基于HGA的模糊神经控制充电器设计与实现

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.

DESIGN AND REALIZATION OF CHARGER OF FUZZY NEURAL CONTROLLER BASED ON HGA

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.