引用本文:余昭旭,杜红彬.时变时滞随机非线性系统的自适应神经网络跟踪控制[J].控制理论与应用,2011,28(12):1808~1812.[点击复制]
YU Zhao-xu,DU Hong-bin.Adaptive neural tracking control for stochastic nonlinear systems with time-varying delay[J].Control Theory and Technology,2011,28(12):1808~1812.[点击复制]
时变时滞随机非线性系统的自适应神经网络跟踪控制
Adaptive neural tracking control for stochastic nonlinear systems with time-varying delay
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DOI编号  10.7641/j.issn.1000-8152.2011.12.CCTA100606
  2011,28(12):1808-1812
中文关键词  自适应跟踪控制  神经网络(NNs)  Razumikhin引理  随机系统  时变时滞
英文关键词  adaptive tracking control  Neural Networks(NNs)  Razumikhin lemma  stochastic systems  time-varying delay
基金项目  国家自然科学基金青年基金资助项目(60704013); 华东理工大学优秀青年教师科研专项基金资助项目(YH0157134).
作者单位E-mail
余昭旭* 华东理工大学 自动化系 yyzx@ecust.edu.cn 
杜红彬 华东理工大学 自动化系  
中文摘要
      针对一类具有时变时滞的不确定随机非线性严格反馈系统的自适应跟踪问题, 利用Razumikhin引理和backstepping方法, 提出一种新的自适应神经网络跟踪控制器. 该控制器可保证闭环系统的所有误差变量皆四阶矩半全局一致最终有界, 并且跟踪误差可以稳定在原点附近的邻域内. 仿真例子表明所提出控制方案的有效性.
英文摘要
      This paper focuses on the adaptive neural control for a class of uncertain stochastic nonlinear strict-feedback systems with time-varying delay. Based on the Razumikhin function approach, a novel adaptive neural controller is developed by using the backstepping technique. The proposed adaptive controller guarantees that all the error variables are 4-moment semi-globally uniformly ultimately bounded in a compact set while the tracking error remains in a neighborhood of the origin. The effectiveness of the proposed design is validated by simulation results.