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In this paper, a new adaptive controller is developed to suppress chaos and gain advanced speed tracking in a permanent magnet synchronous motor (PMSM) with unknown parameters and uncertainties. The controller has two parts: fuzzy neural and compensatory controllers. The fuzzy controller estimates the ideal feedback control law, while the compensatory controller is used to reduce the effects of the estimation error. With the improved controller design, the controller not only meets the control objective but also surely avoids the singularity problem that usually appears in indirect adaptive control techniques based on fuzzy/neural networks estimation. Finally, numerical simulations are executed to verify the validity of the proposed method.

Speed Tracking Control for an Uncertain Permanent Magnet Synchronous Motor Drive System