2.845

2023影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

不确定非线性时滞关联大系统自适应分散容错控制

郭涛 梁燕军

郭涛, 梁燕军. 不确定非线性时滞关联大系统自适应分散容错控制. 自动化学报, 2017, 43(3): 486-492. doi: 10.16383/j.aas.2017.c150827
引用本文: 郭涛, 梁燕军. 不确定非线性时滞关联大系统自适应分散容错控制. 自动化学报, 2017, 43(3): 486-492. doi: 10.16383/j.aas.2017.c150827
GUO Tao, LIANG Yan-Jun. Adaptive Decentralized Fault-tolerant Control for Uncertain Nonlinear Time-delay Large Scale Systems. ACTA AUTOMATICA SINICA, 2017, 43(3): 486-492. doi: 10.16383/j.aas.2017.c150827
Citation: GUO Tao, LIANG Yan-Jun. Adaptive Decentralized Fault-tolerant Control for Uncertain Nonlinear Time-delay Large Scale Systems. ACTA AUTOMATICA SINICA, 2017, 43(3): 486-492. doi: 10.16383/j.aas.2017.c150827

不确定非线性时滞关联大系统自适应分散容错控制

doi: 10.16383/j.aas.2017.c150827
基金项目: 

河南省基础与前沿技术研究计划 142300410114

河南省创新型科技团队项目 C20150028

河南省高校创新人才项目 15HASTIT021

河南省教育厅自然科学基金项目 13A520017

详细信息
    作者简介:

    梁燕军  安阳师范学院计算机与信息工程学院副教授.2010年获得中国海洋大学博士学位.主要研究方向为振动控制和自适应控制.E-mail:myluck0404@126.com

    通讯作者:

    郭涛  安阳师范学院计算机与信息工程学院副教授.2009年获得西安电子科技大学博士学位.主要研究方向为反推控制, 自适应模糊控制和非线性控制.本文通信作者.E-mail:gtmailbox@126.com

Adaptive Decentralized Fault-tolerant Control for Uncertain Nonlinear Time-delay Large Scale Systems

Funds: 

the Science and Technology Project of Henan Province 142300410114

Innovation Scientists and Technicians Troop Construction Projects of Henan Province C20150028

the Program for Science & Technology Innovation Talents in Universities of Henan Province 15HASTIT021

the Project of Natural Science Foundation of Henan Provincial Department of Education 13A520017

More Information
    Author Bio:

    Associate professor at the School of Computer and Information Engineering, Anyang Normal University. He received his Ph.D. degree from Ocean University of China in 2010. His research interest covers vibration control and adaptive control

    Corresponding author: GUO Tao Associate professor at the School of Computer and Information Engineering, Anyang Normal University. He received his Ph.D. degree from Xidian University in 2009. His research interest covers backstepping control, adaptive fuzzy control, and nonlinear control. Corresponding author of this paper
  • 摘要: 针对一类不确定非线性时滞关联大系统,提出了一种基于时滞代换的自适应分散容错控制方案.该方案采用模糊逻辑系统作为逼近器,提出了时滞代换的方法处理系统未知时滞关联函数,并结合自适应技术处理代换误差和逼近误差.与现有方法相比,本文方法能在线补偿所有四种类型的执行器故障,系统控制器的设计也不再依赖于时滞假设条件,同时还可保证闭环系统所有信号全局一致最终有界.仿真结果进一步验证了本文方法的有效性.
  • 图  1  子系统1仿真结果

