A multicriteria genetic tuning for fuzzy logic controllers
This paper presents the use of genetic algorithms to develop smartly tuned fuzzy logic controllers in multicriteria complex problems. This tuning approach has some specific restrictions that make it very particular and complex because of the large time requirements existing due to the need of consid...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2001 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099/3604 |
| Acceso en línea: | https://hdl.handle.net/2099/3604 |
| Access Level: | acceso abierto |
| Palabra clave: | Genetic tuning Multiple criteria Multiple objectives Fuzzy logic controllers Programari Sistemes de control intel·ligents Classificació AMS::68 Computer science::68N Software |
| Sumario: | This paper presents the use of genetic algorithms to develop smartly tuned fuzzy logic controllers in multicriteria complex problems. This tuning approach has some specific restrictions that make it very particular and complex because of the large time requirements existing due to the need of considering multiple criteria ---which enlarges the solution search space---, and to the long computation time models usually used for fitness assessment. To solve these restrictions, two efficient genetic tuning strategies considering different multicriteria approaches have been developed and tested in a real-world problem for fuzzy control of HVAC Systems. |
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