Dynamic parametric sensitivity optimization using simultaneous discretization in JModelica.org

Dynamic optimization problems involving parametric sensitivities, such as optimal experimental design, are typically solved using shooting-based methods, while leveraging numerical integrators with sensitivity computation capabilities. In this paper we present how simultaneous discretization can be employed to solve these problems, by augmenting the dynamic optimization problems with forward sensitivity equations. We present an implementation of this approach in the open-source, Modelica-based tool JModelica.org, which addresses the need for solving optimal experimental design problems in Modelica tools. The implementation is demonstrated on a fed-batch reactor and a plate-fin heat exchanger.