模糊控制在直流无刷电机控制系统中的应用
The Application of Fuzzy Control to Brushless DC Motor Control System

作者: 管于球 , 年晓红 , 丁磊磊 :中南大学信息科学与工程学院;

关键词: 直流无刷电机矢量控制空间矢量脉宽调制模糊控制BLDCM Vector Control SVPWM Fuzzy-Control

摘要: 直流无刷电机控制系统是多变量、时变和非线性的复杂大系统,本文针对简单PID控制方法在电机启动阶段具有较大超调以及在负载跳变时抗负载扰动能力不足的问题,提出了改进方案:电机控制系统的速度环采用参数自整定模糊PID控制。在Matlab/Simulink环境下搭建直流无刷电机矢量控制的仿真模型,通过仿真结果验证了所选控制方案的可行性。将该控制方案的仿真结果与简单PID控制的仿真结果相比较可得响应时间缩短了40%、超调量降低了3.5%、转矩扰动减小了30%,表明模糊PID控制可有效地提高控制系统的精确度、灵敏度和鲁棒性。

Abstract: The brushless direct current motor control system is a complex one with multi-variables, time-variability and non-linear. Regarding to the problems of large overshoot of simple PID control method in the motor start-up phase and insufficiency of anti-load disturbance ability when the load fluctuates suddenly, this thesis proposes an improved program. Parameter self-tuning fuzzy-PID control method is used for the speed loop of the motor control system. The brushless direct current motor’s vector control simulation model is built by using Matlab/Simulink, and the results of simulation verified the selected control scheme’s feasibility. Compared with the simulation result of this control program and that of simple PID, which has demonstrated that the system response time was reduced 40%, the overshoot was decreased 3.5% and the torque disturbance was dropped 30%. This shows that the fuzzy PID control is effective to improve the accuracy, sensitivity and robustness of the control system.

文章引用: 管于球 , 年晓红 , 丁磊磊 (2012) 模糊控制在直流无刷电机控制系统中的应用。 建模与仿真, 1, 39-44. doi: 10.12677/MOS.2012.12006

参考文献

[1] 张深. 直流无刷电动机原理及应用(第二版)[M]. 北京: 机械工业出版社, 2004.

[2] 夏长亮. 无刷直流电机控制系统[M]. 北京: 科学出版社, 2009.

[3] 杨浩东, 李榕, 刘卫国. 无刷直流电动机的数学模型及其仿真[J]. 微电机, 2003, 36(4): 8-10.

[4] 李斌, 唐永哲. 模糊PID算法在无刷直流电机控制系统中的应用[J]. 微电机, 2006, 2: 14-15.

[5] 卢飒, 潘岚, 徐文龙等. 基于模糊PID的永磁同步电动机数学控制系统[J]. 微电机, 2005, 33(6): 26-28.

[6] 杨霞, 李强, 郭庆鼎. 模糊PID控制交流伺服系统的研究[J]. 沈阳工业大学学报, 2005, 27(1): 31-33.

[7] L. S. Li, K. K. Lai. Fuzzy dynamic programming approach to hybrid multi-objective multistage decision-making problems. Fuzzy Sets and Systems, 2001, 117(1): 13-25.

[8] H. M. Kamelhm. Speed control of permanent magnet synchro- nous motor using fuzzy logic controller. IEEE International Elec- tric Machines and Drives Conference, Cairo, 3-6 May 2009: 1587-1591.

[9] C. H. Chou. Model reference adaptive fuzzy control: A Linguis- tic space approach. Fuzzy Sets and Systems, 1998, 96(1): 1-20.

[10] L. X. Wang, J. M. Mendel. Stable fuzzy adaptive control of nonlin- ear systems. IEEE Transactions on Fuzzy Systems, 1993, 1(2): 146-155.

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