Process Model and Implementation the Multivariable Model Predictive Control to Ventilation System

被引:3
|
作者
Hrbcek, Jozef [1 ]
Spalek, Juraj [1 ]
Simak, Vojtech [1 ]
机构
[1] Univ Zilina, Dept Control & Informat Syst, Fac Elect Engn, Zilina 01026, Slovakia
关键词
D O I
10.1109/SAMI.2010.5423738
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Predictive control seems to be a promising approach that can help to improve properties of existing ventilation systems applied in road tunnels. Advantages of predictive control result mainly from its ability to solve both SISO and MIMO tasks, to have regard for dynamics of process changes in a broad extent, to compensate effect of measurable and non-measurable failures and to formulate the task as an optimization control task" considering limiting conditions of control actions, changes of control actions and output variables. Data characterizing the existing ventilation system can be used to analyze and identify the system and create its models. Thereafter the predictive control of ventilation can be designed enabling to predict concentrations of pollutants and optimize system operation.
引用
收藏
页码:211 / 214
页数:4
相关论文
共 50 条
  • [1] Model predictive control for multivariable processes
    VanDoren, J
    [J]. CONTROL ENGINEERING, 1997, 44 (06) : 87 - 87
  • [2] IMPLEMENTATION OF A MULTIVARIABLE PREDICTIVE CONTROL SYSTEM IN A FIRED HEATER
    Gomez, Alejandra
    Correa, Rodrigo
    [J]. DYNA-COLOMBIA, 2009, 76 (157): : 195 - 203
  • [3] Neural model predictive controller for multivariable process
    Sivakumaran, N.
    Kirubakaran, V.
    Radhakrishnan, T. V.
    [J]. 2006 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS 1-6, 2006, : 1511 - +
  • [4] Laboratory Demonstration for Model Predictive Multivariable Control with a Coupled Drive System
    Su, Steven W.
    Nguyen, Hung T.
    Ha, Q. P.
    [J]. 11TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV 2010), 2010, : 762 - 767
  • [5] Automation of reformer process in petroleum plant using fuzzy supervisory model predictive multivariable control system
    Kobayashi, T
    Tani, T
    Miyamoto, S
    [J]. NINTH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2000), VOLS 1 AND 2, 2000, : 1021 - 1024
  • [7] Model Predictive Control of a Heating, Ventilation and Air Conditioning System
    Vasak, Mario
    Starcic, Antonio
    [J]. 2013 36TH INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO), 2013, : 913 - 918
  • [8] Model predictive and fuzzy control of a road tunnel ventilation system
    Bogdan, Stjepan
    Birgmajer, Bruno
    Kovacic, Zdenko
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2008, 16 (05) : 574 - 592
  • [9] Real-Time Implementation of Model Predictive Multivariable Tracking Control for Hydrostatic Transmissions
    Danh, Dang Ngoc
    Aschemann, Harald
    [J]. 2020 24TH INTERNATIONAL CONFERENCE ON SYSTEM THEORY, CONTROL AND COMPUTING (ICSTCC), 2020, : 343 - 348
  • [10] Time-delay Process Multivariable Model Predictive Function Control for Basis Weight & Moisture Content Control System
    Xiao Zhongjun
    Wang Mengxiao
    [J]. CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS, 2009, : 4089 - +