| Optimal state feedback control of brushless direct-current motor drive systems based on Lyapunov stability criterion |
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| 作者姓名： | WANG Wei JIN Ruo-jun JIANG Jing-ping |
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| 作者单位： | WANG Wei1，JIN Ruo-jun2，JIANG Jing-ping2 (1College of Mechatronics Engineering，China Jiliang University，Hangzhou 310018，China) (2School of Electrical Engineering，Zhejiang University，Hangzhou 310027，China) |
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| 摘 要： | This paper develops a unified methodology for a real-time speed control of brushless direct-current motor drive systems in the presence of measurement noise and load torque disturbance. First, the mathematical model and hardware structure of system is established. Next, an optimal state feed back controller using the Kalman filter state estimation technique is derived. This is followed by an adaptive control algorithm to compensate for the effects of noise and disturbance. Those two algorithms working together can provide a very-high-speed regulation and dynamic response over a wide range of operating conditions. Simulated responses are presented to highlight the effectiveness of the proposed control strategy.
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| 关 键 词： | 适应控制技术 电力拖动 最佳状态反馈 操作系统 |
| 收稿时间： | 2007-05-07 |
| 修稿时间： | 2007-09-20 |
Optimal state feedback control of brushless direct-current motor drive systems based on Lyapunov stability criterion |
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| WANG Wei JIN Ruo-jun JIANG Jing-ping.Optimal state feedback control of brushless direct-current motor drive systems based on Lyapunov stability criterion[J].Journal of Zhejiang University Science,2007,8(12):1889-1893. |
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| Authors: | Wei Wang Ruo-jun Jin Jing-ping Jiang |
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| Institution: | (1) College of Mechatronics Engineering, China Jiliang University, Hangzhou, 310018, China;(2) School of Electrical Engineering, Zhejiang University, Hangzhou, 310027, China |
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| Abstract: | This paper develops a unified methodology for a real-time speed control of brushless direct-current motor drive systems in the presence of measurement noise and load torque disturbance. First, the mathematical model and hardware structure of system is established. Next, an optimal state feed back controller using the Kalman filter state estimation technique is derived. This is followed by an adaptive control algorithm to compensate for the effects of noise and disturbance. Those two algorithms working together can provide a very-high-speed regulation and dynamic response over a wide range of operating conditions. Simulated responses are presented to highlight the effectiveness of the proposed control strategy. |
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| Keywords: | Brushless DC motor Adaptive control Optimal state feedback |
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