Summary
Optimization of dynamic processes described by partial differential-algebraic equations (PDAE) is a challenging task due to dimension and complexity of the problems. Fast solutions methods are achieved by using a simultaneous approach for a close coupling of the optimization aspect of the overall algorithm with the solution method of the dynamic system. Especially using partially reduced sequential quadratic programming (PRSQP) approaches reduces the computational complexity while still being able to incorporate inequality constraints. An effective and straightforward generalization of the methods to treat optimization tasks modeled as multiple set point optimization problems is shown. Based on the simultaneous approach for optimization problems in NMPC an efficient real-time iteration technique is developed. As industrial applications we present shape optimization of turbine blades, operation optimization of a catalytic tube reactor and the real-time optimization of a continuous distillation column.
This work has been supported by the German Research Foundation (DFG) through SFB 359 (Project A4) at the University of Heidelberg. Furthermore, the authors thank the cooperation partners of the “Institut für Systemdynamik und Regelungstechnik” (ISR) and the “Institut für Systemtheorie Technischer Prozesse” (IST), University of Stuttgart, for the common work on NMPC of the distillation column, and Bayer Technology Services, Leverkusen, for providing a large-scale complex optimization task of the catalytic tube reactor.
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Bock, H.G., Kostina, E., Schäfer, A., Schlöder, J.P., Schulz, V. (2007). Multiple Set Point Partially Reduced SQP Method for Optimal Control of PDE. In: Jäger, W., Rannacher, R., Warnatz, J. (eds) Reactive Flows, Diffusion and Transport. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28396-6_7
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