Oscillations-free PID control of anesthetic drug delivery in neuromuscular blockade

Medvedev, Alexander; Zhusubaliyev, Zhanybai T.; Rosen, Olov; Silva, Margarida Martins da

doi:10.1016/j.cmpb.2016.07.025

Cited by 16 publications

(14 citation statements)

References 16 publications

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“…PFs in sequential Monte Carlo method obtain weighted samples from the non-Gaussian posterior probability of the state in nonlinear systems 148 . Study shows that a PF with an orthogonal basis (used for approximating the posterior by an orthogonal series expansion) outperformed Extended KF when estimating parameters of a Wiener anesthesia delivery model 146 . The process of parameter estimation is shown in Fig.…”

Section: Parameter Estimation In Dynamic Modelsmentioning

confidence: 99%

Computational Systems Biology in Disease Modeling and Control, Review and Perspectives

Yue¹,

Dutta²

2022

Preprint

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Omics-based approaches have become increasingly influential in identifying disease mechanismsand drug responses. Considering that diseases and drug responses are co-expressed andregulated in the relevant omics data interactions, the traditional way of grabbing omics datafrom single isolated layers cannot always obtain valuable inference. Also, drugs have adverseeffects that may impair patients, and launching new medicines for diseases is costly. To resolvethe above difficulties, systems biology is applied to predict potential molecular interactions byintegrating omics data from genomic, proteomic, transcriptional, and metabolic layers. Combinedwith known drug reactions, the resulting models improve medicines’ therapeutical performanceby re-purposing the existing drugs and combining drug molecules without off-target effects.Based on the identified computational models, drug administration control laws are designedto balance toxicity and efficacy. This review introduces biomedical applications and analysesof interactions among gene, protein and drug molecules for modeling disease mechanisms anddrug responses. The therapeutical performance can be improved by combining the predictiveand computational models with drug administration designed by control laws. The challengesare also discussed for its clinical uses in this work.

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Section: Parameter Estimation In Dynamic Modelsmentioning

confidence: 99%

Computational Systems Biology in Disease Modeling and Control, Review and Perspectives

Yue¹,

Dutta²

2022

Preprint

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“…Recently, an auto-tuning algorithm for PID based on system specifications (e.g., response to a given input) has been proposed that almost met equivalent specifications compared to the design based on knowledge of the full process 122 . To achieve an adequate paralysis level during surgery, a time-varying PID controller paired with a tuning procedure assists the closed-loop drug infusion system recover from sustained oscillations in an autonomous way 112 . The instability of equilibrium caused by dynamic alternations in the PID model was addressed by a stable limit cycle, and bifurcation analysis has been performed on the nonlinear dynamics of the designed control scheme to prevent the oscillation at the unstable equilibrium points caused by plant uncertainty.…”

Section: Parameter Estimation In Dynamic Modelsmentioning

confidence: 99%

“…Based on KF, its expanded versions have been utilized to deal with nonlinear models in biology. For example, the Extended KF, which is the nonlinear version of KF, can be used to estimate states and parameters in a nonlinear system 111,112 . Note that the noise uncertainty of KF is subject to Gaussian distribution.…”

Section: Parameter Estimation In Dynamic Modelsmentioning

confidence: 99%

“…As a sequential Monte Carlo method, PFs obtain weighted samples from the non-Gaussian posterior probability of the state to deal with nonlinear systems 114 . It has been studied that a PF with an orthogonal basis (that was used to approximate the posterior by an orthogonal series expansion) outperformed Extended KF when estimating the Wiener model parameters in an anesthesia delivery model 112 . The process of parameter estimation is shown in Fig.…”

Section: Parameter Estimation In Dynamic Modelsmentioning

confidence: 99%

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Systems biology in disease modeling and control, analysis and perspectives

Yue¹,

Dutta²

2021

Preprint

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Omics and drug molecules become increasingly influential in identifying disease mechanisms and drug response. Because diseases and drug responses are co-expressed and regulated in the relevant omics interactions, the traditional way that grabbing molecular data from single isolated layers cannot always obtain valuable inference. Also, adverse effects exist in drugs that impair patients, and launching new medicines for diseases is costly. To resolve the above difficulties, systems biology is then applied to predict potential molecular interaction elements by integrating omics data from genomic, proteomic, transcriptional, and metabolic layers. Combined with known drug reactions, the resulting models improve medicines’ therapeutical performance by re-purposing the existing drugs and combining drug molecules without off-target effects. Based on the identified computational models, drug administration control laws are designed to balance toxicity and efficacy. This review introduces biomedical applications and analyses of interactions among omics and drug molecules for modeling disease mechanism and drug response. The therapeutical performance can be improved by combining the predictive and computational models with drug administration designed by control laws. The challenges are discussed for its clinic uses.

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“…Applying bifurcation analysis to design of nonlinear control is not a novel idea but more accepted and utilized in certain specific areas of engineering that are challenged with nonlinear dynamical phenomena. Flight control [18], chemical reactor control [19], and closed-loop control of drug delivery [20] are just few examples of nonlinear control applications, where bifurcation analysis and continuation techniques serve design purposes well. However, analysis of nonlinear dynamics becomes computationally heavy in higher dimensions which fact limits the number of controller/observer design degrees of freedom.…”

Section: Introductionmentioning

confidence: 99%

Bifurcation analysis for non-local design of a hybrid observer for the impulsive Goodwin’s oscillator

2020

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The impulsive Goodwin's oscillator is a mathematical model capturing the dynamics arising in a closed-loop system, where a third-order linear time-invariant plant is subject to an intrinsic pulsemodulated feedback. Originally, the model was motivated by pulsatile regulation in endocrine systems but also has other potential applications. The asymptotic estimation of the hybrid state of the impulsive Goodwin's oscillator is considered in this paper. A hybrid observer makes use of the continuous plant output to correct the estimates of the state vector through two output error feedbacks: a continuous and a discrete one. When the hybrid state estimation error is zero, the observer is in a synchronous mode characterized by the firings of the impulses in the observer feedback and those of the plant occurring simultaneously. The synchronous mode thus corresponds to an equilibrium point of the hybrid state error dynamics. To guarantee asymptotic convergence of the observer to the synchronous mode, the basin of attraction of the equilibrium has to include all feasible initial deviations of the state estimates. To guarantee the above properties, a numerical observer design approach based on bifurcation analysis of a discrete map capturing the observer state transitions from one impulse firing to another is proposed and its efficacy is demonstrated in simulation.

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Oscillations-free PID control of anesthetic drug delivery in neuromuscular blockade

Cited by 16 publications

References 16 publications

Computational Systems Biology in Disease Modeling and Control, Review and Perspectives

Computational Systems Biology in Disease Modeling and Control, Review and Perspectives

Systems biology in disease modeling and control, analysis and perspectives

Bifurcation analysis for non-local design of a hybrid observer for the impulsive Goodwin’s oscillator

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