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Tracking Action Potentials of Nonlinear Excitable Cells Using Model Predictive Control

Authors:
Md. Ariful Islam
Abhishek Murthy
Tushar Deshpande
Ezio Bartocci
Scott D. Stoller
Scott A. Smolka
Radu Grosu

Keywords: Biocomputing; Model Predictive Control; Excitable Cells

Abstract:
We present explicit and online Model Predictive Controllers (MPCs) for an excitable cell simulator based on the nonlinear FitzHugh-Nagumo model. Despite the plant’s nonlinearity, we are able to formulate the model predictive control problem as an instance of quadratic programming, using a PieceWise Affine (PWA) abstraction of the plant. The speed-versus-accuracy tradeoff for the explicit and online versions is analyzed on various reference trajectories. Our MPC-based approach, enabled by the PWA abstraction, presents a framework for designing automated in silico biomedical control strategies for excitable cells, such as cardiac myocytes and neurons.

Pages: 52 to 58

Copyright: Copyright (c) IARIA, 2014

Publication date: April 20, 2014

Published in: conference

ISSN: 2308-4383

ISBN: 978-1-61208-335-3

Location: Chamonix, France

Dates: from April 20, 2014 to April 24, 2014