基于HGA的模糊神经控制器设计及其应用  

The Design and Application of Fuzzy Neural Controller Based on HGA

作　　者：常江[1] 景占荣[1] 高田[1] 

机构地区：[1]西北工业大学,西安710072

出　　处：《计算机工程与应用》2006年第14期222-224,共3页Computer Engineering and Applications

摘　　要：将神经网络与模糊控制相结合,实现了模糊控制器的自学习和自适应。给出一种基于递阶遗传算法的模糊神经网络优化算法,通过对每个染色体采用递阶编码,可以同时优化模糊神经网络结构和权值参数。将这种模糊神经网络控制器应用于镍氢电池的充电控制中,证明了算法的有效性。Combine the neural network with controlling fuzzy control ,the ones that have realized the fuzzy controller are from the self-study and self-adaptation.Based on hierarchical genetic algorithm,an algorithm is proposed to optimize fuzzy neural network.In the proposed algorithm,the hierarchical coding is adopted to each chromosome,so it can evolve both the fuzzy neural network＇s topology and weighting parameters.Such fuzzy neural network controller is applied to the control of nickel hydrogen battery charging,have proved the validity of the algorithm.

关 键 词：递阶遗传算法 模糊神经网络 充电控制 

分 类 号：TP301[自动化与计算机技术—计算机系统结构] TP138[自动化与计算机技术—计算机科学与技术]