基于DHP方法的PEM燃料电池优化控制器设计

摘要

质子交换膜燃料电池(PEMFC)系统具有明显的非线性和时变的特质，因此质子交换膜燃料电池的建模和优化控制问题是研究的重点。通过建立单体质子交换膜燃料电池的近似线性动态模型，并在此模型基础上，设计了基于双启发式动态规划(DHP)的质子交换膜燃料电池神经网络优化控制器。仿真结果表明，此近似线性模型有效地简化了非线性和时变的特质，在此模型基础上所设计的神经网络控制器具有更好的控制效果和控制精度。%Proton exchange membrane fuel cell(PEMFC) system had obvious nonlinear and time-varying characteristics, so the study of proton exchange membrane fuel cellsystem neural network optimization control was necessary. The approximation linear dynamic model of a single proton exchange membrane fuel cellwas established. Then based on the approximation linear model, the optimization control er based on the dual heuristic dynamic programming (DHP) of was designed. Simulation results show that the nonlinear and time-varying characteristics are effectively simplified by this approximate linear model, and the proposed neural network control er has better control effect and control accuracy.