基于自适应神经模糊推理控制的无刷直流电机转子位置控制研究

为提高无刷直流电机(Brushless DC Motor, BLDCM)在瞬态和稳态条件下的控制性能,提出一种基于自适应神经模糊推理系统(ANFIS)的转子位置控制器。推导出无刷直流电机位置控制数学模型;基于Takagi-Sugeno模型设计ANFIS控制器,分别利用反向传输算法和最小二乘估计法对输入和输出参数进行了优化;对正弦信号和斜坡信号下的转子位置控制效果进行了仿真和实验研究。结果表明:该控制器可实现无刷直流电机快速、准确的动态响应,具有良好的稳态性能。通过仿真和试验,验证了ANFIS控制策略的有效性。

Rotor Position Control of Brushless DC Motor Based on Adaptive Neuro Fuzzy Inference Control (ANFIS)

In order to improve the control performance of Brushless Direct Current Motor(BLDCM) under transient and steady state conditions, a rotor position controller based on adaptive neural fuzzy inference system(ANFIS) is proposed. Firstly, the mathematical model of BLDCM position control was deduced;secondly, the ANFIS controller was designed based on Takagi-Sugeno model, and the input and output parameters were optimized by using the inverse transmission algorithm and the least square estimation method(LSEM), respectively;finally, the rotor position control effect under sinusoidal signal and slope signal was simulated and experimentally researched. The results show that the controller can achieve fast and accurate dynamic response of BLDCM, and has good steady-state performance. The effectiveness of ANFIS control strategy is verified by simulation and experiment.