摘要
对同步旋转坐标系下的飞轮电池模型的充电控制进行了研究。针对PID控制器自适应较差特性,通过对神经网络自适应特性的研究,设计了基于直接电流控制策略的飞轮电池充电双闭环智能控制结构。其中脉宽调制采用SVPWM,并使用增益自适应单神经元PID控制器取代传统PID控制器,利用其自学习能力在线调整PID参数。通过数字仿真结果表明,所提出的控制器控制性能良好,能够满足飞轮电池实际控制要求,对各种干扰与故障都具有较快的适应性和较强的鲁棒性。
The PID controller is widely used in industrial systems. However, it is not an easy task to adjust its three parameters. An improved algorithm self-adaptive single neuron PID controller, together with PSD optimum method and SVPWM scheme, has been applied for flywheel battery＇s charging control design in flywheel energy storage system （FESS）. The experiment simulation results demonstrated that serf-adaptive single neuron PSD controller with SVPWM scheme has optimized the charging process with strongest electromagnetism torque and speed dynamic characteristics, which has been verified the correct and efficiency of this method.
出处
《水力发电》
北大核心
2008年第8期53-55,共3页
Water Power
基金
湖北省教育厅自然科学计划资助项目(2003A001)
湖北省自然科学基金资助(2005ABA294)
