Modeling of Cerebral Blood Flow Autoregulation Using Mathematical Control Theory

Alexey Golubev, Andrey Kovtanyuk, Renée Lampe

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

A mathematical model of cerebral blood flow in the form of a dynamical system is studied. The cerebral blood flow autoregulation modeling problem is treated as a nonlinear control problem and the potential and applicability of the nonlinear control theory techniques are analyzed in this respect. It is shown that the cerebral hemodynamics model in question is differentially flat. Then, the integrator backstepping approach combined with barrier Lyapunov functions is applied to construct the control laws that recover the cerebral autoregulation performance of a healthy human. Simulation results confirm the good performance and flexibility of the suggested cerebral blood flow autoregulation design. The conducted research should enrich our understanding of the mathematics behind the cerebral blood flow autoregulation mechanisms and medical treatments to compensate for impaired cerebral autoregulation, e.g., in preterm infants.

Original languageEnglish
Article number2060
JournalMathematics
Volume10
Issue number12
DOIs
StatePublished - 1 Jun 2022

Keywords

  • biomechanical system
  • cerebral autoregulation
  • differential flatness
  • integrator backstepping
  • intracranial hemodynamics
  • nonlinear control
  • nonlinear dynamics
  • output tracking

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