空天飞行器的鲁棒自适应模糊轨迹线性化控制

张春雨; 姜长生

空天飞行器的鲁棒自适应模糊轨迹线性化控制

南京航空航天大学自动化学院, 南京 210016

基金项目: 国家自然科学基金资助(90405011)

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出版历程
- 收稿日期: 2006-05-19
- 修回日期: 2006-10-17
- 刊出日期: 2007-06-28

Robust adaptive fuzzy trajectory linearization control of an aerospace vehicle

College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

摘要

摘要: 提出了鲁棒自适应模糊轨迹线性化控制(RAFTLC)方法并应用于空天飞行器(ASV)飞行控制系统设计.根据系统的先验知识, 设计出标称模糊系统对系统的未知干扰和不确定进行估计, 并通过鲁棒自适应控制项来克服标称模糊系统逼近误差和权值误差的影响.标称模糊系统逼近误差和权值误差的界在线调整.采用Lyapunov方法证明了闭环系统的所有信号一致最终有界.最后利用提出的控制方案设计了ASV飞行控制系统, 并在高超声速条件下进行了仿真验证.仿真结果表明了控制方案的有效性和鲁棒性.
- 航空、航天推进系统 /
- 飞行控制系统 /
- 轨迹线性化控制 /
- 鲁棒自适应控制 /
- 模糊系统 /
- 空天飞行器
Abstract: This paper presents a robust adaptive fuzzy trajectory linearization control(RAFTLC) method and its application to an aero-space vehicle(ASV) flight control system.Based on the system's prior knowledge,the nominal fuzzy system is designed to estimate the unknown disturbances and uncertainties.A robust adaptive item is used to overcome the approximate error and weights error of the nominal fuzzy system.The bounds of the approximate error and weights error are adjusted on line.Uniform ultimate boundedness of all the signals of the composite closed-loop system is proved using Lyapunov theory.Finally,the flight control system of an ASV is designed based on the proposed method.Simulation results demonstrate the effectiveness and robustness of the control scheme.
- aerospace propulsion system /
- fight control system /
- trajectory linearization control(TLC) /
- robust adaptive control /
- fuzzy system /
- aerospace vehicle(ASV)

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参考文献(13)

[1]	Liu Y,Wu X,Zhu J.Omni-directional mobile robot controller design by Trajectory Linearization[A].Proceedings of the American Control[C].Denver:2003:3423-3428.
[2]	Zhu J J,Banker D,Hall C E.X-33 ascent flight control deign by trajectory linearization-a singular perturbation approach[R].AIAA-2000-4159.
[3]	Mickle M C,Zhu J.Bank-to-turn roll-yaw-pitch autopilot design using dynamic nonlinear inversion and PD-eigenvalue assignment[A].Proceedings of the American Control Conference[C].Chicago:2000:1359-1364.
[4]	Kim E.A fuzzy disturbance observer and its application to control[J].IEEE Transactions on fuzzy systems,2002,10(1):77-84.
[5]	Li H X,Tong S C.A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems[J].IEEE Transactions on Fuzzy Systems,2003,11(1):24-34.
[6]	Vélez-Díaz D,Tang Y.Adaptive robust fuzzy control of nonlinear systems[J].IEEE Transactions on Systems,Man,and Cybernetics-Part B:Cybernetics,2004,34(3):1596-1601.
[7]	Barmish B R,Leimann G.On ultimate boundedness control of uncertain systems in the absence of matching assumptions[J].IEEE Trans.on Automatic Control,1982,27:153-158.
[8]	Kahlil H K.Nonlinear systems[M].2nd ed.Prentice-Hall,Upper Saddle River,N J,1996.
[9]	王立新.自适应模糊系统与控制-设计与稳定性分析[M].北京:国防工业出版社,1995.WANG Lixin.Adaptive fuzzy system and control-design and stability analysis[M].Beijing:National Defence Industry Press,1995.
[10]	郑大钟.线性系统理论[M].第2版.北京:清华大学出版社,2002.ZHENG Dazhong.Linear system theory[M].2nd ed.Beijing:Tsinghua University Press,2002.
[11]	Shaughnessy J D,Pinckney S Z,McMinn J D,et al.Hypersonic vehicle simulation model:winged-cone configuration[R].NASA TM-102610,1990.
[12]	Snell S A.Nonlinear dynamic inverse flight control of supermaneuverale aircraft[D].University of Minnesota,1991.
[13]	Zhu J J.A unified spectral theory for linear time-varying systems-progress and challenges[A].Proc.of 34th IEEE Conf.on Decision & Control[C].New Orleans:1995:2540-2546.