引用本文:王敏,胡锐,辛学刚,时昊天.严格反馈系统的事件触发学习控制[J].控制理论与应用,2021,38(10):1577~1586.[点击复制]
Wang Min,HU Rui,XIN Xue-gang,SHI Hao-tian.Event-triggered learning control for strict-feedback systems[J].Control Theory and Technology,2021,38(10):1577~1586.[点击复制]
严格反馈系统的事件触发学习控制
Event-triggered learning control for strict-feedback systems
摘要点击 1409  全文点击 501  投稿时间:2020-10-20  修订日期:2021-09-17
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DOI编号  10.7641/CTA.2021.00730
  2021,38(10):1577-1586
中文关键词  确定学习  事件触发机制  自适应控制  神经网络  严格反馈系统  网络控制系统
英文关键词  deterministic learning  event-triggered mechanism  adaptive control  neural networks  strict-feedback systems  network control system
基金项目  国家自然科学基金项目(61773169, 61973129), 广东省自然科学基金项目(2019B151502058), 广东省重点领域研发计划项目(2020B1111010002), 广东海洋经济发展专项(粤自然资合[2020]018号), 广州市科技计划项目(201904010295)资助.
作者单位E-mail
王敏* 华南理工大学 auwangmin@scut.edu.cn 
胡锐 华南理工大学  
辛学刚 华南理工大学  
时昊天 华南理工大学  
中文摘要
      本文针对一类严格反馈非线性系统, 提出了基于确定学习的事件触发控制方案. 首先, 在本地控制测试端 设计自适应神经网络控制, 并在控制过程中实现系统未知动态的知识获取和存储. 随后, 基于常值权值, 设计了新颖 的事件触发控制器和事件触发条件. 结合李雅普诺夫稳定性分析和非线性脉冲动态系统原理, 验证了所提方案能够 保证跟踪误差收敛到零的小邻域内以及所有闭环信号是最终一致有界的. 此外, 本文所提方案采用常值权值代替了 估计权值, 使得所提方案易于实现, 暂态性能好和网络资源占用少. 最后, 通过对比仿真结果证明了所提方案的有效 性.
英文摘要
      This paper proposes a novel event-triggered tracking control scheme for a class of strict-feedback nonlinear systems based on deterministic learning. Firstly, this paper designs an adaptive neural network control for strict-feedback systems on the local control test side and realizes the knowledge acquirement of unknown dynamics in the control process. Then, based on stored constant weights, this paper designs a novel event-triggered controller and a triggering condition. By combining Lyapunov stability analysis with nonlinear impulse dynamic system theory, the proposed control scheme can be verified to guarantee that the tracking error converges to a small neighborhood of zero and all the signals in the closedloop system are uniformly ultimately bounded. Moreover, the proposed control scheme uses constant weights instead of estimated weights, which makes the proposed scheme possess some good features including the easy-to-implement triggered condition, the improved transient control performance, and the less network resource occupancy. A comparative simulation is given to illustrate the effectiveness of the proposed scheme.