Analysis and Control of the Inflammatory Immune Response Model
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Abstract
Inflammation is the body’s way of responding to infection, and one needs to develop effective strategies to control it. In this work, bifurcation analysis and multiobjective nonlinear model predictive control are performed on an inflammatory immune response model. Bifurcation analysis is a powerful mathematical tool for studying the nonlinear dynamics of any process. Several factors must be considered, and multiple objectives must be met simultaneously. The MATLAB program MATCONT was used to perform the bifurcation analysis. The MNLMPC calculations were performed using the optimization language PYOMO in conjunction with the state-of-the-art global optimization solvers IPOPT and BARON. The bifurcation analysis revealed the existence of limit and branch points. The MNLMC converged on the Utopia solution (best possible). The limit and branch points (which cause multiple steady-state solutions from a singular point) are very beneficial because they enable the Multiobjective nonlinear model predictive control calculations to converge to the Utopia point (the best possible solution) in the model.
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