This paper shows how "soft computing" could be useful to solve control problems. For this aim the dynamic of temperature in a room has been modelled, simulating it by the use of an artificial neural network (ANN) opportunely trained. Then, using this model, two main kinds of controllers have been tuned using a genetic algorithm: a standard PID and a fuzzy PID. Then the advantage of fuzzy systems, intended as "supervisors" to standard PID controllers, was experimented. A final comparison shows that fuzzy systems, if well tuned, could give great results in control.
A soft computing approach to the intelligent control / Bevilacqua, Vitoantonio; Grasso, E.; Mastronardi, Giuseppe; Riccardi, L.. - (2006), pp. 1312-1317. (Intervento presentato al convegno IEEE International Conference on Industrial Informatics, INDIN'06 tenutosi a Singapore nel August 16-18, 2006) [10.1109/INDIN.2006.275849].
A soft computing approach to the intelligent control
BEVILACQUA, Vitoantonio;MASTRONARDI, Giuseppe;
2006-01-01
Abstract
This paper shows how "soft computing" could be useful to solve control problems. For this aim the dynamic of temperature in a room has been modelled, simulating it by the use of an artificial neural network (ANN) opportunely trained. Then, using this model, two main kinds of controllers have been tuned using a genetic algorithm: a standard PID and a fuzzy PID. Then the advantage of fuzzy systems, intended as "supervisors" to standard PID controllers, was experimented. A final comparison shows that fuzzy systems, if well tuned, could give great results in control.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
