In this paper, the authors describe a design procedure for cascaded controller for electrical drives based on genetic algorithms (GAs). Most electric drives have two separate controllers for current and speed control, which are in general designed in two consecutive steps (firstly the current controller and then the speed controller). Using a GA devised to test and compare controllers of different orders, the authors search simultaneously for the couple of discrete anti-windup controllers achieving the optimal compromise of weighted cost and performance indices related to both current and speed responses. The search is performed online, on the physical hardware, by continuously downloading and testing new solutions on a micro-processor running the control algorithms in real time. The paper also describes some heuristic mechanisms to avoid the experimentation of unstable controllers. The cascaded control system obtained through genetic search significantly outperforms alternative schemes obtained with linear design techniques.
On-line genetic optimization of unstructured controllers for electric drives / Cupertino, Francesco; E., Mininno; Naso, David; Turchiano, Biagio; L., Salvatore. - (2002), pp. 347-352. (Intervento presentato al convegno IEEE International Symposium on Industrial Electronics, ISIE 2002. tenutosi a L'Aquila, Italy nel July 8-11, 2002) [10.1109/ISIE.2002.1026091].
On-line genetic optimization of unstructured controllers for electric drives
CUPERTINO, Francesco;NASO, David;TURCHIANO, Biagio;
2002-01-01
Abstract
In this paper, the authors describe a design procedure for cascaded controller for electrical drives based on genetic algorithms (GAs). Most electric drives have two separate controllers for current and speed control, which are in general designed in two consecutive steps (firstly the current controller and then the speed controller). Using a GA devised to test and compare controllers of different orders, the authors search simultaneously for the couple of discrete anti-windup controllers achieving the optimal compromise of weighted cost and performance indices related to both current and speed responses. The search is performed online, on the physical hardware, by continuously downloading and testing new solutions on a micro-processor running the control algorithms in real time. The paper also describes some heuristic mechanisms to avoid the experimentation of unstable controllers. The cascaded control system obtained through genetic search significantly outperforms alternative schemes obtained with linear design techniques.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
