基于模糊神经网络的导弹最优寻的末制导律

提出了一种适用于一类末制导段采用推力矢量控制的新型导弹的模糊神经网络最优寻的末制导律.在制导律设计时不仅要求导弹能量最省,脱靶量最小,同时考虑了推力矢量控制的非线性特点,并且为改善该神经网络系统的学习效果,在学习算法中还引入模糊学习规则.数字仿真表明所提出的模糊神经网络制导律对于机动目标具有较好的攻击能力.

Optimal Terminal Missile Guidance Law Based on Fuzzy Neural Networks

Because fuzzy neural networks technique has the advantages not only strong adaptability to nonlinear systems but also quick learning ability, it has been applied to nonlinear systems successfully. an optimal terminal missile guidance law based on fuzzy neural networks for the advanced missiles with thruster vector control is presented. In the design of optimal guidance law, the minimum of missile energy loss and miss distance is required while the nonlinear character of the thruster vector control is considered. In addition, fuzzy learning rules are presented to improve the learning ability of the neural networks system. Numerical simulation results are given to illustrate that the presented fuzzy neural networks guidance law has good performance to hit maneuvering targets.