基于反推方法的一类自适应神经网络容错控制

朱子杰, 黄向华

朱子杰, 黄向华. 基于反推方法的一类自适应神经网络容错控制[J]. 信息与控制, 2010, 39(5): 531-535.
引用本文: 朱子杰, 黄向华. 基于反推方法的一类自适应神经网络容错控制[J]. 信息与控制, 2010, 39(5): 531-535.
ZHU Zijie, HUANG Xianghua. An Adaptive Neural Network Fault-Tolerant Control Using Backstepping[J]. INFORMATION AND CONTROL, 2010, 39(5): 531-535.
Citation: ZHU Zijie, HUANG Xianghua. An Adaptive Neural Network Fault-Tolerant Control Using Backstepping[J]. INFORMATION AND CONTROL, 2010, 39(5): 531-535.

基于反推方法的一类自适应神经网络容错控制

基金项目: 航空科学基金资助项目(2009ZB52024)
详细信息
    作者简介:

    朱子杰(1986-),男,硕士生.研究领域为故障诊断与容错控制.
    黄向华(1972-),女,博士,教授,博士生导师.研究领域为控制系统建模,故障诊断与容错控制.

    通讯作者:

    朱子杰, zhuzijie256@163.com

  • 中图分类号: TP18

An Adaptive Neural Network Fault-Tolerant Control Using Backstepping

  • 摘要: 针对一类可控标准型基础上添加非线性模型误差与故障项的MIMO非线性系统,结合反推技术,提出了神经网络自适应控制方案,对模型误差与故障项进行在线估计.文中鲁棒项用于补偿逼近模型误差,当检测出系统故障时,通过调整各步骤的虚拟控制量来补偿故障项,消除故障项对系统的影响.通过理论证明实现了提出的控制方法使得各残差信号一致有界,并最终收敛到一个小的邻域内.实例仿真表明该方案的可行性.
    Abstract: Aiming at a class of control canonical form MIMO(multi-input multi-output) nonlinear systems which add nonlinear error and fault form,an adaptive control scheme combining backstepping technology for neural network is proposed. The method is used to estimate the model error and fault form on-line.In this paper,the robust term is utilized to compensate approximation model error.When the fault term is detected,the virtual control value is used to compensate the fault form by adjusting every step.The fault term effects on system is eliminated.By theoretical proof,every residual error signal is uniformly bounded,and finally converges to an arbitrarily small neighborhood around zero.Simulation results show the feasibility of the presented approach.
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出版历程
  • 收稿日期:  2009-09-10
  • 发布日期:  2010-10-19

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