GA-based tuning of nonlinear observers for sensorless control of IPMSMs

Bhangu, B S and Bingham, Chris (2004) GA-based tuning of nonlinear observers for sensorless control of IPMSMs. In: Power Electronics, Machines and Drives, 2004. (PEMD 2004). Second International Conference on (Conf. Publ. No. 498), 31 Mar - 2 April 2004, Edinburgh, Scotland.

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GA-based tuning of nonlinear observers for sensorless control of IPMSMs
The paper considers two observer-based rotor position estimation schemes for sensorless control of interior permanent magnet synchronous machines (IPMSMs). Emphasis is given to techniques based on feedback linearisation followed by Luenberger observer design, and direct design of nonlinear observers. Genetic algorithms (GAs) based on the principles of evolution, natural selection and genetic mutation are employed to address difficulties in selecting correction gains for the observers, since no analytical tuning mechanisms yet exist, with results included to demonstrate the enhanced performance attributes offered by observers tuned in this way.
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Abstract

The paper considers two observer-based rotor position estimation schemes for sensorless control of interior permanent magnet synchronous machines (IPMSMs). Emphasis is given to techniques based on feedback linearisation followed by Luenberger observer design, and direct design of nonlinear observers. Genetic algorithms (GAs) based on the principles of evolution, natural selection and genetic mutation are employed to address difficulties in selecting correction gains for the observers, since no analytical tuning mechanisms yet exist, with results included to demonstrate the enhanced performance attributes offered by observers tuned in this way.

Additional Information:The paper considers two observer-based rotor position estimation schemes for sensorless control of interior permanent magnet synchronous machines (IPMSMs). Emphasis is given to techniques based on feedback linearisation followed by Luenberger observer design, and direct design of nonlinear observers. Genetic algorithms (GAs) based on the principles of evolution, natural selection and genetic mutation are employed to address difficulties in selecting correction gains for the observers, since no analytical tuning mechanisms yet exist, with results included to demonstrate the enhanced performance attributes offered by observers tuned in this way.
Keywords:Sensorless control, interior permanent magnet synchronous machines, nonlinear observers
Subjects:H Engineering > H600 Electronic and Electrical Engineering
Divisions:College of Science > School of Engineering
ID Code:2582
Deposited On:27 May 2010 14:01

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