.png){kind=icon}
返回
Constrained Event-Triggered H∞ Control Based on Adaptive Dynamic Programming With Concurrent Learning
.png){kind=icon}
PRE
AI
DOI：10.1109/TSMC.2020.2997559.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this article, an event-triggered H-infinity control method is proposed based on adaptive dynamic programming (ADP) with concurrent learning for unknown continuous-time nonlinear systems with control constraints. First, a system identification technique based on neural networks (NNs) is adopted to identify completely unknown systems. Second, a critic NN is employed to approximate the value function. A novel weight updating rule is developed based on the event-triggered control law and time-triggered disturbance law, which reduces controller execution times and guarantees the stability of the system. Subsequently, concurrent learning is applied to the weight updating rule to relax the demand for the traditional persistence of excitation condition that is difficult to implement online. Finally, the comparison between the time-triggered method and event-triggered method in simulation demonstrates the effectiveness of the developed constrained event-triggered ADP method.
Keyword:
Adaptive dynamic programming (ADP)
concurrent learning
event-triggering mechanism
H-infinity control
input constraints
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
10.5
论文数:
1.1W
被引数:
5.0W
机构
引用论文
Ac-Electrogravimetry Study of Electroactive Thin Films. II. Application to Polypyrrole电活性薄膜的交流电重分析研究。二。聚吡咯的应用
PREAI
分享收藏Event-Triggered Decentralized Tracking Control of Modular Reconfigurable Robots Through Adaptive Dynamic Programming基于自适应动态规划的模块化可重构机器人事件触发分散跟踪控制
OAAI
OAAI分享收藏Integral reinforcement learning and experience replay for adaptive optimal control of partially-unknown constrained-input continuous-time systems.png)
AUTOMATICA
AUTOMATICAIF5.9
PREAI
分享收藏Reinforcement Learning and Adaptive Dynamic Programming for Feedback Control用于反馈控制的强化学习和自适应动态规划
PREAI
分享收藏Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints基于强化学习的具有输入约束的连续时间不确定非线性系统的鲁棒控制器设计
PREAI
分享收藏H∞ Tracking Control of Completely Unknown Continuous-Time Systems via Off-Policy Reinforcement Learning基于非策略强化学习的完全未知连续时间系统的h ∞ 跟踪控制
PREAI
分享收藏Market integration and price transmission in wheat markets of India: a transaction cost approach
PREAI
分享收藏
查看更多内容