摘要
针对无刷直流电机(BLDCM)双闭环控制调速系统的控制响应速度慢、转速波动较大等问题,提出一种模糊神经网络与内模控制相结合的驱动方式。该方式利用Matlab/Simulink来构建一种基于BLDCM和控制器的电梯一体式限速器仿真模型,得到BLDCM的速度、转矩响应曲线。仿真分析和实验结果均表明,模糊T-S型内模PID控制算法在响应速度、转速误差、抗干扰能力和控制精度等性能方面优于内模PID控制算法与常规双闭环PID控制系统。该研究可为模糊神经网络T-S型内模PID算法在电梯一体式限速器上的应用积累经验。
A driving method combining fuzzy neural network and internal model control is proposed to address the problems of slow control response speed and large speed fluctuations of brushless DC motor(BLDCM)dual closed-loop control speed regulation system.In this method,Matlab/Simulink is used to construct the simulation model of elevator integrated governor based on BLDCM and controller,and the speed and torque response curves of BLDCM are obtained.The simulation analysis and results show that fuzzy T-S(Takagi-Sugeno)internal model PID control algorithm is superior to internal model PID control algorithm and conventional double closed loop PID control system in response speed,speed error,anti-interference ability and control precision.This research can accumulate experience for the application of fuzzy neural network T-S internal model PID algorithm in elevator integrated speed limiter.
作者
孙崇智
吴永伟
安建民
杨佳
郭伟伟
SUN Chongzhi;WU Yongwei;AN Jianmin;YANG Jia;GUO Weiwei(Gansu Province Special Equipment Inspection and Testing Institute,Lanzhou 730050,China)
出处
《现代电子技术》
北大核心
2024年第24期18-24,共7页
Modern Electronics Technique
基金
甘肃省市场监督管理局科技计划资助(SSCJG-TS-A202204)。
