SIRMs Connected Fuzzy Inference Model Applied to Process Control — Automatic Tuning Using a Genetic Algorithm Carla Cavalcante
Koike* and Kaoru Hirota**
*Departamento de Engenharia Mecanica e Engenharia, Universidadl de Brasilia
**Department of Computational Intelligence and Systems Science Interdisciplinary Graduate School of Science and Engineering Tokyo Institute of Technology
A tuning process proposed for the single input rule modules (SIRMs) connected inference model is applied to process control. Using a genetic algorithm (GA), the importance degree is adjusted to improve process response. Simulation using first-order processes with dead time verified the validity of this approach.
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