基于自适应预测控制的PEMFC动态特性研究  

Dynamic Behaviors of PEMFC Based on Adaptive Prediction Control

作　　者：吕学勤[1] 段利伟[1] 姜英杰[1] 

机构地区：[1]上海电力学院自动化工程学院,上海200090

出　　处：《农业机械学报》2015年第5期350-356,共7页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家自然科学基金资助项目(51405286);上海市电站自动化技术重点实验室开放基金资助项目(13DZ2273800)

摘　　要：质子交换膜燃料电池(PEMFC)是具有多参数影响的复杂系统,针对其时变、非线性及不确定性导致其输出动态特性难以控制的问题,设计了自适应预测控制器。该控制器以PEMFC系统的神经网络模型作为预测模型,充分利用神经网络对非线性系统的拟合能力,并在控制过程中实时对神经网络连接权值、阈值进行优化,实现自适应预测的滚动优化,保证了控制器对PEMFC控制的实时性;在控制过程中将输出电压分别反馈至自适应模型及预测控制前端,以提高系统的响应速度和控制精度。验证结果表明:基于自适应预测的控制方法具有较强的鲁棒性,学习能力强,控制精度高,并具有自适应能力,对质子交换膜燃料电池输出动态特性的稳定性具有较好的控制效果。PEMFC is a complex system which is often affected by many parameters. Its time-varying performance, nonlinear performance and uncertainty lead to its dynamic output unable to be controlled. Taking that into account, the controller based on adaptive prediction control was designed to control the dynamic output of PEMFC. The neural network model of PEMFC system was used as a predictive model of the controller, which could make full use of the nonlinear fitting ability of neural networks. Through optimizing the neural network connection weights and threshold in real time, receding horizon optimization could be realized, which could guarantee the real-time control and the effective electrochemical reaction. During the control process, the control precision and response speed of the system could be improved by the introduction of the negative feedback control to the front of adaptive model and predictive control. The simulation results show that the adaptive prediction controller owns adaptive ability, stronger robustness, stronger learning ability and higher control precision, and it has perfect control effect on the dynamic stability of proton exchange membrane fuel cell output characteristics.

关 键 词：质子交换膜燃料电池 时变非线性系统 自适应预测控制 

分 类 号：TM911.4[电气工程—电力电子与电力传动]