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,提出了基于递阶遗传算法的模糊神经网络优化算法来进行蓄电池的充电控制,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,实现对非线性的、时变的、有干扰的、具有纯滞后的蓄电池充电控制系统的最佳控制.
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 control to charge,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. It realize the nonlinear,mutative,interferential and hysteresis instance, for the sake of actualizing optimal control.
出处
《陕西科技大学学报（自然科学版）》
2009年第4期107-111,共5页
Journal of Shaanxi University of Science & Technology
关键词
递阶遗传算法
模糊神经网络
充电控制
hierarchical genetic algorithm
fuzzy neural network
control of charging
