改进算法单神经元PID在飞轮储能系统中的研究  

Studying on improved algorithm self-adaptive single neuron PID controller in flywheel energy storage system

作　　者：汤双清[1] 李志雄[1] 蒋宇[2] 

机构地区：[1]三峡大学机械与材料学院,宜昌443002 [2]黄山学院信息工程学院,黄山245021

出　　处：《机械设计与制造》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)

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.

关 键 词：飞轮电池 PSD 单神经元 SVPWM 

分 类 号：TH16[机械工程—机械制造及自动化] TM914.4[电气工程—电力电子与电力传动]