Gaussian adaptive PID control optimized via genetic algorithm applied to a step-down DC-DC converter
| Autor: | Erickson D. P. Puchta, Mauricio dos Santos Kaster, Felipe R. V. Ferreira, Hugo Siqueira, Ricardo Lucas |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Imagination
021103 operations research Computer science Buck converter media_common.quotation_subject Gaussian 0211 other engineering and technologies PID controller 02 engineering and technology Search engine symbols.namesake Control theory Bounded function Genetic algorithm 0202 electrical engineering electronic engineering information engineering Overshoot (signal) symbols 020201 artificial intelligence & image processing media_common |
| Zdroj: | 2016 12th IEEE International Conference on Industry Applications (INDUSCON). |
| DOI: | 10.1109/induscon.2016.7874509 |
| Popis: | In this paper, the proposal of an adaptive PID based on Gaussian functions is presented. Gaussian functions are of interest because they are smooth, with smooth derivatives, upper and lower bounded and with an adjustable concavity. The resulting Gaussian Adaptive PID (GAPID) have six parameters to be defined, that are optimized for the lowest settling-time with low overshoot by employing Genetic Algorithm (GA). Here, the choice of keeping the GAPID parameters linked to the PID parameters has the advantage of sharing the same design requirements, making it easy to replace existing PID controllers in most systems. Comments about GA and the way it was used (parameters of GA, individuals, evolution over each generation) are presented too. This technique is applied to a step-down Buck converter. The performance enhancement is notable (52.8%). Simulation and experimental results are also shown. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|