直流调速系统神经模糊自适应控制器设计  

Design of Neural Fuzzy Adaptive Controller for DC Speed Regulation System

作　　者：王立红[1] Wang Lihong(Electrial Engineering College,Liaoning University of Technology,Jinzhou,Liaoning 121001,China)

机构地区：[1]辽宁工业大学电气工程学院,辽宁锦州121001

出　　处：《机电工程技术》2021年第4期190-191,253,共3页Mechanical & Electrical Engineering Technology

摘　　要：针对传统PID控制的不足,将传统PID控制和神经网络控制有效结合,构成神经模糊自适应控制器,作为双闭环直流调速系统的转速调节器,电流调节器仍采用PID控制。同时采用分目标误差学习规则对神经网络进行训练,使系统过渡过程平稳,稳态无静差。仿真结果表明,转速调节器改进后系统的超调量明显减小,调节时间变短,动态特性和抗干扰性均有所提高。Aiming at the deficiency of traditional PID control,combined the traditional PID control and neural network control effectively,a neural fuzzy adaptive controller was constructed as the speed regulator of the double closed loop DC speed regulation system,the current regulator still adopted PID control.At the same time,the objective error learning rules were used to train the neural network,make the transition process of the system smooth,steady state without static error.The simulation results show that the overshoot of the system decreases obviously after the speed regulator is improved,the adjustment time is shorter,the dynamic characteristics and anti-interference are improved.

关 键 词：直流调速 分目标 神经网络 自整定 

分 类 号：TM33[电气工程—电机]