Finite-time guaranteed cost control for uncertain mean-field stochastic systems

被引：19
|
作者：
Liu, Xikui [1 ]
Liu, Qiming [1 ]
Li, Yan [2 ]
机构：
[1] Shandong Univ Sci & Technol, Coll Math & Syst Sci, Qingdao 266590, Peoples R China
[2] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao 266590, Peoples R China
来源：
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2020年 / 357卷 / 05期
基金：
中国国家自然科学基金;
关键词：
MARKOVIAN JUMP SYSTEMS; NEURAL-NETWORKS; STABILIZATION; STABILITY;
D O I：
10.1016/j.jfranklin.2019.12.012
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper deals with the finite-time guaranteed cost control problem for uncertain mean-field stochastic systems. Some sufficient conditions for the existence of state and output feedback finite-time guaranteed cost laws are given using finite-time stability theory. A guaranteed cost control gain is obtained through a convex optimization problem. The effectiveness of the proposed results is illustrated by a numerical example. (c) 2019 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：2813 / 2829
页数：17
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