Title :
Position control of six-phase induction machine using FuzzyPI controller tuned by genetic algorithms
Author :
Moghadasian, M. ; Kianinezhad, R. ; Betin, F. ; Yazidi, A. ; Lanfranchi, V. ; Capolino, G.A.
Author_Institution :
Lab. of Innovative Technol., Univ. of Picardie Jules Verne, Amiens, France
Abstract :
In this paper, a fuzzy PI (FPI) controller is proposed for position control of six-phase induction motor (6PIM). The fuzzy controller is tuned by using the genetic algorithm so that a high performance of the overall system´s response can be achieved. The performance and the robustness of the control system are tested for fully loaded and widely load inertia variations. The proposed scheme is compared to the conventional proportional-integral control and validated by simulation and experimental tests of both control techniques.
Keywords :
PI control; fuzzy control; genetic algorithms; induction motors; machine control; position control; control system; fuzzy PI controller; genetic algorithms; load inertia variations; position control; proportional-integral control; six-phase induction machine; six-phase induction motor; Genetic algorithms; Induction machines; Mathematical model; Niobium; Position control; Stator windings; Faulted Mode; Fuzzy PI controller; Genetic Algorithms; Multiphase induction machines; Position Control;
Conference_Titel :
Power Engineering, Energy and Electrical Drives (POWERENG), 2011 International Conference on
Conference_Location :
Malaga
Print_ISBN :
978-1-4244-9845-1
Electronic_ISBN :
2155-5516
DOI :
10.1109/PowerEng.2011.6036435
