This paper presents an industrial case study relevant to a fuzzy logic controller designed via a properly developed genetic algorithm. We consider an example of a fuzzy logic-based industrial process-controller. In particular, we deal with the problem of controlling the speed of a belt conveyor for glass containers in a bottling plant. The primary objective of the controller is to guarantee the continuous feed to the filling station, in the presence of frequent gaps between bottles. The secondary objective is to reduce the impact speed between arriving bottles and those standing in the queue, in order to reduce the plant noise. High-performance parameters of the fuzzy controller are found by a properly developed genetic algorithm. The results provided by Monte Carlo simulations demonstrate that, with such controllers, it is possible to achieve both the objectives mentioned above.
Designing a belt conveyor controller in bottling plant using fuzzy logic and genetic algorithms
BRAGLIA, MARCELLO
2001-01-01
Abstract
This paper presents an industrial case study relevant to a fuzzy logic controller designed via a properly developed genetic algorithm. We consider an example of a fuzzy logic-based industrial process-controller. In particular, we deal with the problem of controlling the speed of a belt conveyor for glass containers in a bottling plant. The primary objective of the controller is to guarantee the continuous feed to the filling station, in the presence of frequent gaps between bottles. The secondary objective is to reduce the impact speed between arriving bottles and those standing in the queue, in order to reduce the plant noise. High-performance parameters of the fuzzy controller are found by a properly developed genetic algorithm. The results provided by Monte Carlo simulations demonstrate that, with such controllers, it is possible to achieve both the objectives mentioned above.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
