Predictive functional control based on fuzzy model: magnetic suspension system case study
Fuzzy model based predictive functional controller (FPFC) is applied to the magnetic suspension system - a pilot plant for magnetic bearing. High quality control requirements are short settle time with a-periodical step response and zero steady-state error. Open loop unstable process was stabilised...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2003 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/104083 |
| Acceso en línea: | http://hdl.handle.net/11336/104083 |
| Access Level: | acceso abierto |
| Palabra clave: | FUZZY IDENTIFICATION PREDICTIVE CONTROL REAL-TIME CONTROL https://purl.org/becyt/ford/2.2 https://purl.org/becyt/ford/2 |
| Sumario: | Fuzzy model based predictive functional controller (FPFC) is applied to the magnetic suspension system - a pilot plant for magnetic bearing. High quality control requirements are short settle time with a-periodical step response and zero steady-state error. Open loop unstable process was stabilised with linear lead compensator. The FPFC was used as a cascade controller. Due to some model uncertainties, the Takagi-Sugeno fuzzy model of stabilised system was obtained using fuzzy identification. Comparing to PID, it improved quality and robustness performance. With its computational efficiency, it proved to be ideal solution for high sampling frequency. |
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