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Parameter optimization for a fuzzy logic control of a Permanent Magnet Brushless Motor

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This paper proposes a strategy to optimize parameters in a fuzzy logic control of a Permanent Magnet Brushless Motor. The proposed system uses a neural network optimization to determine all the static parameters of the fuzzy logic control strategy. Analysis of the vector control scheme and the fuzzy controller are illustrated from the simulation with the MATLAB Environment to compare their performance. The main objective behind this optimization strategy is to improve the performance of the fuzzy logic control scheme. This approach has been experimentally evaluated on a 1.5 kW permanent magnet brushless motor drive.

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This paper proposes a strategy to optimize parameters in a fuzzy logic control of a Permanent Magnet Brushless Motor. The proposed system uses a neural network optimization to determine all the static parameters of the fuzzy logic control strategy. Analysis of the vector control scheme and the fuzzy controller are illustrated from the simulation with the MATLAB Environment to compare their performance. The main objective behind this optimization strategy is to improve the performance of the fuzzy logic control scheme. This approach has been experimentally evaluated on a 1.5 kW permanent magnet brushless motor drive.

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