Tracking normal action potential based on the FHN model using adaptive feedback linearization technique

In this paper, we present an adaptive input-output feedback linearization controller, using the single cell FitzHugh-Nagumo (FHN) model, to track a normal action potential. The problem is to design a feedback control law which stabilizes an unstable rhythm of the FHN model and track a normal action potential only using output feedback. Here we use an adaptive observer to estimate the unknown parameters and states of the FHN model so that it can be used in the controller design process. The procedure is based on the combination of high-gain parameter and state observer and feedback linearization controller with the aim of reference signal tracking for the single cell FHN model. Simulation results show the efficacy of the proposed technique. FHN model seems to correctly capture the electrical behavior of the cardiac cells, and therefore this method might have important applications, especially, in the ground of control of cardiac arrhythmia.

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