摘要
研究了无刷电机的控制问题,针对常规PID控制的无刷直流电机系统存在参数难以整定、超调量大、调节时间长、抗干扰能力差等问题,建立了无刷直流电机的数学模型,提出了RBF神经网络控制在系统中的总体设计方法,并在常规PID控制器的基础上建立了RBF网络控制器;利用Matlab软件对常规PID控制和RBF网络控制进行仿真比较,结果表明基于RBF网络控制器能动态调整控制器参数,有效的提高了系统的性能以及控制效果,系统对参数扰动具有较强的鲁棒性。
This paper researches control problem of brushless motor. For difficult parameter tuning,large overshoot,long regulation time and poor anti-interference ability of brushless DC motor with conventional PID control system,a mathematical model of brushless DC motor is established,overall design method of RBF neural network control is presented,and RBF network controller based on conventional PID controller is established. The simulative comparison between conventional PID control and RBF network control is carried out by Matlab software,the results show that RBF network controller can dynamically adjust parameters of controller and effectively improve system performance and control effect. The system has strong robustness to parameter perturbation.
出处
《防爆电机》
2015年第6期10-13,共4页
Explosion-proof Electric Machine
基金
2012年湖南省教育厅高等学校科学研究项目(12c1005)
