Name
Title | ||
|---|---|---|
Scenario-Based Probabilistic Reachable Sets for Recursively Feasible Stochastic Model Predictive Control. |
Abstract | ||
|---|---|---|
This letter presents a stochastic model predictive control approach (MPC) for linear discrete-time systems subject to unbounded and correlated additive disturbance sequences, which makes use of the scenario approach for offline computation of probabilistic reachable sets. These sets are used in a tube-based MPC formulation, resulting in low computational requirements. Using a recently proposed MPC... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/LCSYS.2019.2949194 | IEEE Control Systems Letters |
Keywords | Field | DocType |
Electron tubes,Optimization,Probabilistic logic,Stochastic processes,Additives,Optimal control | Constraint satisfaction,Mathematical optimization,Optimal control,Nonlinear system,Overhead crane,Computer science,Stochastic process,Initialization,Probabilistic logic,Computation | Journal |
Volume | Issue | ISSN |
4 | 2 | 2475-1456 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lukas Hewing | 1 | 25 | 4.27 |
| Melanie Nicole Zeilinger | 2 | 298 | 30.91 |