Optimal State Feedback and Fuzzy Adaptive Compensation Control of Brushless DC Motor

Abstract:

In order to improve the dynamic response, the steady state precision and the anti-disturbance capability of the brushless DC motor drive system, a kind of adaptive compensation control strategy combining with the linear quadratic optimal control and fuzzy control theory is proposed in this paper. According to the state space model of Brushless DC motor, the Kalman filter is adopted to estimate the state variables. The optimal state feedback control matrix is given by linear quadratic optimal control theory. The deviation caused by random disturbance is compensated by the output of fuzzy controller. The results of simulation show that proposed method can not only effectively suppress random disturbance, but also has good speed regulation performance.

• Periodical: Advanced Materials Research (Volumes 850-851)
• Pages: 624-627
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.850-851.624
• Online since: December 2013
• Authors: Bao Long Zhu*, Min Li, Wei Sun, Hui Min Sun, Chao Fu
• Keywords: Brushless Dc Motor (BLDCM), Fuzzy Adaptive Compensation, Kalman Filter (KF), Optimal State Feedback Control

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