摘要
PID控制器是在工业中应用最为广泛的控制技术,然在而其三个参数的调节较复杂烦琐。通过对神经网络自适应特性的研究,设计了改进算法的单神经元PID控制器,利用单神经元自学习能力在线调整PID参数;同时结合自适应PSD算法对神经元增益在线调整。将该控制器应用于飞轮储能系统中,结合SVPWM算法对飞轮电池进行充放电控制。实验仿真结果表明,该控制方法能够使飞轮电池充放电过程快速稳定,鲁棒性强,满足实际控制要求。
The PID controller is the most widely used controller in industrial systems. However,appropriately tuning a PID controller is not an easy task although it has only three parameters. A improved algorithm self-adaptive single neuron PID controller,together with PSD optimum method and SVPWM scheme ,has been applied for flywheel battery＇s charging/discharging control design in .flywheel energy storage system（ FESS ）. The experiment simulation result demonstrates that self-adaptive single neuron PID controller with SVPWM scheme has optimized the charging/discharging process with strongest dynamic characteristics ,which has been verified the correct and efficiency of this method.
出处
《机械设计与制造》
北大核心
2009年第5期127-129,共3页
Machinery Design & Manufacture
基金
湖北省自然科学基金资助(2005ABA294)
三峡大学博士基金资助(2005)
