基于自适应模糊神经网络的感应电机矢量控制

doi:10.16180/j.cnki.issn1007-7820.2022.09.010

摘要/Abstract

摘要：

感应电机在传统PI控制中,参数固定且容易超调。针对该问题,文中研究了一种基于自适应模糊神经网络PI控制与全阶自适应观测器的感应电机矢量控制方案。根据感应电机数学模型建立了全阶自适应观测器的模型,采用Lyapunov稳定性理论对其进行了稳定性分析设计,并推导了转速自适应律。电机速度外环PI由自适应模糊神经网络推理系统在线整定优化,与传统控制方案相比,该方法易于实现,能够有效提高控制精准性,抑制外部扰动,节省了传感器成本。MATLAB/Simulink仿真实验表明,所提方案不仅改善了无速度传感器感应电机矢量控制系统的动态性能,还减小了外部负载扰动等情况的影响,提高了系统的自适应性和鲁棒性。

关键词: 感应电机, 无速度传感器, 矢量控制, PI控制器, ANFIS, 全阶自适应观测器, 在线整定, 鲁棒性

Abstract:

In view of the problem that the induction motor has fixed parameters and is easy to overshoot in the traditional PI control, a method based on the adaptive fuzzy neural network PI control and the full-order adaptive observer is proposed in this study. According to the mathematical model of the induction motor, the model of the full-order adaptive observer is established, and the stability analysis and design are carried out using the Lyapunov stability theory, and the speed adaptive law is deduced. The motor speed outer loop PI is adjusted and optimized online by an adaptive fuzzy neural network inference system. Compared with traditional control schemes, this method is easy to implement, can effectively improve control accuracy, suppress external disturbances, and save sensor costs. MATLAB/Simulink simulation experiments show that the proposed scheme not only improves the dynamic performance of the speed sensorless induction motor vector control system, but also reduces the influence of external load disturbances, and improves the system's adaptability and robustness.

Key words: induction motor, no speed sensor, vector control, PI controller, ANFIS, full-order adaptive observer, online tuning, robustness

中图分类号:

TN787

金爱娟,邵飞旋,严紫光. 基于自适应模糊神经网络的感应电机矢量控制[J]. 电子科技, 2022, 35(9): 65-73.

JIN Aijuan,SHAO Feixuan,YAN Ziguang. Vector Control of Induction Motor Based on Adaptive Fuzzy Neural Network[J]. Electronic Science and Technology, 2022, 35(9): 65-73.

图/表 11

图1

图2

表1

电机参数表"

参数	数值
定子电阻/R_s	1.115
转子电阻/R_r	1.083
定子漏感/ $L l s$	0.005 974
转子漏感/ $L l r$	0.005 974
定转子互感/L_m	0.203 7
级对数/P_n	2
转动惯量/J	0.02
摩擦系数/N·m·s	0.005 752

表1

图3

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图9

图10

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