期刊文献+

无人机非线性非仿射飞控系统的自适应模糊H_∞输出反馈控制及其应用 被引量:1

Adaptive Fuzzy H_∞ Output Feedback Control and Its Application in Non-affine Nonlinear Flight Control System of UAV
在线阅读 下载PDF
导出
摘要 研究了非仿射非线性系统的模糊自适应H∞输出反馈跟踪。在非仿射非线性模型不确定或未知的情况下,首先将非仿射系统展开为仿射系统的形式,使用模糊自适应控制器对系统进行控制,然后基于Lyapunov稳定性定理得出自适应律,并通过解一个代数Riccati方程实现了H∞跟踪性能。在状态不可测情况下,引入高增益观测器估计系统状态并设计了输出反馈控制器,实现了系统的输出反馈控制性能。最后,通过对无人机飞行控制的仿真验证了算法的有效性。 A fuzzy adaptive H∞ output feedback controller for non-affine nonlinear systems is studied. Considering the uncertainties and un-modeled dynamics, firstly, the non-affine system is expanded to the form of an affine system, and a fuzzy logic adaptive controller is employed to control the system. Then, adaptive laws are designed based on Lyapunov stability theorem. Secondly, H∞ tracking performance is achieved through solving an algebra Riccati equation. In unobservable cases of systems states, a high gain observer is employed to obtain the estimation of states, and an output feedback controller is designed to achieve the performance of output feedback control. Finally, a simulation example of flight control of unmanned aerial vehicle (UAV) is given to illustrate the effectiveness of the proposed method.
出处 《南京航空航天大学学报》 EI CAS CSCD 北大核心 2013年第1期99-103,共5页 Journal of Nanjing University of Aeronautics & Astronautics
基金 国家自然科学基金(60716028)资助项目
关键词 自适应模糊 非仿射非线性系统 H∞ 输出反馈 高增益观测器 adaptive fuzzy non-affine nonlinear system H∞ output feedback high gain observer
  • 相关文献

参考文献10

  • 1Zou A M,Hou Z G,Tan M. Adaptive control of a class of nonlinear pure-feedback systems using fuzzy backstepping approach[J].IEEE Transactions on Fuzzy Systems,2008,(04):886-897.doi:10.1109/TFUZZ.2008.917301.
  • 2刘艳军,王伟.一类多变量非线性系统的自适应模糊控制[J].自动化学报,2007,33(11):1163-1169. 被引量:13
  • 3Liu Y J,Wang W. Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems[J].Information Sciences,2007,(18):3901-3917.doi:10.1016/j.ins.2007.03.005.
  • 4Chen Borsen,Lee Chinghsing,Chang Yeongchan. H∞ tracking design of uncertain nonlinear SISO systems:Adaptive fuzzy approach[J].IEEE Transactions on Fuzzy Systems,1996,(01):32-43.
  • 5Liu Y J,Tong S C,Wang W. Adaptive fuzzy output tracking control for a class of uncertain nonlinear systems[J].Fuzzy Sets and Systems,2009,(19):2727-2754.doi:10.1016/j.fss.2008.12.016.
  • 6Wang M,Ge S S,Hong K S. Approximation-based adaptive tracking control of pure-feedback nonlinear systems with multiple unknown time-varying delays[J].IEEE Transactions on Neural Networks,2010,(11):1804-1816.
  • 7Ren B B,Ge S S,Lee T H. Adaptive neural control of SISO non-affine nonlinear time-delay systems with unknown hysteresis input[A].Washington,USA:[s.n.],2008.4203-4208.
  • 8Lin S C,Chen Y Y. Design of self-learning fuzzy sliding mode controllers based on genetic algorithms[J].Fuzzy Sets and Systems,1997,(02):139-153.
  • 9Park J H,Kim S H. Direct adaptive output-feedback fuzzy controller for a nonaffine nonlinear system[J].IEE Proceedings-Control Theory and Applications,2004,(01):65-72.doi:10.1049/ip-cta:20040011.
  • 10RenB B,Ge S S,Su C Y. Adaptive neural control for a class of uncertain nonlinear systems in pure-feedback form with hysteresis input[J].IEEE Trans Systems Man Cybernetics-Part B:Cybernetics,2009,(02):431-443.

二级参考文献14

  • 1Krstic M, Kanellakopoulos I, Kokotovic P. Nonlinear and Adaptive Control Design. New York: Weley Interscience, 1995.
  • 2Wang L X. Fuzzy systems are universal approximators. In: Proceedings of IEEE International Conference on Fuzzy Systems. San Diego: 1992. 1163-1170.
  • 3Park J, Sandberg I W. Universal approximation using radial-basis-function network. Neural Computation, 1991, 3(2): 246-257.
  • 4Tong S C, Wang T, Tang J T. Fuzzy adaptive output tracking control of nonlinear systems. Fuzzy Sets and Systems, 2000, 111(2): 169-182.
  • 5Tong S C, Li H X. Direct adaptive fuzzy output tracking control of nonlinear systems. Fuzzy Sets and Systems, 2002, 128(1): 107-115.
  • 6Tong S C, Tang J T, Wang T. Fuzzy adaptive control of multivariable nonlinear systems. Fuzzy Sets and Systems, 2000, 111(2): 153-167.
  • 7Labiod S, Boucherit M S, Guerra T M. Adaptive fuzzy control of a class of MIMO nonlinear systems. Fuzzy Sets and Systems, 2005, 151(1): 59-77.
  • 8Wang W Y, Chan M L, Lee T T, Liu C H. Adaptive fuzzy control for strict-feedback canonical nonlinear systems with H∞ tracking performance. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 2000, 30(6): 878-885.
  • 9Ge S S, Wang J. Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems, IEEE Transactions on Neural Networks, 2002, 13(6): 1409-1419.
  • 10Yang Y S, Zhou C J. Adaptive fuzzy H∞ stabilization for strict-feedback canonical nonlinear systems via backstepping and small-gain approach, IEEE Transactions on Fuzzy Systems, 2005, 13(1): 104-114.

共引文献12

同被引文献7

引证文献1

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部