基于模糊神经网络的捷联惯导系统初始对准快速优化方法

X. Bo, Sun Feng, Yu Fei, Liu Fuqiang
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引用次数: 1

摘要

提出了一种将LQ最优控制应用于捷联惯导系统初始对准的方法。对该方法进行了详细的分析,并对系统中出现的近似阶跃干扰进行了抗干扰设计,为获得最优控制参数,该方法采用模糊神经网络。通过仿真验证了该方案的初始对准效果,获得了与其他对准方法相同的精度。最重要的是,LQ最优控制的使用大大缩短了对准时间,比其他传统方法快得多。仿真发现,当初始误差角小于10度时;误差角会在几秒钟内收敛到相当高的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Fast and Optimal Method Based on Fuzzy Neural Networks for SINS Initial Alignment
The paper presents an approach which applies LQ optimal control in Strap-down Inertial Navigation System (SINS) initial alignment. The detailed analysis process about this method has been shown, and anti-jamming designs were done for the approximate step-wise disturbance which appeared in the system, to gain the optimal control parameter, the fuzzy neural network is used in the method. Simulations are performed to validate the scheme for initial alignment, obtained the same precision to other alignment method. And the most splendid was that the using of the LQ optimal control reduces the alignment time consumedly much more quickly than other traditional method. What is discovered in the simulation is while the initial error angles were smaller than 10 degrees; error angle will converge to quite good precision in several seconds.
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