• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >Adaptive Neural Control for a Class of Nonlinear Time-Varying Delay Systems With Unknown Hysteresis
【24h】

Adaptive Neural Control for a Class of Nonlinear Time-Varying Delay Systems With Unknown Hysteresis

机译：一类具有未知滞后的非线性时变时滞系统的自适应神经控制

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form. Compared with previous works on the hysteresis phenomenon, the direction of the modified Bouc–Wen hysteresis model investigated in the literature is unknown. To reduce the computation burden in adaptation mechanism, an optimized adaptation method is successfully applied to the control design. Based on the Lyapunov–Krasovskii method, two neural-network-based adaptive control algorithms are constructed to guarantee that all the system states and adaptive parameters remain bounded, and the tracking error converges to an adjustable neighborhood of the origin. In final, some numerical examples are provided to validate the effectiveness of the proposed control methods.
机译：针对具有严格反馈形式的时滞连续时间非线性系统，研究了未知方向滞后模型与自适应神经控制技术的融合。与先前的磁滞现象研究相比，文献中研究的改进的Bouc-Wen磁滞模型的方向尚不清楚。为了减轻自适应机构的计算负担，将一种优化的自适应方法成功地应用于控制设计中。基于Lyapunov–Krasovskii方法，构造了两种基于神经网络的自适应控制算法，以确保所有系统状态和自适应参数保持有界，并且跟踪误差收敛到原点的可调邻域。最后，提供了一些数值示例来验证所提出的控制方法的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号