面向非沿轨迹成像的切比雪夫神经网络滑模姿态控制

doi:10.7527/S1000-6893.2015.0114

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面向非沿轨迹成像的切比雪夫神经网络滑模姿态控制

叶东¹, 屠园园², 孙兆伟¹

1. 哈尔滨工业大学航天学院, 哈尔滨 150001;
2. 北京控制工程研究所, 北京 100190

收稿日期:2014-08-27 修回日期:2015-04-30 出版日期:2015-09-15 发布日期:2015-10-13
通讯作者: 屠园园女, 硕士研究生。主要研究方向: 航天器姿态控制。 Tel: 0451-86402357 E-mail: tyyfti@163.com E-mail:tyyfti@163.com
作者简介:叶东男, 博士, 讲师。主要研究方向: 航天器姿态快速机动控制, 姿态控制半物理仿真。 E-mail: yed@hit.edu.cn
基金资助:
中央高校基本科研业务费专项资金(HIT.NSRIF.2015033)

Sliding mode control for nonparallel-ground-track imaging using Chebyshev neural network

YE Dong¹, TU Yuanyuan², SUN Zhaowei¹

1. School of Astronautics, Harbin Institute of Technology, Harbin 150001, China;
2. Beijing Institute of Control Engineering, Beijing 100190, China

Received:2014-08-27 Revised:2015-04-30 Online:2015-09-15 Published:2015-10-13
Supported by:
The Fundamental Research Funds for the Central Universities (HIT.NSRIF.2015033)

摘要/Abstract

摘要：

针对地面兴趣点不沿星下点轨迹的动态非沿轨迹成像问题,设计了一种基于切比雪夫神经网络(CNN)的非奇异快速终端滑模控制器。首先,研究了非沿轨迹成像模式的姿态调整方法,并推导了相应的期望姿态角和姿态角速度。其次,基于由误差四元数描述的跟踪运动学模型设计了非奇异快速终端滑模(NFTSM)控制器。为提高控制精度,引入了只需要期望信号的CNN来估计系统总扰动,从而有效削弱了滑模系统的固有抖振。为保证神经网络的输出有界,引入一个开关函数以实现自适应神经网络(ANN)与鲁棒控制之间的切换控制。最后,对具有干扰和参数不确定的姿态控制系统进行了数值仿真,结果表明该方法收敛速度快,控制精度高,具有一定的工程实际意义。

关键词: 遥感成像, 姿态跟踪, 滑模控制, 切比雪夫神经网络(CNN), 李雅普诺夫方法

Abstract:

A nonsingular and fast terminal sliding mode controller based on the Chebyshev neural network (CNN) is designed for nonparallel-ground-track imaging mode, whose ground targets and ground track are not parallel. Firstly, the specific method of attitude adjustment for nonparallel-ground-track imaging mode is studied to get the desired attitude angle and angular velocity. Secondly, according to the tracking dynamic and kinematic model described by quaternion error, a nonsingular and fast terminal sliding mode (NFTSM) controller is derived. In order to enhance control accuracy, a CNN that is implemented using only desired signals is introduced to approximate the general disturbance which efficiently weakens the chattering inherent in sliding mode structure. In order to guarantee that the output of the NN used in the controller is bounded by the corresponding bound of the approximated disturbance, a switch function is applied to generating a switching between the adaptive neural network (ANN) control and the robust controller. Finally, numerical simulations on the attitude tracking control of spacecraft in the presence of environmental disturbance and parameters' uncertainties are performed, the results of which show that the designed control scheme has fast convergence, high control accuracy and certain actual engineering significance.

Key words: remote sensing, attitude tracking, sliding mode control, Chebyshev neural network (CNN), Lyapunov method

中图分类号:

V448.22

叶东, 屠园园, 孙兆伟. 面向非沿轨迹成像的切比雪夫神经网络滑模姿态控制[J]. 航空学报, 2015, 36(9): 3092-3104.

YE Dong, TU Yuanyuan, SUN Zhaowei. Sliding mode control for nonparallel-ground-track imaging using Chebyshev neural network[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(9): 3092-3104.

