SIR Epidemic Control Using a 2DoF IMC-PID with Filter Control Strategy

被引:0
|
作者
Rivera, D. E. [1 ]
Banerjee, S. [1 ]
Kobs, C. [1 ]
El Mistiri, M. [1 ]
Shi, Z. [1 ]
机构
[1] Arizona State Univ, Sch Engn Matter Transport & Energy, Control Syst Engn Lab, Ira A Fulton Schools Engn, Tempe, AZ 85287 USA
来源
IFAC PAPERSONLINE | 2024年 / 58卷 / 07期
基金
美国国家科学基金会;
关键词
Process control applications; epidemic modeling and control; model-based PID; controller tuning;
D O I
10.1016/j.ifacol.2024.08.035
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The COVID-19 pandemic has given rise to many significant research activities, among these a resurgence of the use of control-oriented approaches for modeling and controlling epidemics. An examination of a SIR (Susceptible-Infectious-Recovered) dynamic model under endemic conditions using Internal Model Control (IMC) shows that a two-degree-of-freedom (2DoF) PID with filter structure is a natural solution for understanding how to manage a pandemic, with model-based IMC-PID tuning being extremely effective when evaluated on a first-principles, nonlinear plant model. Dynamic modeling (nonlinear and linearized), PID controller design, and closed-loop evaluation (under conditions that include vaccination and the loss of immunity/potential for re-infection) are presented, with the results demonstrating the deep insights that can be gained from simple models and control policies. Computational models as presented in this work could be used to inform the actions of governments and individuals.
引用
收藏
页码:204 / 209
页数:6
相关论文
共 50 条
  • [31] 2DOF control design for nanopositioning
    Lee C.
    Mohan G.
    Salapaka S.
    [J]. Lecture Notes in Control and Information Sciences, 2011, 413 : 67 - 82
  • [32] 2DOF motion stabilization of biped robot by gaze control strategy
    Takizawa, S
    Ushida, S
    Okatani, T
    Deguchi, K
    [J]. 2005 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-4, 2005, : 3809 - 3814
  • [33] Analytical design of fractional IMC filter - PID control strategy for performance enhancement of cascade control systems
    Ranganayakulu, Rayalla
    Seshagiri Rao, Ambati
    Uday Bhaskar Babu, Gara
    [J]. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2020, 51 (10) : 1699 - 1713
  • [34] Application of boiler superheated steam pressure control which based on IMC-PID
    Zhao Kun-long
    Wang Zai-ying
    [J]. 2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 586 - 589
  • [35] LQG Benchmark Based Performance Assessment of IMC-PID Temperature Control System
    Fang, Tao
    Zhang, Ridong
    Gao, Furong
    [J]. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2017, 56 (51) : 15102 - 15111
  • [36] The application of model PID or IMC-PID advanced process control to refinery algid petrochemical plants
    Zhen Xinping
    Li Quanshan
    Wei Huan
    Wang Wenxin
    Jin Qibing
    Pan Lideng
    [J]. PROCEEDINGS OF THE 26TH CHINESE CONTROL CONFERENCE, VOL 4, 2007, : 699 - +
  • [37] Neural Network IMC-PID Control of CPE Polymerization Temperature Based on DDE
    Qi, Shu-fen
    Zhou, Yi-lin
    Jiang, Hai-bo
    [J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, 2008, : 79 - 82
  • [38] Two-step IMC-PID method for multiloop control system design
    Cha, SY
    Chun, D
    Lee, J
    [J]. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2002, 41 (12) : 3037 - 3041
  • [39] Real-time IMC-PID Control and Monitoring of Essential Oil Extraction Process Using IoT
    Johari, Siti Nur Hasinah
    Rahiman, Mohd Hezri Fazalul
    Adnan, Ramli
    Tajjudin, Mazidah
    [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC CONTROL AND INTELLIGENT SYSTEMS (I2CACIS 2020), 2020, : 51 - 56
  • [40] Indirect iterative learning control design based on 2DOF IMC for batch processes with input delay
    Cui, Jiyao
    Wang, Zhihong
    Chen, Yueling
    Liu, Tao
    [J]. PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017), 2017, : 3587 - 3592