Bifurcation analysis and multiobjective nonlinear model predictive control of sustainable ecosystems
Abstract
Problem: All optimal control work involving ecological models involves single objective optimization. In this work, we perform multiobjective nonlinear model predictive control (MNLMPC) in conjunction with bifurcation analysis on an ecosystem model. Methods: Bifurcation analysis was performed using the MATLAB software MATCONT MATLAB CONTINUITION, while multiobjective nonlinear model predictive control was performed by using the optimization language PYOMO (PYTHON OPTIMIZATION). Results: Rigorous proof showing the existence of bifurcation (branch) points is presented along with computational validation. It is also demonstrated (both numerically and analytically) that the presence of the branch points was instrumental in obtaining the Utopia solution when the multi-objective nonlinear model prediction calculations were performed. Conclusions: The main conclusions of this work are that one can attain the utopia point in MNLMPC calculations because of the branch points that occur in the ecosystem model, and the presence of the branch point can be proved analytically.
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