(91b) Dyos: A Software Package for Dynamic Optimization Using Direct Shooting

Authors: 
Mitsos, A. - Presenter, RWTH Aachen University
Faust, J. M. M., RWTH Aachen
Schulze, J., RWTH Aachen University (AVT.SVT)
Caspari, A., RWTH Aachen University
Hannemann-Tamás, R., RWTH Aachen University
Sass, S., RWTH Aachen University
Mhamdi, A., RWTH Aachen University
Over the past decades, dynamic optimization has become a fundamental instrument in process design and operation. We present DyOS [1], our in-house open-source software framework for solving optimization problems with large-scale differential algebraic equation systems (DAEs). DyOS features state-of-the-art open-source as well as commercial DAE integrators and nonlinear programming solvers. A special feature is that the parameterization of the control variables can be determined automatically using control grid adaptation [2, 3]. This allows for a highly performant problem-adapted solution of the dynamic optimization problems. In addition to various model interfaces for C++ formulations, DyOS provides an interface to functional mock-up units (FMU). FMU offer a standardized interface to higher object-oriented, declarative languages such as Modelica. Equipped with MATLAB, Python, and C++ bindings, optimizing with DyOS is straightforward. Moreover, a graphic user interface allows direct and intuitive usage. In this tutorial session, we give a brief overview of the features of DyOS and provide instructions on how to get started with the software. Here, we show how to set up and solve a simple nonlinear dynamic optimization problem. Finally, we demonstrate the strong capabilities of DyOS on small and large-scale real-world problems.

* Corresponding author: A. Mitsos

AVT Process Systems Engineering, RWTH Aachen University, 52056 Aachen, Germany

E-mail: amitsos@alum.mit.edu

Acknowledgements

The authors gratefully acknowledge the financial support of the Kopernikus project SynErgie by the Federal Ministry of Education and Research (BMBF) and of the KoPPonA 2.0 project by German Federal Ministry for Economic Affairs and Energy (BMWi) under grant number 03EN2004L and the project supervision for both projects by the project management organization Projektträger Jülich.

References

  • Caspari, A.; Bremen, A. M.; Faust, J. M. M.; Jung, F.; Kappatou, C. D.; Sass, S.; Vaupel, Y.; Hannemann-Tamàs, R.; Mhamdi, A. & Mitsos, A., DyOS – A framework for optimization of large-scale differential algebraic equation systems, Computer Aided Chemical Engineering, 2019, 46, 619-624
  • Schlegel, M.; Stockmann, K.; Binder, T. & Marquardt, W., Dynamic optimization using adaptive control vector parameterization, Computers & Chemical Engineering, 2005, 29, 1731-1751
  • Assassa, F. & Marquardt, W., Optimality-based grid adaptation for input-affine optimal control problems, Computers & Chemical Engineering, 2016, 92, 189-203