Soft-Constrained Stochastic MPC of Markov Jump Linear Systems : Application to Real-Time Control With Deadline Overruns
(2025) In IEEE Control Systems Letters 9. p.1532-1537- Abstract
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... (More)
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.
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- author
- Gallant, Melanie ; Mark, Christoph ; Pazzaglia, Paolo ; von Keler, Johannes ; Beermann, Laura ; Schmidt, Kevin and Maggio, Martina LU
- organization
- publishing date
- 2025
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Markov processes, predictive control, Stochastic optimal control, switched systems, uncertain systems
- in
- IEEE Control Systems Letters
- volume
- 9
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:105009102917
- ISSN
- 2475-1456
- DOI
- 10.1109/LCSYS.2025.3581518
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2017 IEEE.
- id
- 2d029b09-4378-47c1-9cf0-67d0b3af8556
- date added to LUP
- 2026-01-13 16:28:11
- date last changed
- 2026-01-14 15:01:26
@article{2d029b09-4378-47c1-9cf0-67d0b3af8556,
abstract = {{<p>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.</p>}},
author = {{Gallant, Melanie and Mark, Christoph and Pazzaglia, Paolo and von Keler, Johannes and Beermann, Laura and Schmidt, Kevin and Maggio, Martina}},
issn = {{2475-1456}},
keywords = {{Markov processes; predictive control; Stochastic optimal control; switched systems; uncertain systems}},
language = {{eng}},
pages = {{1532--1537}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Control Systems Letters}},
title = {{Soft-Constrained Stochastic MPC of Markov Jump Linear Systems : Application to Real-Time Control With Deadline Overruns}},
url = {{http://dx.doi.org/10.1109/LCSYS.2025.3581518}},
doi = {{10.1109/LCSYS.2025.3581518}},
volume = {{9}},
year = {{2025}},
}