PhD in Engineering Science by Tecnologico de Monterrey, Mexico.
Current postdoctoral fellow at University of Waterloo.
My research interests include: optimal control, model predictive control, scheduling and nonlinear optimization of chemical and energy processes.
I would like to show how Julia/JuMP can be used to solve nonlinear (large-scale) optimal control problems in chemical processes by applying a direct method. The problem is solved as an NLP after applying orthogonal collocation on constant or moving finite elements with control parametrization. Collocation points and Butcher tableau are generated with Jacobi.jl. NLP problems are solved in JuMP with Ipopt and MA27 solvers. An ilustrative example is shown and future directions are discussed.