参考文献

[1] Huang Q D, Yang F, Zhao J. Drift angle analysis for agile satellite imaging when its attitude points to the Earth changing continuously[J]. Journal of Astronautics, 2012, 33(10): 1544-1551 (in Chinese). 黄群东, 杨芳, 赵键. 姿态对地指向不断变化成像时的偏流角分析[J]. 宇航学报, 2012, 33(10): 1544-1551.
[2] Nijmeijer H, Schaft A J. A nonlinear dynamical control systems[M]. New York: Springer, 1990: 1-22.
[3] Brockett R W, Millman R S, Sussman J J. Differential geometric control theory[M]. Birkhauser, 1983: 181-191.
[4] Aranda-Bricaire E, Moog C H, Pomet J B. A linear algebraic framework for dymamic feedback linearization[J]. IEEE Transactions on Automatic Control, 1995, 40(1): 127-132.
[5] Bodson M, Chiasson J. Differential geometric methods for control of electric motors[J]. International Journal of Robust and Nonlinear Control, 1998, 8: 923-954.
[6] Guo M W. Research on disturbance rejection of space attitude control[D]. Harbin: Harbin Institute of Technology, 2010 (in Chinese). 郭敏文. 航天器姿态控制的干扰抑制问题研究[D]. 哈尔滨: 哈尔滨工业大学, 2010.
[7] Vadali S R. Variable-structure control of spacecraft large-angle maneuvers[J]. Journal of Guidance, Control , and Dynamics, 1986, 9(2): 235-239.
[8] Wang B Q, Gong K, Yang D. Fine attitude control by reaction wheels using variable-structure controller[J]. Acta Astronautica, 2003, 52: 613-618.
[9] Ding S H, Li S H. Sliding mode control of spacecraft attitude with finite-time convergence[C]//Proceedings of the 6th World Congress on Intelligent Control and Automation, 2006: 830-834.
[10] Li J Q, Post M, Lee R. Real-time nonlinear attitude control system for nanosatellite applications[J]. Journal of Guidance, Control, and Dynamics, 2013, 36(6): 1661-1671.
[11] Pukdeboon C, Zinober A S I, Thein M W L. Quasi-continuous higher order sliding mode controllers for spacecraft attitude tracking maneuvers[J]. IEEE Transactions on Industrial Electronics, 2010, 57(4): 1436-1444.
[12] Cao L, Sheng T, Chen X Q. A non-singular terminal adaptive fuzzy sliding-mode controller[C]//Proceedings of 2011 Second International Conference on Digital Manufacturing & Automation, 2011: 74-80.
[13] Wie B, Bailey D, Heiberg C J. Singularity robust steering logic for redundant single-gimbal control moment gyros[J]. Journal of Guidance, Control, and Dynamics, 2001, 24(5) : 865-872.
[14] Huang Q D, Yang F, Zhao J. Research on attitude guidance technology for agile satellite wide regional dynamic imaging[J]. Spacecraft Engineering, 2013(4): 17-22 (in Chinese). 黄群东, 杨芳, 赵键. 敏捷卫星宽幅动态成像姿态调整技术研究[J]. 航天器工程, 2013(4): 17-22.
[15] Guan P, Chen J B. The adaptive fuzzy sliding mode control for flexible satellite[J]. Aerospace Control, 2004, 22(4): 62-67 (in Chinese). 管萍, 陈家斌. 挠性卫星的自适应模糊滑模控制[J]. 航天控制, 2004, 22(4) : 62-67.
[16] Zou A M, Kumar K D. Adaptive attitude control of spacecraft without velocity measurements using Chebyshev neural network[J]. Acta Astronautica, 2010, 66(5-6): 769-779.
[17] Zou A M, Krishna D K. Finite-time attitude tracking control for spacecraft using terminal sliding mode and Chebyshev neural network[J]. IEEE Transactions on Systerms, Man, and Cybernetics-Part B: Cybernetics, 2011, 41(4): 950-963.
[18] Zou A M, Krishna D K, Hou G Z. Distributed consensus control for multi-agent systems using terminal sliding mode and Chebyshev neural networks[J]. International Journal of Robust and Nonlinear Control, 2013, 23(3): 334-357.
[19] Zou A M, Krishna D K, Hou Z G. Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks[J]. IEEE Transactions on Neural Networks, 2010, 21(9): 1457-1471.
[20] Lewis F L, Abdallah C T, Dawson D M. Robot manipulator control theory and practice[M]. New York: Marcel Dekker, 2004: 67-79.

E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

面向非沿轨迹成像的切比雪夫神经网络滑模姿态控制

Sliding mode control for nonparallel-ground-track imaging using Chebyshev neural network

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