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首页> 外文期刊>International Journal of Control, Automation, and Systems >Multivariable Autopilot Design for Sounding Rockets using Intelligent Eigenstructure Assignment Technique
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Multivariable Autopilot Design for Sounding Rockets using Intelligent Eigenstructure Assignment Technique

机译:基于智能特征结构分配技术的火箭探测多变量自动驾驶仪设计

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摘要

When a sounding rocket rolls about its longitudinal axis, the role of angle of attack and sideslip angle exchange regularly. This interchange causes the aerodynamic moments to alternate between pitching and yawing moments, which, coupled with the moment of inertia effects, further aggravates the inertial cross-coupling. In this paper, first we analyze the cross-coupling phenomena and derive a Linear, Time-Invariant (LTI), multi input - multi output model of a spinning sounding rocket and then we design an autopilot for this system. An application of multivariable control technique is presented to the design of the autopilot. The involved controller is advanced by combining Eigenstructure Assignment (EA) approach with the Particle Swarm Optimization (PSO) algorithm. Results of linear and nonlinear simulations are reported to demonstrate the performance and stability margin of the considered autopilot.
机译:当探空火箭绕其纵轴滚动时,迎角和侧滑角的作用会定期交换。这种互换导致空气动力学力矩在俯仰力矩和偏航力矩之间交替,这与惯性矩效应相结合,进一步加剧了惯性交叉耦合。在本文中,我们首先分析了交叉耦合现象,并推导了旋转探测火箭的线性,时不变(LTI),多输入多输出模型,然后为该系统设计了自动驾驶仪。介绍了多变量控制技术在自动驾驶仪设计中的应用。通过将特征结构分配(EA)方法与粒子群优化(PSO)算法相结合,可以提高所涉及的控制器的性能。据报道,线性和非线性仿真结果证明了所考虑的自动驾驶仪的性能和稳定性。

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