DocumentCode :
2725428
Title :
GA-tuning of nonlinear observers for sensorless control of automotive power steering IPMSMs
Author :
Bhangu, B.S. ; Bingham, C.M.
Author_Institution :
Dept. of Electron. & Electr. Eng., Univ. of Sheffield, UK
fYear :
2005
fDate :
7-9 Sept. 2005
Firstpage :
772
Lastpage :
779
Abstract :
The paper considers two observer-based rotor position estimation schemes for sensorless control of interior permanent magnet synchronous motors (IPMSMs) for use in future automotive power steering systems. Specifically, emphasis is given to techniques based on feedback-linearisation followed by classical Luenberger observer design, and direct design of non-linear observers. Genetic algorithms (GAs), using the principles of evolution, natural selection and genetic mutation, are introduced to address difficulties in selecting correction gains for the observers, since no analytical tuning mechanisms yet exist. Experimental measurements from an automotive power steering test-facility are included, to demonstrate the enhanced performance attributes offered by tuning the proposed observer schemes, online, in this manner.
Keywords :
automobiles; feedback; genetic algorithms; machine control; observers; permanent magnet motors; rotors; steering systems; synchronous motors; GA tuning; automotive power steering system; classical Luenberger observer design; feedback-linearisation; genetic algorithm; genetic mutation; interior permanent magnet synchronous motor; nonlinear observer; rotor position estimation; sensorless control; state estimation; Algorithm design and analysis; Automotive engineering; Genetic algorithms; Genetic mutations; Permanent magnet motors; Power measurement; Power steering; Rotors; Sensorless control; Testing; Genetic algorithms; Nonlinear estimation; Observers; Permanent magnet machines; State estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicle Power and Propulsion, 2005 IEEE Conference
Print_ISBN :
0-7803-9280-9
Type :
conf
DOI :
10.1109/VPPC.2005.1554645
Filename :
1554645
Link To Document :
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