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Soft-Constrained Stochastic MPC of Markov Jump Linear Systems : Application to Real-Time Control With Deadline Overruns

Gallant, Melanie ; Mark, Christoph ; Pazzaglia, Paolo ; von Keler, Johannes ; Beermann, Laura ; Schmidt, Kevin and Maggio, Martina LU (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
; ; ; ; ; and
organization
publishing date
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}},
}