Tracking Action Potentials of Nonlinear Excitable Cells Using Model Predictive Control
Md. Ariful Islam, Abhishek Murthy, Tushar Deshpande, Scott D. Stoller, Scott A. Smolka, Ezio Bartocci, and Radu Grosu

We present explicit and online Model Predictive Controllers (MPCs) for an excitable cell simulator based on the nonlinear FitzHugh-Nagumo model. Despite the plantas 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.