中国科技核心期刊

中文核心期刊

CSCD来源期刊

空间控制技术与应用

• 论文与报告 • 上一篇    下一篇

平流层飞艇巡航姿态自适应神经网络补偿控制

刘其睿1, 李勇2   

  1. 1.北京控制工程研究所,空间智能控制技术国家级重点实验室,北京100190; 2.中国空间技术研究院研究发展中心,北京100094
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-08-26 发布日期:2009-08-26

Adaptive Neural Network Compensation for Stratospheric Airship Attitude Control of Cruising Phase

LIU Qi-rui1, LI Yong2   

  1. 1. National Laboratory of Space Intelligent Control, Beijing Institute of Control Engineering, Beijing 100190, China;
    2. R&D Center, China Academy of Space Technology, Beijing 100094, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-08-26 Published:2009-08-26

摘要: 研究了一种基于自适应神经网络补偿的平流层飞艇前向速度与姿态控制系统设计方法。针对近似模型进行常规线性动态补偿器设计,并引入自适应径向基函数(Radial Basis Function, RBF)神经网络对模型误差进行补偿。根据Lyapunov方法得到神经网络权值自适应律,保证了闭环系统误差信号一致最终有界。该控制器设计对模型参数信息仅有较少的要求。仿真结果表明对于两类不同的飞艇模型,所设计的控制器在响应性及对未知环境风速作用的鲁棒性方面均具有良好的效果。

关键词: 平流层飞艇, 巡航姿态, 神经网络

Abstract: By designing a speed and attitude control system based on adaptive neural network compensation,this paper presents a solution of solving the cruise tracking control problem for the stratospheric airship. An adaptive RBFNN (Radial Basis Function Neural Network ) is used to compensate modeling errors, which come from the approximate model applied to a regular linear controller design. The network weight adaptation rule, derived from Lyapunov stability analysis, guarantees that the adapted weight errors and the tracking errors are bounded. The controller design exploits only a little information of model parameters. Simulation results demonstrate the excellent performance and robustness of the controller, even if environmental winds with unknown information exist.

Key words: stratospheric airship, cruise tracking, neural network, adaptive control

中图分类号: 

  • v448