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Adaptive Scenario Generation for Multistage NMPC with Shrinking Horizons
- Source :
- IFAC-PapersOnLine. 52:586-591
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- We present a multistage scheme for shrinking horizon nonlinear model predictive control (NMPC). This approach generates scenario trees on-line in an adaptive manner, and assembles them from predictions of worst-case uncertainty realizations through first-order approximations of the process model. A key result of this approach is that both size and complexity of the resultant optimal control problems do not scale directly with the number of uncertain model parameters. Moreover, we apply and demonstrate this approach on a challenging industrially-relevant semi-batch polymerization process under parametric model uncertainty. The results show that adaptive scenario generation leads to improved performance, while maintaining the attained level of robustness for the considered process.
- Subjects :
- 0209 industrial biotechnology
Model predictive control
Mathematical optimization
020901 industrial engineering & automation
Control and Systems Engineering
Computer science
Robustness (computer science)
020208 electrical & electronic engineering
Parametric model
0202 electrical engineering, electronic engineering, information engineering
02 engineering and technology
Optimal control
Subjects
Details
- ISSN :
- 24058963
- Volume :
- 52
- Database :
- OpenAIRE
- Journal :
- IFAC-PapersOnLine
- Accession number :
- edsair.doi...........d6f3aae1a2bfda20bfe1077a31f05442