    Fig.  1  Simulation results of Subsystem 1

    图  2  子系统2仿真结果

    Fig.  2  Simulation results of Subsystem 2

    图  3  不同设计参数下仿真结果

    Fig.  3  Simulation results under different design parameters

  • [1] Choi J Y, Farrell J A. Adaptive observer backstepping control using neural networks. IEEE Transactions on Neural Networks, 2001, 12(5): 1103-1112 doi: 10.1109/72.950139
    [2] Wang C, Hill D J, Ge S S, Chen G R. An ISS-modular approach for adaptive neural control of pure-feedback systems. Automatica, 2006, 42(5): 723-731 doi: 10.1016/j.automatica.2006.01.004
    [3] Chen W S, Zhang Z Q. Globally stable adaptive backstepping fuzzy control for output-feedback systems with unknown high-frequency gain sign. Fuzzy Sets and Systems, 2010, 161(6): 821-836 doi: 10.1016/j.fss.2009.10.026
    [4] Wu J, Chen W S, Yang F Z, Li J, Zhu Q. Global adaptive neural control for strict-feedback time-delay systems with predefined output accuracy. Information Sciences, 2015, 301: 27-43 doi: 10.1016/j.ins.2014.12.039
    [5] Wu J, Chen W S, Li J. Fuzzy-approximation-based global adaptive control for uncertain strict-feedback systems with a priori known tracking accuracy. Fuzzy Sets and Systems, 2015, 273: 1-25 doi: 10.1016/j.fss.2014.10.009
    [6] Wang M L, Zhang Z Q. Globally adaptive asymptotic tracking control of nonlinear systems using nonlinearly parameterized fuzzy approximator. Journal of the Franklin Institute, 2015, 352(7): 2783-2795 doi: 10.1016/j.jfranklin.2015.04.011
    [7] Huang J T. Global tracking control of strict-feedback systems using neural networks. IEEE Transactions on Neural Networks and Learning Systems, 2012, 23(11): 1714-1725 doi: 10.1109/TNNLS.2012.2213305
    [8] Fu J, Ma R C, Chai T Y. Global finite-time stabilization of a class of switched nonlinear systems with the powers of positive odd rational numbers. Automatica, 2015, 54: 360-373 doi: 10.1016/j.automatica.2015.02.023
    [9] Xu B, Yang C G, Pan Y P. Global neural dynamic surface tracking control of strict-feedback systems with application to hypersonic flight vehicle. IEEE Transactions on Neural Networks and Learning Systems, 2015, 26(10): 2563-2575 doi: 10.1109/TNNLS.2015.2456972
    [10] Chen W S, Ge S S, Wu J, Gong M G. Globally stable adaptive backstepping neural network control for uncertain strict-feedback systems with tracking accuracy known a priori. IEEE Transactions on Neural Networks and Learning Systems, 2015, 26(9): 1842-1854 doi: 10.1109/TNNLS.2014.2357451
    [11] Ge S S, Hong F, Lee T H. Robust adaptive control of nonlinear systems with unknown time delays. Automatica, 2005, 41(7): 1181-1190 doi: 10.1016/j.automatica.2005.01.011
    [12] Tong S C, Li Y, Li Y M, Liu Y J. Observer-based adaptive fuzzy backstepping control for a class of stochastic nonlinear strict-feedback systems. IEEE Transactions on Systems, Man, and Cybernetics: Part B (Cybernetics), 2011, 41(6): 1693-1704 doi: 10.1109/TSMCB.2011.2159264
    [13] Guo T, Liu G Y. Adaptive fuzzy control for unknown nonlinear time-delay systems with virtual control functions. International Journal of Control, Automation and Systems, 2011, 9(6): 1227-1234 doi: 10.1007/s12555-011-0625-1
    [14] Guo T, Wang A M. Simplified output feedback stabilization for time-delay interconnected systems based on dynamic surface control. International Review on Computers and Software, 2012, 7(1): 275-282 https://www.researchgate.net/publication/293080709_Simplified_output_feedback_stabilization_for_time-delay_interconnected_systems_based_on_dynamic_surface_control
    [15] Yang Y, Yue D, Xue Y S. Decentralized adaptive neural output feedback control of a class of large-scale time-delay systems with input saturation. Journal of the Franklin Institute, 2015, 352(5): 2129-2151 doi: 10.1016/j.jfranklin.2015.02.009
