Title :
Position control of faulted six-phase induction machine using genetic algorithms
Author :
Moghadasian, M. ; Kianinezhad, R. ; Betin, F. ; Yazidi, A. ; Lanfranchi, V. ; Capolino, G.A.
Author_Institution :
Lab. of Innovative Technol., Univ. of Picardi Jules Verne, Amiens, France
Abstract :
In this paper, a fuzzy PI (FPI) controller tuned using genetic algorithms (GA) is proposed for position control of six-phase induction motor (6PIM). The performance and the robustness of the control system are tested for healthy and several faulted operational modes and rotor inertia variations. The FPI controller presents many advantages such as satisfactory control performance under a wide range of operating conditions. The proposed scheme is compared to the conventional proportional-integral control and validated by simulation and experimental tests.
Keywords :
PI control; asynchronous machines; fault diagnosis; fuzzy control; genetic algorithms; machine control; position control; conventional proportional-integral control; faulted operational modes; faulted six-phase induction machine; fuzzy PI controller; genetic algorithms; healthy operational modes; position control; rotor inertia variations; satisfactory control performance; Genetic algorithms; Induction machines; Mathematical model; Position control; Simulation; Stator windings; Faulted Mode; Fuzzy PI controller; Genetic Algorithms; Multiphase induction machines; Position Control;
Conference_Titel :
Diagnostics for Electric Machines, Power Electronics & Drives (SDEMPED), 2011 IEEE International Symposium on
Conference_Location :
Bologna
Print_ISBN :
978-1-4244-9301-2
Electronic_ISBN :
978-1-4244-9302-9
DOI :
10.1109/DEMPED.2011.6063652
