有界函数
控制理论(社会学)
非线性系统
计算机科学
模型预测控制
数学
控制(管理)
数学分析
物理
人工智能
量子力学
作者
Mengzhi Wang,Peng Cheng,Zhenyong Zhang,Mufeng Wang,Jiming Chen
标识
DOI:10.1109/tac.2023.3282066
摘要
This article is concerned with periodic event-triggering laws in robust model predictive control (MPC) for continuous-time constrained nonlinear systems. The online optimal control problem solved at triggering times is introduced. A periodic static event-triggering condition, in which a fixed sampling time interval plays an important role in avoiding Zeno behavior, is presented to alleviate continuous checking of event detections. Then, a periodic dynamic event-triggering condition is investigated to further enlarge the minimal interexecution time. Single-mode MPC with a prediction horizon larger than the control one is considered. Sufficient conditions of recursive feasibility for the online optimal control problem are derived. In order to relax the sufficient condition of stability, ultimately boundedness properties are utilized in stability analysis. Finally, numerical simulation is provided to demonstrate the effectiveness of the proposed methods.
科研通智能强力驱动
Strongly Powered by AbleSci AI