计算机应用研究2011，Vol.28Issue(9)：3387-3389,3.DOI:10.3969/j.issn.1001-3695.2011.09.052
基于自结构动态递归模糊神经网络的无人机姿态控制
Motion control for unmanned aircraft vehicle based on self-structuring recurrent fuzzy neural network
摘要
Abstract
This paper designed motion control system of micro aircraft vehicle based on self-organizing dynamic recurrent fuzzy neural network, and proved the stability of the motion control system based on Lyapunov function. It proposed a new self-organizing dynamic recurrent fuzzy neural network based on the fuzzy neural networks with four layers, the weights and nodes of the proposed network could be updated online for network structure optimization. Simulation results demonstrate that the proposed control scheme can effectively improve stability and tracking performance with strong uncertainty, nonlinear and extern disturbance. Compared with fixed structured fuzzy neural network, the proposed self-organizing dynamic recurrent fuzzy neural network has advantages in estimation speed.关键词
自结构动态递归模糊神经网络/优化网络结构/响应速度快Key words
self-organizing recurrent fuzzy neural network/ optimization of network structure/ fast response分类
信息技术与安全科学引用本文复制引用
陈向坚,白越,续志军,李迪..基于自结构动态递归模糊神经网络的无人机姿态控制[J].计算机应用研究,2011,28(9):3387-3389,3.基金项目
国家自然科学基金资助项目(50905174) （50905174）
