自适应聚焦粒子群算法是根据粒子群优化(particle swarm optimization，PSO)算法的全局搜索与局部搜索平衡特性，改进得到的一种具有较好全局搜索能力和寻优速度的自适应群体智能优化算法。为实现对质子交换膜燃料电池(proton exchange membrane fuel cell，PEMFC)空气供应系统的控制，建立空气供应系统机理模型，并采用多目标自适应聚焦粒子群(adaptive focusing particle swarm optimization，AFPSO)算法提出H∞鲁棒控制方法。仿真结果证明该H￥鲁棒控制方法能够实现对PEMFC空气供应系统的控制，在模拟电动车行驶过程时可使系统稳定运行，并与其它控制方法比较，证明该H￥鲁棒控制方法具有明显的优越性和有效性，对PEMFC实时控制系统的研究有重要的指导作用。

Adaptive focusing particle swarm optimization (AFPSO) based on the balance characteristic between global search and local search of particle swarm optimization was an adaptive swarm intelligence optimization algorithm with preferable ability of global search and search rate. In order to control the air supply system of proton exchange membrane fuel cell (PEMFC), an air supply system mechanism model of PEMFC was developed and multi-objective AFPSO was proposed to achieve H∞ robust control for this model. The simulation results show that the H∞ robust control method could obtain great control effect for the air supply system of PEMFC and make the system stable operation when the vehicle running process was simulated. The comprehensive comparison with other control methods demonstrate that the H∞ robust control method had manifest superiority and validity. Therefore, the H∞ robust control based on multi-objective AFPSO makes important supervise effect for designing the real-time control system of PEMFC.

西南交通大学科技发展研究基金项目(A017)。