Multiobjective nonlinear model predictive control of microalgal culture processes

Abstract

Lakshmi. N. Sridhar

A rigorous multiobjective nonlinear model predictive control strategy was used for dynamic models involving the microalgae culture process. The models are the droop model, the nitrogen limited microalgae culture process model, and the Thornton model. It was shown that the implementation of the NLMPC method causes an increase in algal growth. The optimization language pyomo is used in conjunction with the state-of-the-art global optimization solvers IPOPT and BARON. Pareto surfaces are generated. When some optimal control profiles were found to exhibit sharp spikes, an activation factor involving the hyperbolic cotangent function was used to eliminate the inconvenient spikes.

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