| 引用本文: | 戚志东,朱新坚.基于一种FGA–ANFIS技术的DMFC温度建模和控制[J].控制理论与应用,2008,25(4):738~742.[点击复制] |
| QI Zhi-dong,ZHU Xin-jian.Temperature modeling and control of DMFC based on FGA–ANFIS technology[J].Control Theory and Technology,2008,25(4):738~742.[点击复制] |
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| 基于一种FGA–ANFIS技术的DMFC温度建模和控制 |
| Temperature modeling and control of DMFC based on FGA–ANFIS technology |
| 摘要点击 1382 全文点击 1003 投稿时间：2005-09-23 修订日期：2007-05-09 |
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| DOI编号 10.7641/j.issn.1000-8152.2008.4.028 |
| 2008,25(4):738-742 |
| 中文关键词 直接甲醇燃料电池 自适应神经模糊推理系统 模糊遗传算法 |
| 英文关键词 direct methanol fuel cell adaptive neural fuzzy inference system fuzzy genetic algorithms |
| 基金项目 国家863项目资助(2002AA517020). |
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| 中文摘要 |
| 为了提高直接甲醇燃料电池(DMFC)的发电性能, 采用自适应神经模糊推理技术(FGA–ANFIS)对电池的工作温度进行建模与控制. 首先, 基于实验的输入输出数据建立了DMFC电堆温度的自适应神经模糊辨识模型, 避开了DMFC电堆的内部复杂性. 然后, 将训练好的网络模型作为DMFC控制系统的参考模型, 采用一种改进的模糊遗传算法对神经模糊控制器的参数和模糊规则进行自适应调整. 最后, 通过仿真, 将所提出的算法与非线性PID和传统模糊算法进行比较, 结果表明所设计的神经模糊控制器具有较好的性能 |
| 英文摘要 |
| To improve the performance of a direct methanol fuel cell (DMFC), the adaptive neural fuzzy inference (FGA–ANFIS) technology is applied to the modeling and control of a DMFC temperature system. First, an adaptive neural fuzzy inference system (ANFIS) identification model of DMFC stack temperature is developed based on the input-output sampled data, getting around the internal complexity of DMFC stack. Then, taking the well-trained network model as the reference model of the control system of DMFC stack, we use a novel fuzzy genetic algorithm (FGA) for adaptively adjusting the parameters and fuzzy rules of a neural fuzzy controller. Simulation results demonstrate better performance of this neural fuzzy controller in comparison with those of the nonlinear PID and traditional fuzzy algorithm. |