Real-Time Optimization for Large Scale Nonlinear Processes

Efficient numerical methods for the real-time solution of optimal control problems arising in nonlinear model predictive control (NMPC) are presented, and their contraction properties are investigated theoretically. The practical applicability of the methods is demonstrated in an experimental application to a real distillation column, involving the real-time optimization of a differential algebraic process model with more than 200 states, with sampling times of only a few seconds. In a numerical experiment, the periodic control of an unstable system, an airborne kite that is flying loopings, is investigated. The algorithm shows excellent robustness and real-time performance for both challenging on-line optimization examples.

Level thesis:degree_level

thesis.doctoral

Grantor dc:publisher

Universität Heidelberg

Year

2001

Author dc:creator

• Diehl, Moritz

Contributors dc:contributor

• Bock, Hans Georg

Repository record source_url

http://www.ub.uni-heidelberg.de/archiv/1659

OAI identifier oai:identifier

oai:archiv.ub.uni-heidelberg.de:1659