validation, test and implementation. These stages are not always transparent when dealing with a system whose mathematical model does not exist or is difficult to obtain. When faced with this kind of problem, control enhancement techniques, such as knowledge-based, and intelligent system are always an obvious alternative. |
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