    [16] Zhou Q, Shi P, Xu S Y, Li H Y. Observer-based adaptive neural network control for nonlinear stochastic systems with time delay. IEEE Transactions on Neural Networks and Learning Systems, 2013, 24(1): 71-80 doi: 10.1109/TNNLS.2012.2223824
    [17] Chen B, Liu X P, Liu K F, Lin C. Adaptive fuzzy tracking control of nonlinear MIMO systems with time-varying delays. Fuzzy Sets and Systems, 2013, 217: 1-21 doi: 10.1016/j.fss.2012.11.002
    [18] Chen B, Liu X P, Liu K F, Lin C. Adaptive control for nonlinear MIMO time-delay systems based on fuzzy approximation. Information Sciences, 2013, 222: 576-592 doi: 10.1016/j.ins.2012.07.058
    [19] Zhang X, Lin Y. Adaptive control of nonlinear time-delay systems with application to a two-stage chemical reactor. IEEE Transactions on Automatic Control, 2015, 60(4): 1074-1079 doi: 10.1109/TAC.2014.2330436
    [20] Tang X D, Tao G, Joshi S M. Adaptive actuator failure compensation for parametric strict feedback systems and an aircraft application. Automatica, 2003, 39(11): 1975-1982 doi: 10.1016/S0005-1098(03)00219-X
    [21] Wang W, Wen C Y. Adaptive actuator failure compensation control of uncertain nonlinear systems with guaranteed transient performance. Automatica, 2010, 46(12): 2082-2091 doi: 10.1016/j.automatica.2010.09.006
    [22] Fan H J, Liu B, Wang W, Wen C Y. Adaptive fault-tolerant stabilization for nonlinear systems with Markovian jumping actuator failures and stochastic noises. Automatica, 2015, 51: 200-209 doi: 10.1016/j.automatica.2014.10.084
    [23] Tang X D, Tao G, Joshi S M. Virtual grouping based adaptive actuator failure compensation for MIMO nonlinear systems. IEEE Transactions on Automatic Control, 2005, 50(11): 1775-1780 doi: 10.1109/TAC.2005.858633
    [24] Tong S C, Huo B Y, Li Y M. Observer-based adaptive decentralized fuzzy fault-tolerant control of nonlinear large-scale systems with actuator failures. IEEE Transactions on Fuzzy Systems, 2014, 22(1): 1-15 doi: 10.1109/TFUZZ.2013.2241770
    [25] Boskovic J D, Mehra R K. Stable multiple model adaptive flight control for accommodation of a large class of control effector failures. In: Proceedings of the 1999 American Control Conference. San Diego, CA, USA: IEEE, 1999. 1920-1924
    [26] Zhang Z Q, Xu S Y, Guo Y, Chu Y M. Robust adaptive output-feedback control for a class of nonlinear systems with time-varying actuator faults. International Journal of Adaptive Control and Signal Processing, 2010, 24(9): 743-759 doi: 10.1002/acs.v24:9
    [27] Tang X D, Tao G, Joshi S M. Adaptive actuator failure compensation for nonlinear MIMO systems with an aircraft control application. Automatica, 2007, 43(11): 1869-1883 doi: 10.1016/j.automatica.2007.03.019
    [28] Li P, Yang G H. An adaptive fuzzy design for fault-tolerant control of MIMO nonlinear uncertain systems. Journal of Control Theory and Applications, 2011, 9(2): 244-50 doi: 10.1007/s11768-011-8167-x
    [29] Xu Y Y, Tong S C, Li Y M. Adaptive fuzzy decentralised fault-tolerant control for nonlinear large-scale systems with actuator failures and unmodelled dynamics. International Journal of Systems Science, 2015, 46(12): 2195-2209 doi: 10.1080/00207721.2013.859328
    [30] Wang L X. Adaptive Fuzzy Systems and Control: Design and Stability Analysis. Englewood Cliffs, NJ: Prentice-Hall, 1994.
    [31] Krstic M, Kokotovic P V, Kanellakopoulos I. Nonlinear and Adaptive Control Design. New York: John Wiley & Sons, 1995.
    [32] Polycarpou M M. Stable adaptive neural control scheme for nonlinear systems. IEEE Transactions on Automatic Control, 1996, 41(3): 447-451 doi: 10.1109/9.486648
  • 加载中
图(3)
计量
  • 文章访问数:  2254
  • HTML全文浏览量:  176
  • PDF下载量:  803
  • 被引次数: 0
出版历程
  • 收稿日期:  2015-12-16
  • 录用日期:  2016-04-18
  • 刊出日期:  2017-03-20

目录

    /

    返回文章
    返回