| Abstract: |
| In this work, we developed a reduced ordinary differential equation model of acute inflammatory response to endotoxin challenge. To modulate inflammation, an open-loop optimal control based treatment strategy was formulated to regulate endotoxin-induced inflammatory response. As open-loop control methods do not have the ability to incorporate disturbances in the system as time progresses, we implemented a feedback scheme known as Nonlinear Model Predictive Control (NMPC) in conjunction with Unscented Kalman Filter (UKF). In conclusion, we demonstrated our methodology with an example where noise was added to our simulated results to create an experimental data with noise. Further, UKF was used to filter out the noisy data and then estimate the unobserved states at every recalculation step in the NMPC scheme. |
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