基于特征结构分配的先进战斗机飞行控制智能优化方法

Yong Fan, Jihong Zhu, Zeng-qi Sun
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引用次数: 0

摘要

提出了一种基于神经网络的特征结构分配智能优化方法,通过神经网络自动调节输出向量的分量。基本思想是利用EA技术提供的设计自由度,最小化期望矢量和可实现矢量之间的L2范数误差。除了调整输出矢量参数外,还在左半复平面的期望区域内优化闭环特征值,以保证闭环稳定性和动态性能。利用该方法,还可以很容易地实现不同模式的解耦和鲁棒性等额外的闭环规范。最后,以某型先进战斗机为例,讨论了该方法在飞行控制律设计中的应用。结果表明,该方法具有良好的闭环性能,验证了EA技术的智能优化方法
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Optimization Approach of Eigenstructure Assignment Based Flight Control for Advanced Fighter
An intelligent optimization approach is proposed for eigenstructure assignment (EA) via neural network (NN) adjusting the components of output vector autonomously. The Basic idea is to minimize the L2 norm of error between the desired vector and achievable vector using the designing freedom provided by EA technique. Besides adjusting the output vector parameters, the closed-loop eigenvalues are also optimized within desired regions on the left-half complex plane to ensure both closed-loop stability and dynamical performance. With the proposed approach, additional closed-loop specifications such as decoupling of different modes and robustness can also be easily achieved. As a demonstration, application of the proposed approach to the designing of flight control law for an advanced fighter is discussed. The results show good closed loop performance and validate the proposed intelligent optimization approach of EA technique
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