控制理论(社会学)
模型预测控制
有界函数
估计员
离散时间和连续时间
线性系统
稳健性(进化)
国家(计算机科学)
鲁棒控制
计算机科学
集合(抽象数据类型)
控制(管理)
数学
控制系统
算法
工程类
人工智能
数学分析
电气工程
统计
基因
化学
程序设计语言
生物化学
作者
Siyuan Guo,Zhichen Li,Zhe Li,Huaicheng Yan,Hao Zhang
标识
DOI:10.1080/00207179.2023.2269266
摘要
In networked control systems, the communication load is a main concern for implementing model predictive control (MPC). This paper introduces a self-triggered MPC algorithm under network environments to reduce communication load, for discrete-time linear systems with bounded state and output disturbances, when only the system output can be measured at triggering instants. The proposed algorithm mainly based on a state estimator whose estimation error is bounded by an invariant set, and on the self-triggered model predictive control of a nominal system. Moreover, the new cost function explicitly adopts communication load is in consideration. The proposed algorithm is proved to drive the system to an invariant set with respect to the bounded disturbances. Finally, simulation results is provided to verify the effectiveness of the proposed robust output feedback MPC algorithm.
科研通智能强力驱动
Strongly Powered by AbleSci AI