Adaptive process control using biological paradigms
Researchers at the US Bureau of Mines have combined several biologically oriented techniques into a comprehensive approach to adaptive process control. The three specific techniques from the field of artificial intelligence used to produce the adaptive process control systems are: (1) fuzzy logic, (...
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| Published in | Journal of network and computer applications Vol. 19; no. 1; pp. 21 - 44 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
1996
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| Online Access | Get full text |
| ISSN | 1084-8045 1095-8592 |
| DOI | 10.1006/jnca.1996.0004 |
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| Abstract | Researchers at the US Bureau of Mines have combined several biologically oriented techniques into a comprehensive approach to adaptive process control. The three specific techniques from the field of artificial intelligence used to produce the adaptive process control systems are: (1) fuzzy logic, (2) genetic algorithms, and (3) neural networks. Fuzzy logic is a technique in which the human «rule-of-thumb» approach to decision making is modelled. Genetic algorithms are search algorithms based on the mechanics of natural genetics that are able to rapidly locate near-optimum solutions to difficult problems. Neural networks are crude paradigms of the mammalian brain that have been used to model industrial systems. The paper provides an overview of the architecture used to achieve adaptive process control, and demonstrates its effectiveness in the control of three industrial systems: (1) a titration system, (2) an exothermic chemical reaction, and (3) a column flotation unit. |
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| AbstractList | Researchers at the US Bureau of Mines have combined several biologically oriented techniques into a comprehensive approach to adaptive process control. The three specific techniques from the field of artificial intelligence used to produce the adaptive process control systems are: (1) fuzzy logic, (2) genetic algorithms, and (3) neural networks. Fuzzy logic is a technique in which the human «rule-of-thumb» approach to decision making is modelled. Genetic algorithms are search algorithms based on the mechanics of natural genetics that are able to rapidly locate near-optimum solutions to difficult problems. Neural networks are crude paradigms of the mammalian brain that have been used to model industrial systems. The paper provides an overview of the architecture used to achieve adaptive process control, and demonstrates its effectiveness in the control of three industrial systems: (1) a titration system, (2) an exothermic chemical reaction, and (3) a column flotation unit. |
| Author | Karr, Charles L. |
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| CitedBy_id | crossref_primary_10_1016_j_mineng_2009_02_004 crossref_primary_10_1016_S0040_1625_97_00022_X crossref_primary_10_1016_j_mineng_2011_08_003 crossref_primary_10_1057_palgrave_jors_2602132 crossref_primary_10_1016_j_mineng_2004_08_013 |
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| Title | Adaptive process control using biological paradigms |
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