Abstract
In this paper, a biologically inspired optimal control strategy, denoted as BIO-CS, is proposed for nonlinear chemical processes with constraints. This approach combines the ants’ rule of pursuit idea with multiagent and optimal control concepts. In this agent-based framework, starting from an initially feasible trajectory for the leader agent, each follower agent improves its path toward the set point by employing optimal control laws. As the number of agents progresses, the trajectories converge to an optimal solution. The developed algorithm employs gradient-based optimal control solvers for the intermediate problems associated with the leader–follower local interactions. The effectiveness of the developed approach is illustrated by addressing the nonlinear dynamic model of a fermentation process to produce ethanol, whose challenges in process dynamics include oscillations and steady-state multiplicity. The proposed method is successfully implemented for this system considering set point tracking, dist...
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