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浙江大学学报(工学版)
J4  2013, Vol. 47 Issue (4): 650-655    DOI: 10.3785/j.issn.1008-973X.2013.04.013
自动化技术、电信技术     
基于自适应观测器的飞行器抗干扰控制
贺乃宝1, 高倩1, 徐启华1, 姜长生2
1.淮海工学院 电子工程学院, 江苏 连云港 222005；2.南京航空航天大学 自动化学院,江苏 南京 210016
Anti-interference control of NSV based on adaptive observer
HE Nai-bao1, GAO Qian1, XU Qi-hua1, JIANG Chang-sheng2
1.School of Electrical Engineering, Huaihai Institute of Technology, Lianyungang 222005, China;
2.College of Automatic Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
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摘要：

针对近空间飞行器(NSV)在高超音速飞行时气动参数变化剧烈且容易受到外界干扰的特点,提出快速自适应干扰观测器抗干扰方法.建立近空间飞行器的数学模型,进行抗干扰自适应观测器的设计.通过调整自适应参数和设计补偿项的自适应律,在自适应律中增加非线性指数项,提高了干扰观测系统对复合干扰的逼近速度,使其能够在有限时间内将系统误差收敛为零.对闭环系统性能进行严格的理论分析.在高超声速条件下对NSV进行仿真验证,结果表明,设计的控制方案具有更好的快速性和收敛性.
Abstract:

An anti-disturbance control method with fast adaptive disturbance observer was proposed for near-space vehicle (NSV) that would have severely changed aero-dynamic parameters and external disturbances during hypersonic flight. The mathematical model was built for the motion of NSV. Then the anti-disturbance adaptive observer was designed by employing an adaptive law which is based on the adaptive parameters and the compensation term against tracking errors. A nonlinear exponential term was employed into the adaptive law, so that the approaching rapidity of the adaptive disturbances observer was increased. Moreover, the proposed control scheme can make the system errors converge to zero in the finite time. The strict theoretical analysis was driven to analyze the performance of the closed-loop system. The simulation validation was implemented and the simulation results showed the good performance of the proposed control strategy for NSV in rapidity and convergence.
出版日期: 2013-04-01
:  TP 273  
基金资助:

国家自然科学基金资助项目（60974106,90716028）;连云港工业攻关计划资助项目（CG1123）.
作者简介: 贺乃宝（1967—）,男,教授,从事智能控制、鲁棒控制研究.E-mail: henaibao@126.com
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贺乃宝, 高倩, 徐启华, 姜长生. 基于自适应观测器的飞行器抗干扰控制[J]. J4, 2013, 47(4): 650-655.

HE Nai-bao, GAO Qian, XU Qi-hua, JIANG Chang-sheng. Anti-interference control of NSV based on adaptive observer. J4, 2013, 47(4): 650-655.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2013.04.013    或    http://www.zjujournals.com/eng/CN/Y2013/V47/I4/650

［1］ CAITLIN H. USAF successfully tests X-51A WaveRider ［J］.  Jane’s Defence Weekly, 2010, 47(22): 13-15.

［2］ LISA F, ANDREA S. Adaptive restricted trajectory tracking for a non-minimum phase hypersonic vehicle model ［J］. Automatica, 2012, 48(7): 1248-1261.

［3］ HU X, WU L, HU C. Fuzzy guaranteed cost tracking control for a flexible air-breathing hypersonic vehicle ［J］. IET Control Theory Applications, 2012, 6(9): 1238-1249.

［4］ LISA F, ANDREA S, MICHAEL A. Nonlinear robust adaptive control of flexible air-breathing hypersonic vehicles ［J］. Journal of Guidance, Control and Dynamics, 2009, 32(2): 402-417.

［5］ CHEN M, JIANG C S, WU Q X. Disturbance-observer-based robust flight control for hypersonic vehicles using neural networks ［J］. Advanced Science Letters,2011,4(5): 1771-1775.

［6］ GAO D X, SUN Z Q. Fuzzy tracking control design for hypersonic vehicles via T-S model ［J］. Science China Information Sciences, 2011, 54(3): 521-528.

［7］ SHEN Q, JIANG B, COCQUEMPOT V. Fault diagnosis and estimation for near-space hypersonic vehicle with sensor faults ［J］. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2012, 226(1): 302-313.

［8］ WU Y J, LIU X D, TIAN D P. Research of compound controller for flight simulator with disturbance observer ［J］. Chinese Journal of Aeronautics, 2011, 24 (5): 613-621.

［9］ CHEN W H. nonlinear disturbance observer enhanced dynamic inversion control of missiles ［J］. Journal of Guidance Control and Dynamics, 2003,26(1): 161-166.

［10］ LI X, XIAN B, CHEN D. Output feedback control of hypersonic vehicles based on neural network and high gain observer ［J］. Science China Information Sciences, 2011, 54(3): 429-447.

［11］ SHAUGHNESSY J D, PINCKNEY S Z, MCMINN J D, et al. Hypersonic vehicle simulation model: winged-cone configuration ［R］. USA: NASA, 1990: 1-140.

［12］ KIM E. A fuzzy disturbance observer and its application to control ［J］. IEEE Transactions on Fuzzy Systems, 2002, 10(1) : 77-84.

［13］ YU S, YU X, MAN H. A fuzzy neural network approximator with fast terminal sliding mode and its applications ［J］. Fuzzy Sets and Systems, 2004, 148(2): 469-486.
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