Soft-Constrained Stochastic MPC of Markov Jump Linear Systems: Application to Real-Time Control With Deadline Overruns
Modern real-time control systems can sporadically exceed the computation deadlines, which may lead to a deterioration in performance or even instability if not actively accounted for. This letter proposes a stochastic model predictive control approach that incorporates deadline miss probabilities of subsequent control task executions in a scenario tree. To account for the effect of missed deadlines, we utilize Markov jump linear systems that allow us to prove mean-square stability and recursive feasibility under hard input and mixed hard/soft state constraints. The proposed stochastic controller is benchmarked using a Furuta pendulum, demonstrating improved performance and an increased feasible region compared to a nominal and a hard-constrained stochastic controller, respectively.
Authors
- Martina Maggio (ORCID: https://orcid.org/0000-0002-1143-1127)
- P Pazzaglia (ORCID: https://orcid.org/0000-0003-0377-3327)
- Kevin Schmidt (ORCID: https://orcid.org/0000-0003-0808-1557)
- Laura Beermann
- Christoph Mark (ORCID: https://orcid.org/0000-0002-5275-9428)
- Johannes von Keler
- Melanie Gallant
Institutions
- Robert Bosch (Germany) (DE)
- Saarland University (DE)
Publication Details
- Journal
- IEEE Control Systems Letters
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/lcsys.2025.3581518
- Citations
- 1
- Primary Topic
- Advanced Control Systems Optimization
- Type
- article
- Field-Weighted Citation Impact
- 1.21
Funders
- The Ministry of Economic Affairs and Employment