Design of a switched robust control scheme for drug delivery in blood pressure regulation

Ahmed, Saeed; Özbay, Hitay

doi:10.1016/j.ifacol.2016.07.538

Cited by 13 publications

(6 citation statements)

References 17 publications

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“…The novelty of the solution presented in this paper is the design of the robust discrete time feedback control system, which can ensure that the drug concentration follows the desired steady state despite the uncertain parameters of the system. Such applications of system-based approaches to solve problems related to drug kinetics can be found in [2,3]. Additionally, other relevant results have been presented in our recent work [4,5].…”

Section: Introductionmentioning

confidence: 84%

Robust Control of Repeated Drug Administration with Variable Doses Based on Uncertain Mathematical Model

et al. 2023

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The aim of this paper was to design a repeated drug administration strategy to reach and maintain the requested drug concentration in the body. Conservative designs require an exact knowledge of pharmacokinetic parameters, which is considered an unrealistic demand. The problem is usually resolved using the trial-and-error open-loop approach; yet, this can be considered insufficient due to the parametric uncertainties as the dosing strategy may induce an undesired behavior of the drug concentrations. Therefore, the presented approach is rather based on the paradigms of system and control theory. An algorithm was designed that computes the required doses to be administered based on the blood samples. Since repeated drug dosing is essentially a discrete time process, the entire design considers the discrete time domain. We have also presented the idea of applying this methodology for the stabilization of an unstable model, for instance, a model of tumor growth. The simulation experiments demonstrated that all variants of the proposed control algorithm can reach and maintain the desired drug concentration robustly, i.e., despite the presence of parametric uncertainties, in a way that is superior to that of the traditional open-loop approach. It was shown that the closed-loop control with the integral controller and stabilizing state feedback is robust against large parametric uncertainties.

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Section: Introductionmentioning

confidence: 84%

Robust Control of Repeated Drug Administration with Variable Doses Based on Uncertain Mathematical Model

et al. 2023

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“…Automated and computer-aided drug administration via feedback control strategies has been investigated to overcome the challenges of manual drug delivery and operator monitoring. Various feedback control paradigms have been used for the automated closed-loop blood pressure regulation in emergency care (Malagutti et al, 2013;Ahmed and Özbay, 2016;Sandu and Popescu, 2016;Tasoujian et al, 2019b;Urooj and Singh, 2019). In the present work we consider an LPV time-delay model to represent the MAP response to PHP drug infusion dynamics, as a benchmark example to evaluate the proposed delaydependent LPV control design method for MAP regulation.…”

Section: Introductionmentioning

confidence: 99%

An Improved Integral Inequality for Delay-Dependent Gain-Scheduled LPV Control

Tasoujian

Grigoriadis

Franchek

2021

Front. Control Eng.

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The present work examines the delay-dependent gain-scheduling feedback control with guaranteed closed-loop stability and induced L2 norm performance for continuous-time linear parameter-varying (LPV) systems with arbitrary time-varying delay. An extension of Lyapunov stability utilizing Krasovskii functionals is considered to derive stability analysis and synthesis conditions for delay-dependent dynamic output feedback LPV control design. The main challenges associated with this approach are selecting appropriate Lyapunov-Krasovskii functionals (LKFs) and finding efficient integral inequalities to bound the derivative of the LKF. Accordingly, a novel modified parameter-dependent LKF candidate along with an affine version of Jensen’s inequality bounding technique are employed leading to the derivation of less conservative sufficient conditions expressed in terms of convex linear matrix inequalities (LMIs). The proposed methodology is compared with past work in the literature in terms of conservatism reduction and performance improvement through a numerical example. Finally, the application of the proposed output-feedback LPV control design is evaluated on the automated mean arterial blood pressure (MAP) regulation in critical patient resuscitation via vasoactive drug infusion. Closed-loop simulation results are presented to illustrate the potential of the introduced LPV gain-scheduling design to provide MAP set-point tracking in the presence of disturbances and varying input delays.

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“…Accordingly, the automation of the vasoactive drug infusion via feedback control has been proposed as a potential remedy to tackle the mentioned challenges of manual drug administration [5]. To address the automated MAP regulation problem, several approaches including fractional‐order proportional–integral (PI) and PI–derivative (PID) controls [6, 7], non‐linear PID digital control [8], adaptive predictive control [9, 10], robust multiple‐model adaptive control [11], switching robust control [12], reinforcement learning [13], and more recently PID and loop‐shaping control methods [14] have been considered.…”

Section: Introductionmentioning

confidence: 99%

Robust delay‐dependent LPV synthesis for blood pressure control with real‐time Bayesian parameter estimation

Tasoujian

Salavati

Franchek

et al. 2020

IET Control Theory & Appl

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Mean arterial blood pressure (MAP) dynamics estimation and its automated regulation could benefit the clinical and emergency resuscitation of critical patients. In order to address the variability and complexity of the MAP response of a patient to vasoactive drug infusion, a parameter-varying model with a varying time delay is considered to describe the MAP dynamics in response to drugs. The estimation of the varying parameters and the delay is performed via a Bayesian-based multiple-model square root cubature Kalman filtering approach. The estimation results validate the effectiveness of the proposed random-walk dynamics identification method using collected animal experiment data. Following the estimation algorithm, an automated drug delivery scheme to regulate the MAP response of the patient is carried out via time-delay linear parameter-varying (LPV) control techniques. In this regard, an LPV gain-scheduled output-feedback controller is designed to meet the MAP response requirements of tracking a desired reference MAP target and guarantee robustness against norm-bounded uncertainties and disturbances. In this context, parameter-dependent Lyapunov-Krasovskii functionals are used to derive sufficient conditions for the robust stabilization of a general LPV system with an arbitrarily varying time delay and the results are provided in a convex linear matrix inequality (LMI) constraint framework. Finally, to evaluate the performance of the proposed MAP regulation approach, closed-loop simulations are conducted and the results confirm the effectiveness of the proposed control method against various simulated clinical scenarios.

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Design of a switched robust control scheme for drug delivery in blood pressure regulation

Cited by 13 publications

References 17 publications

Robust Control of Repeated Drug Administration with Variable Doses Based on Uncertain Mathematical Model

Robust Control of Repeated Drug Administration with Variable Doses Based on Uncertain Mathematical Model

An Improved Integral Inequality for Delay-Dependent Gain-Scheduled LPV Control

Robust delay‐dependent LPV synthesis for blood pressure control with real‐time Bayesian parameter estimation

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