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Robust feasible control based on multi-stage eNMPC considering worst-case scenarios
- Source :
- Journal of Process Control. 69:8-15
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- The goal of this work is an efficient control scheme for the robust satisfaction of constraints for batch processes under parametric uncertainties. The multi-stage economic nonlinear model-predictive controller (eNMPC) [S. Lucia, et al. J. Process Control, 2013] is combined with two different methods for robust dynamic optimization. The multi-stage NMPC considers a scenario tree, branching at each sampling interval. In this work, the scenarios for the branches are generated with two previously investigated methods of detecting worst-case scenarios. One method is based on discretization of the uncertain parameter set (J. Puschke, et al. Comput. Chem. Eng., Vol. 98, 2017a). With this approach, all worst-case models are considered, including points not lying at the boundary of the uncertainty set. The other method is a heuristic approach (J. Puschke, et al. Comput. Chem. Eng., 2017b), which considers only values at the boundary with a high sensitivity. These methods for robust control are evaluated on the basis of an illustrative case study. The results show that, in contrast to the nominal eNMPC, less or even no constraint violations occur.
- Subjects :
- 0209 industrial biotechnology
Mathematical optimization
Discretization
Computer science
02 engineering and technology
Industrial and Manufacturing Engineering
Scenario tree
Computer Science Applications
Multi stage
Nonlinear system
020901 industrial engineering & automation
020401 chemical engineering
Control and Systems Engineering
Modeling and Simulation
Process control
0204 chemical engineering
Robust control
Sampling interval
Parametric statistics
Subjects
Details
- ISSN :
- 09591524
- Volume :
- 69
- Database :
- OpenAIRE
- Journal :
- Journal of Process Control
- Accession number :
- edsair.doi...........1368a26e79543d933a1340dcb12a8f4a