重庆理工大学学报（自然科学版）2025，Vol.39Issue(3)：47-54,8.DOI:10.3969/j.issn.1674-8425(z).2025.02.006
基于FNN的车用永磁同步电机转动惯量识别与摩擦补偿控制
FNN-based moment of inertia identification and friction compensation control for PMSM
摘要
Abstract
It is difficult for servo system to achieve the desired control with the influence of uncertain frictions,which also exert great unexpected impacts on motor parameter identification.Focusing on the servo system with speed planning,we design an identification method of the friction and the moment of inertia considering inherent friction.With the consideration of the strong nonlinearity of friction,T-S fuzzy neural network is employed to identify the friction and the moment of inertia online.The identified friction model based on T-S fuzzy neural network is used as compensation control while the moment of inertia is used as parameters from the tuned PI controller.Simulation results show our identification method achieves fairly good approximation performance and satisfactory trajectory tracking effect.关键词
伺服系统/参数辨识/模糊神经网络/自适应控制Key words
servo system/parameter identification/fuzzy neural network/compensation control分类
信息技术与安全科学引用本文复制引用
刘晏,李刚,俞兆起,程浩宁..基于FNN的车用永磁同步电机转动惯量识别与摩擦补偿控制[J].重庆理工大学学报（自然科学版）,2025,39(3):47-54,8.基金项目
国家自然科学基金面上项目(51675257 （）
辽宁省自然科学基金面上项目(2022-MS-376) （2022-MS-376）
