Input-to-state stability for networked control system with predictive scheme

被引：7
|
作者：
Du, Sheng-Li [1 ]
Wang, Rui [2 ]
Shi, Peng [3 ,4 ]
Shi, Yan [5 ]
机构：
[1] Dalian Univ Technol, Sch Control Sci & Engn, Dalian 116024, Peoples R China
[2] Dalian Univ Technol, Sch Aeronaut & Astronaut, Dalian 116024, Peoples R China
[3] Harbin Engn Univ, Coll Automat, Harbin 150001, Heilongjiang, Peoples R China
[4] Victoria Univ, Coll Engn & Sci, Melbourne, Vic 8001, Australia
[5] Tokai Univ, Grad Sch Sci & Technol, Kumamoto 8628652, Japan
来源：
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2015年 / 352卷 / 10期
基金：
澳大利亚研究理事会; 美国国家科学基金会;
关键词：
LINEAR-SYSTEMS; FEEDBACK; DELAY; NONLINEARITIES; STABILIZATION; DESIGN;
D O I：
10.1016/j.jfranklin.2015.06.021
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 studies the input-to-state stability (ISS) problem for a class of networked control systems (NCSs). The improved varying controller gain predictive scheme is used to compensate the effects of network-induced delays and packet dropouts. By introducing a new auxiliary variable and analyzing the relationship of the network-induced delays and packet dropouts between two consecutive sampling instants, the considered networked control system (NCS) is converted into a coupled switched system. Based on the small gain theorem, a novel stability criterion is proposed to guarantee the ISS property of the considered system. Compared with existing works in literature, the stability criterion obtained here is easier to test and is much less conservative. A numerical simulation is presented to show the effectiveness of the proposed method. (C) 2015 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：4565 / 4578
页数：14
相关论文
共 50 条
  • [11] Input-to-state stability for networked control systems via an improved impulsive system approach
    Chen, Wu-Hua
    Zheng, Wei Xing
    AUTOMATICA, 2011, 47 (04) : 789 - 796
  • [12] Networked Predictive Control of Uncertain Constrained Nonlinear Systems: Recursive Feasibility and Input-to-State Stability Analysis
    Pin, Gilberto
    Parisini, Thomas
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2011, 56 (01) : 72 - 87
  • [13] Regional input-to-state stability for nonlinear model predictive control
    Magni, L.
    Raimondo, D. M.
    Scattolini, R.
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2006, 51 (09) : 1548 - 1553
  • [14] Input-Output Stability with Input-to-State Stable Protocols for Quantized and Networked Control Systems
    Tabbara, Mohammad
    Nesic, Dragan
    47TH IEEE CONFERENCE ON DECISION AND CONTROL, 2008 (CDC 2008), 2008, : 2680 - 2685
  • [15] Trajectory Bounds of Input-to-State Stability for Nonlinear Model Predictive Control
    Griffith, Devin W.
    Biegler, Lorenz T.
    IFAC PAPERSONLINE, 2015, 48 (08): : 1027 - 1032
  • [16] Input-to-State Stability: A Unifying Framework for Robust Model Predictive Control
    Limon, D.
    Alamo, T.
    Raimondo, D. M.
    Munoz de la Pena, D.
    Bravo, J. M.
    Ferramosca, A.
    Camacho, E. F.
    NONLINEAR MODEL PREDICTIVE CONTROL: TOWARDS NEW CHALLENGING APPLICATIONS, 2009, 384 : 1 - +
  • [17] On input-to-state stability of min-max nonlinear model predictive control
    Lazar, M.
    De la Pena, D. Munoz
    Heemels, W. P. M. H.
    Alamo, T.
    SYSTEMS & CONTROL LETTERS, 2008, 57 (01) : 39 - 48
  • [18] Neural Network-Based Model Predictive Control with Input-to-State Stability
    Seel, Katrine
    Grotli, Esten, I
    Moe, Signe
    Gravdahl, Jan T.
    Pettersen, Kristin Y.
    2021 AMERICAN CONTROL CONFERENCE (ACC), 2021, : 3556 - 3563
  • [19] Model predictive control of uncertain singular systems based on input-to-state stability
    Wei, Fangzheng
    Liu, Xiaohua
    2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 5316 - 5321
  • [20] Power characterizations of input-to-state stability and integral input-to-state stability
    Angeli, D
    Nesic, D
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2001, 46 (08) : 1298 - 1303
12345