2.765

2022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

基于非线性映射的约束系统自适应反推控制

郭涛 王丁磊 王爱民

郭涛, 王丁磊, 王爱民. 基于非线性映射的约束系统自适应反推控制. 自动化学报, 2013, 39(9): 1558-1563. doi: 10.3724/SP.J.1004.2013.01558
引用本文: 郭涛, 王丁磊, 王爱民. 基于非线性映射的约束系统自适应反推控制. 自动化学报, 2013, 39(9): 1558-1563. doi: 10.3724/SP.J.1004.2013.01558
GUO Tao, WANG Ding-Lei, WANG Ai-Min. Adaptive Backstepping Control for Constrained Systems Using Nonlinear Mapping. ACTA AUTOMATICA SINICA, 2013, 39(9): 1558-1563. doi: 10.3724/SP.J.1004.2013.01558
Citation: GUO Tao, WANG Ding-Lei, WANG Ai-Min. Adaptive Backstepping Control for Constrained Systems Using Nonlinear Mapping. ACTA AUTOMATICA SINICA, 2013, 39(9): 1558-1563. doi: 10.3724/SP.J.1004.2013.01558

基于非线性映射的约束系统自适应反推控制

doi: 10.3724/SP.J.1004.2013.01558
基金项目: 

河南省科技攻关项目(112102210126); 河南省自然科学基金(2011B120001)资助

详细信息
    作者简介:

    郭涛 安阳师范学院计算机与信息工程学院副教授.2009年在西安电子科技大学计算机应用技术专业获博士学位.主要研究方向为反推控制, 自适应模糊控制, 非线性控制.E-mail: gtmailbox@126.com

Adaptive Backstepping Control for Constrained Systems Using Nonlinear Mapping

Funds: 

Supported by Key Scientific and Technological Research of Henan Province (112102210126) and Natural Science Foundation of Henan Province (2011B120001)

