Eigenstructure Assignment Based Flight Control for Advanced Fighter: An Optimization Based Approach

Yong Fan, Jihong Zhu, Chunning Yang, Zeng-qi Sun
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引用次数: 8

Abstract

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, close-loop eigenvalues are also optimised within desired regions on the left-half complex plane according to the design objective 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 simulation results show good closed loop performance and validate the proposed intelligent optimization approach of EA technique.
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基于特征结构分配的先进战斗机飞行控制:一种基于优化的方法
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。其基本思想是利用EA技术提供的设计自由度,最小化期望矢量与可实现矢量之间的L2范数误差。此外,在复平面左半部分的期望区域内,根据设计目标对闭环特征值进行优化,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。仿真结果表明,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。
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