Literature DB >> 28303789

Flatness-based control approach to drug infusion for cardiac function regulation.

Gerasimos Rigatos1, Nikolaos Zervos2, Alexey Melkikh3.   

Abstract

A new control method based on differential flatness theory is developed in this study, aiming at solving the problem of regulation of haemodynamic parameters. Actually control of the cardiac output (volume of blood pumped out by heart per unit of time) and of the arterial blood pressure is achieved through the administered infusion of cardiovascular drugs such as dopamine and sodium nitroprusside. Time delays between the control inputs and the system's outputs are taken into account. Using the principle of dynamic extension, which means that by considering certain control inputs and their derivatives as additional state variables, a state-space description for the heart's function is obtained. It is proven that the dynamic model of the heart is a differentially flat one. This enables its transformation into a linear canonical and decoupled form, for which the design of a stabilising feedback controller becomes possible. The proposed feedback controller is of proven stability and assures fast and accurate tracking of the reference setpoints by the outputs of the heart's dynamic model. Moreover, by using a Kalman filter-based disturbances' estimator, it becomes possible to estimate in real-time and compensate for the model uncertainty and external perturbation inputs that affect the heart's model.

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Year:  2017        PMID: 28303789      PMCID: PMC8687353          DOI: 10.1049/iet-syb.2016.0012

Source DB:  PubMed          Journal:  IET Syst Biol        ISSN: 1751-8849            Impact factor:   1.615


  7 in total

Review 1.  Automated regulation of hemodynamic variables.

Authors:  R R Rao; C C Palerm; B Aufderheide; B W Bequette
Journal:  IEEE Eng Med Biol Mag       Date:  2001 Jan-Feb

2.  Experimental studies on multiple-model predictive control for automated regulation of hemodynamic variables.

Authors:  Ramesh R Rao; Brian Aufderheide; B Wayne Bequette
Journal:  IEEE Trans Biomed Eng       Date:  2003-03       Impact factor: 4.538

3.  Reduction of interference in oscillometric arterial blood pressure measurement using fuzzy logic.

Authors:  Chin-Teng Lin; Shing-Hong Liu; Jia-Jung Wang; Zu-Chi Wen
Journal:  IEEE Trans Biomed Eng       Date:  2003-04       Impact factor: 4.538

4.  ADRC or adaptive controller--A simulation study on artificial blood pump.

Authors:  Yi Wu; Qing Zheng
Journal:  Comput Biol Med       Date:  2015-09-10       Impact factor: 4.589

5.  A model-based approach to stability analysis of autonomic-cardiac regulation.

Authors:  Pedram Ataee; Jin-Oh Hahn; Guy A Dumont; Hossein A Noubari; W Thomas Boyce
Journal:  Comput Biol Med       Date:  2015-03-27       Impact factor: 4.589

6.  Automatic regulation of hemodynamic variables in acute heart failure by a multiple adaptive predictive controller based on neural networks.

Authors:  Koji Kashihara
Journal:  Ann Biomed Eng       Date:  2006-10-18       Impact factor: 3.934

7.  Model reference adaptive scheme for multi-drug infusion for blood pressure control.

Authors:  S Enbiya; F Mahieddine; A Hossain
Journal:  J Integr Bioinform       Date:  2011-09-15
  7 in total
  2 in total

1.  Efficient prediction of drug-drug interaction using deep learning models.

Authors:  Prashant Kumar Shukla; Piyush Kumar Shukla; Poonam Sharma; Paresh Rawat; Jashwant Samar; Rahul Moriwal; Manjit Kaur
Journal:  IET Syst Biol       Date:  2020-08       Impact factor: 1.615

2.  Model predictive control optimisation using the metaheuristic optimisation for blood pressure control.

Authors:  Mohammad Reza Ahmadpour; Hamid Ghadiri; Saeed Reza Hajian
Journal:  IET Syst Biol       Date:  2021-02-14       Impact factor: 1.615

  2 in total

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