Adaptive internal model control research in autonomous landing phase for a fixed-wing UAV

被引：0
|
作者：
Gao J.-Z. [1 ,2 ]
Jia H.-G. [1 ]
机构：
[1] Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun
[2] University of Chinese Academy of Sciences, Beijing
来源：
CEAS Aeronautical Journal | 2017年 / 8卷 / 01期
关键词：
AIMC; Autonomous landing; Estimation of process model; Filter parameter adjustment; Monte Carlo simulation;
D O I：
10.1007/s13272-016-0216-1
中图分类号：
学科分类号：
摘要：
Autonomous landing is a very complex phase of flight for unmanned aerial vehicle (UAV). Adaptive internal model control (AIMC) is proposed and applied on autonomous landing control system in this paper. Controllers are designed based on the decoupled and linearized models of a sample UAV. Estimation of process model is carried out to enhance system robustness, and filter parameter adjustment is proposed to achieve a good dynamic performance. Control effects are compared and analyzed between IMC and AIMC in different wind conditions which demonstrate that AIMC has better performances than IMC. At last, Monte Carlo simulations prove the system stability. © 2016, The Author(s).
引用
收藏
页码：45 / 51
页数：6
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