...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Neurocomputing >Event-triggered adaptive fixed-time NN control for constrained nonstrict-feedback nonlinear systems with prescribed performance
【24h】

Event-triggered adaptive fixed-time NN control for constrained nonstrict-feedback nonlinear systems with prescribed performance

机译：具有规定性能的约束非触控反馈非线性系统的事件触发的自适应固定时间NN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

In this paper, an observer-based adaptive fixed-time control strategy is put forward for uncertain nonstrict-feedback nonlinear systems subject to prescribed performance, full-state constraints and event-triggered mechanism. The difficulty of control design is to use the state observer to estimate unmeasurable states for nonstrict-feedback form in the fixed-time convergence setting. Neural networks are implemented to model the unknown nonlinearities of system. Via introducing fixed-time theory and asymmetric barrier Lyapunov function (ABLF), the fixed-time control problem of the full-state contrained nonlinear system with prescribed performance is solved. Meanwhile, the problem of "explosion of com-plexity" caused by backstepping technique is averted by utilizing the dynamic surface control technique. Furthermore, an event-triggered controller is devised, which can significantly save communication resources. Moreover, it is concluded that all signals involved are bounded, full-state constraints are not transgressed, tracking error remains within a prescribed domain and Zeno phenomenon is completely circumvented. Finally, the effectiveness of the proposed algorithm is verified by some simulation results. (C) 2020 Elsevier B.V. All rights reserved.
机译：本文提出了一种基于观察者的自适应固定时间控制策略，提出了不确定的非将性能，全状态约束和事件触发机制的不确定非经用反馈非线性系统。控制设计的难度是使用状态观察者在定时收敛设置中估计非误判状态的不可分布状态。实现神经网络以模拟系统的未知非线性。通过引入定时理论和不对称障碍Lyapunov函数（ABLF），解决了规定性能的全态禁区非线性系统的固定时间控制问题。同时，通过利用动态表面控制技术来厌烦由反向技术引起的“COM-PLEXITY爆炸”的问题。此外，设计了一个事件触发的控制器，可以显着节省通信资源。此外，得出结论是，所涉及的所有信号都是有界的，全状态约束未违反，跟踪误差仍然在规定的域中，并且ZENO现象完全避免。最后，通过一些仿真结果验证了所提出的算法的有效性。 （c）2020 Elsevier B.v.保留所有权利。

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