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Online Parameter Estimation and Adaptive Control of Permanent-Magnet Synchronous Machines

S. Underwood, Iqbal Husain

📄 Abstract

This paper focuses on the benefits of adaptive control for permanent-magnet synchronous machines; a novel method of online parameter estimation for such machines has been developed. Two recursive least square algorithm segments, a fast and a slow one, are uniquely combined in real time with rich enough data from the machine to estimate all four machine parameters instead of a subset of these. Simulation and experimental results demonstrate the effectiveness of the proposed method.

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