Open Access
2014 An Improved Adaptive Tracking Controller of Permanent Magnet Synchronous Motor
Tat-Bao-Thien Nguyen, Teh-Lu Liao, Hang-Hong Kuo, Jun-Juh Yan
Abstr. Appl. Anal. 2014: 1-12 (2014). DOI: 10.1155/2014/987308


This paper proposes a new adaptive fuzzy neural control to suppress chaos and also to achieve the speed tracking control in a permanent magnet synchronous motor (PMSM) drive system with unknown parameters and uncertainties. The control scheme consists of fuzzy neural and compensatory controllers. The fuzzy neural controller with online parameter tuning is used to estimate the unknown nonlinear models and construct linearization feedback control law, while the compensatory controller is employed to attenuate the estimation error effects of the fuzzy neural network and ensure the robustness of the controlled system. Moreover, due to improvement in controller design, the singularity problem is surely avoided. Finally, numerical simulations are carried out to demonstrate that the proposed control scheme can successfully remove chaotic oscillations and allow the speed to follow the desired trajectory in a chaotic PMSM despite the existence of unknown models and uncertainties.


Download Citation

Tat-Bao-Thien Nguyen. Teh-Lu Liao. Hang-Hong Kuo. Jun-Juh Yan. "An Improved Adaptive Tracking Controller of Permanent Magnet Synchronous Motor." Abstr. Appl. Anal. 2014 1 - 12, 2014.


Published: 2014
First available in Project Euclid: 27 February 2015

zbMATH: 07023462
Digital Object Identifier: 10.1155/2014/987308

Rights: Copyright © 2014 Hindawi

Vol.2014 • 2014
Back to Top