  • 摘要: 针对基于障碍Lyapunov函数的非线性约束系统反推控制中, 控制器结构复杂、约束量初值选取区间小、会引入额外参数等问题, 提出了一种新的基于非线性映射的自适应反推控制方案. 该方法扩大约束量的初值选取区间为整个约束区间, 增加了系统初值选取和控制器设计的便易性. 约束量被映射至实数空间中, 因此映射后的新系统可以直接应用反推法设计控制器, 简化了控制器结构且不会引入额外参数. 证明了映射前后系统具有一致的收敛性, 保证闭环系统所有信号一致有界, 并且跟踪误差渐近收敛于零. 仿真结果进一步验证了本文方法的有效性.
  • [1] Blanchini F. Set invariance in control. Automatica, 1999, 35(11): 1747-1767
    [2] Mayne D Q, Rawlings J B, Rao C V, Scokaert P O M. Constrained model predictive control: stability and optimality. Automatica, 2000, 36(6): 789-814
    [3] Bemporad A. Reference governor for constrained nonlinear systems. IEEE Transactions on Automatic Control, 1998, 43(3): 415-419
    [4] Kogiso K, Hirata K. Reference governor for constrained systems with time-varying references. Robotics and Autonomous Systems, 2009, 57(3): 289-295
    [5] Dehaan D, Guay M. Extremum-seeking control of state-constrained nonlinear systems. Automatica, 2005, 41(9): 1567-1574
    [6] Adetola V, Guay M. Parameter convergence in adaptive extremum-seeking control. Automatica, 2007, 43(1): 105-110
    [7] Kanellakopoulos I, Kokotovic P V, Morse A S. Systematic design of adaptive controllers for feedback linearizable systems. IEEE Transactions on Automatic Control, 1991, 36(11): 1241-1253
    [8] Krstic M, KanellaKopulos I, Kokotovic P V. Nonlinear and Adaptive Control Design. New York: Wiley, 1995
    [9] Ge S S, Hong F, Lee T H. Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients. IEEE Transactions on System, Man, and Cybernetics, Part B: Cybernetics, 2004, 34(1): 499-516
    [10] 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
    [11] Deng H, Krstić M. Stochastic nonlinear stabilization —— I: a backstepping design. Systems and Control Letters, 1997, 32(3): 143-150
    [12] Jain S, Khorrami F. Decentralized adaptive control of a class of large-scale interconnected nonlinear systems. IEEE Transactions on Automatic Control, 1997, 42(2): 136-154
    [13] Chen W S, Li J M. Decentralized output-feedback neural control for systems with unknown interconnections. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2008, 38(1): 258-266
    [14] Liu Y J, Wang W. Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems. Information Sciences, 2007, 177(18): 3901-3917
    [15] Ngo K B, Mahony R, Jiang Z P. Integrator backstepping using barrier functions for systems with multiple state constraints. In: Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference. Seville, Spain: IEEE, 2005. 8306-8312
    [16] Tee K P, Ge S S, Tay E H. Barrier Lyapunov functions for the control of output-constrained nonlinear systems. Automatica, 2009, 45(4): 918-927
    [17] Ren B, Ge S S, Tee K P, Lee T H. Adaptive control for parametric output feedback systems with output constraint. In: Proceedings of the Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference. Shanghai, China: IEEE, 2009. 6650-6655
    [18] Ren B B, Ge S S, Tee K P, Lee T H. Adaptive neural control for output feedback nonlinear systems using a barrier Lyapunov function. IEEE Transactions on Neural Networks, 2010, 21(8): 1339-1345
    [19] Sun W, Yeow J T W, Sun Z. Robust adaptive control of a one degree of freedom electrostatic microelectromechanical systems model with output-error-constrained tracking. IET Control Theory and Applications, 2012, 6(1): 111-119
    [20] Tee K P, Ge S S. Control of nonlinear systems with full state constraint using a barrier Lyapunov function. In: Proceedings of the Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference. Shanghai, China: IEEE, 2009. 8618-8623
    [21] Tee K P, Ge S S, Li H Z, Ren B B. Control of nonlinear systems with time-varying output constraints. In: Proceedings of the 2009 IEEE International Conference on Control and Automation. Christchurch, New Zealand: IEEE, 2009. 524-529
    [22] Tee K P, Ren B B, Ge S S. Control of nonlinear systems with time-varying output constraints. Automatica, 2011, 47(11): 2511-2516
    [23] Tee K P, Ge S S, Tay F E H. Adaptive control of electrostatic microactuators with bidirectional drive. IEEE Transactions on Control Systems Technology, 2009, 17(2): 340-352
    [24] Tee K P, Yan R, Li H Z. Adaptive admittance control of a robot manipulator under task space constraint. In: Proceedings of the 2010 IEEE International Conference on Robotics and Automation. Anchorage, Alaska: IEEE, 2010. 5181-5186
    [25] Yan F J, Wang J M. Fuel-assisted in-cylinder oxygen fraction transient trajectory shaping control for diesel engine combustion mode switching. In: Proceedings of the 2011 American Control Conference. San Francisco, CA: IEEE, 2011. 1573-1578
    [26] Do K D, Nguyen D H, Nguyen T B. Nonlinear control of magnetic bearing. Journal of Measurement Science and Instrumentation, 2010, 1(1): 10-16
    [27] Ge S S, Lee T H, Harris C J. Adaptive Neural Network Control of Robotic Manipulators. London: World Scientific, 1998
    [28] Yang Y S, Feng G, Ren J S. A combined backstepping and small-gain approach to robust adaptive fuzzy control for strict-feedback nonlinear systems. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 2004, 34(3): 406-420
    [29] Chen B, Liu X P, Liu K F, Shi P, Lin C. Direct adaptive fuzzy control for nonlinear systems with time-varying delays. Information Sciences, 2010, 180(5): 776-792
    [30] Tong S C, Cheng N. Adaptive fuzzy observer backstepping control for a class of uncertain nonlinear systems with unknown time-delay. International Journal of Automation and Computing, 2010, 7(2): 236-246
  • 加载中
计量
  • 文章访问数:  1986
  • HTML全文浏览量:  65
  • PDF下载量:  1450
  • 被引次数: 0
出版历程
  • 收稿日期:  2012-03-23
  • 修回日期:  2012-07-05
  • 刊出日期:  2013-09-20

目录

    /

    返回文章
    返回