Conference paper
Tuning of methods for offset free MPC based on ARX model representations
Department of Chemical and Biochemical Engineering, Technical University of Denmark1
Mathematical Statistics, Department of Informatics and Mathematical Modeling, Technical University of Denmark2
Department of Informatics and Mathematical Modeling, Technical University of Denmark3
Computer Aided Process Engineering Center, Department of Chemical and Biochemical Engineering, Technical University of Denmark4
Scientific Computing, Department of Informatics and Mathematical Modeling, Technical University of Denmark5
Center for Energy Resources Engineering, Centers, Technical University of Denmark6
In this paper we investigate model predictive control (MPC) based on ARX models. ARX models can be identified from data using convex optimization technologies and is linear in the system parameters. Compared to other model parameterizations this feature is an advantage in embedded applications for robust and automatic system identification.
Standard MPC is not able to reject a sustained, unmeasured, non zero mean disturbance and will therefore not provide offset free tracking. Offset free tracking can be guaranteed for this type of disturbances if Δ variables are used or if the state space is extended with a disturbance model state. The relation between the base case and the two extended methods are illustrated which provides good understanding and a platform for discussing tuning for good closed loop performance.
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 2010 |
| Pages: | 2255-2360 |
| Proceedings: | American Control Conference (ACC 2010) |
| ISBN: | 1424474256 , 1424474264 , 1424474272 , 9781424474257 , 9781424474264 and 9781424474271 |
| ISSN: | 23785861 and 07431619 |
| Types: | Conference paper |
| DOI: | 10.1109/ACC.2010.5530560 |
| ORCIDs: | Huusom, Jakob Kjøbsted , Poulsen, Niels Kjølstad , Jørgensen, Sten Bay and Jørgensen, John Bagterp |
