A novel technique for controller tuning
Neural networks and genetic algorithms have been in the past successfully applied, separately, to controller tuning problems. In this paper we purpose to combine its joint use, by exploiting the nonlinear mapping capabilities of neural networks to model objective functions, and use them to supply th...
| Autor principal: | |
|---|---|
| Outros Autores: | , , , |
| Formato: | conferenceObject |
| Idioma: | eng |
| Publicado em: |
2013
|
| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10400.1/2203 |
| País: | Portugal |
| Oai: | oai:sapientia.ualg.pt:10400.1/2203 |
| Resumo: | Neural networks and genetic algorithms have been in the past successfully applied, separately, to controller tuning problems. In this paper we purpose to combine its joint use, by exploiting the nonlinear mapping capabilities of neural networks to model objective functions, and use them to supply their values to a genetic algorithm which performs on-line minimization. Simulation results show that this is a valid approach, offering desired properties for on-line use such as a dramatic reduction in computation time and avoiding the need of perturbing the closed-loop operation. |
|---|