Networked generalized predictive control based on state-space model

被引:0
|
作者
Tang, Bin [1 ,2 ]
Zhang, Yun [1 ]
Liu, Guo-Ping [2 ,3 ]
Gui, Wei-Hua [2 ]
机构
[1] Faculty of Automation, Guangdong University of Technology, Guangzhou 510006, China
[2] School of Information Science and Engineering, Central South University, Changsha 410083, China
[3] Department of Engeneering, University of Glamorgan, Pontypridd CF37 1DL, United Kingdom
来源
Kongzhi yu Juece/Control and Decision | 2010年 / 25卷 / 04期
关键词
Controllers - Delay control systems - Networked control systems - State space methods - Model predictive control - Time delay - Timing circuits - Predictive control systems;
D O I
暂无
中图分类号
学科分类号
摘要
This paper concerns about state-space model based generalized predictive control for networked control systems with time-varying network-induced time delay and packet loss. A new method is proposed to compensate the influences of network-induced time delay and packet loss on control performance by minimal prediction horizon and predictive control vector, respectively. The controller design method is discussed with respect to three cases, which are related to packet loss, network-induced time delay and both of the two former, respectively. Simulation and experimental results show the effectiveness of the proposed method.
引用
收藏
页码:535 / 541
相关论文
共 50 条
  • [31] Comments on "Predictive Torque Control of Induction Machines Based on State-Space Models"
    Rojas, Christian A.
    Yuz, Juan I.
    Silva, Cesar A.
    Rodriguez, Jose
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2014, 61 (03) : 1635 - 1638
  • [32] GENERALIZED STATE-SPACE MODEL FOR THE INTERLEAVED BUCK CONVERTER
    Schittler, Andressa C.
    Pappis, Douglas
    Rech, Cassiano
    Campos, Alexandre
    Dalla Costa, Marco A.
    XI BRAZILIAN POWER ELECTRONICS CONFERENCE (COBEP 2011), 2011, : 451 - 457
  • [33] Computationally Efficient Nonlinear Predictive Control Based on State-Space Neural Models
    Lawrynczuk, Maciej
    PARALLEL PROCESSING AND APPLIED MATHEMATICS, PT I, 2010, 6067 : 350 - 359
  • [34] Direct State-Space Model for Model Predictive Control of Multi-Level Power Converters
    Jupin, Samuel
    Vechiu, Ionel
    Tapia, Gerardo
    IECON 2017 - 43RD ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2017, : 7759 - 7764
  • [35] A state-space thermal model incorporating humidity and thermal comfort for model predictive control in buildings
    Yang, Shiyu
    Wan, Man Pun
    Ng, Bing Feng
    Zhang, Tian
    Babu, Sushanth
    Zhang, Zhe
    Chen, Wanyu
    Dubey, Swapnil
    ENERGY AND BUILDINGS, 2018, 170 : 25 - 39
  • [36] Networked Predictive Control Based on a State Observer
    Ren Lili
    Liu Yun
    Yu Daqing
    Liang Yanlei
    2012 INTERNATIONAL CONFERENCE ON INDUSTRIAL CONTROL AND ELECTRONICS ENGINEERING (ICICEE), 2012, : 1532 - 1535
  • [37] Non-minimal state-space model-based continuous-time model predictive control with constraints
    Wang, Liuping
    Young, Peter C.
    Gawthrop, Peter J.
    Taylor, C. James
    INTERNATIONAL JOURNAL OF CONTROL, 2009, 82 (06) : 1122 - 1137
  • [38] MODEL PREDICTIVE CONTROL OF MULTIRATE SAMPLED-DATA SYSTEMS - A STATE-SPACE APPROACH
    LEE, JH
    GELORMINO, MS
    MORARI, M
    INTERNATIONAL JOURNAL OF CONTROL, 1992, 55 (01) : 153 - 191
  • [39] Variational Bayesian learning of nonlinear hidden state-space models for model predictive control
    Raiko, Tapani
    Tornio, Matti
    NEUROCOMPUTING, 2009, 72 (16-18) : 3704 - 3712
  • [40] Offset-free nonlinear Model Predictive Control with state-space process models
    Tatjewski, Piotr
    ARCHIVES OF CONTROL SCIENCES, 2017, 27 (04): : 595 - 615