Fair control of uncertain dynamical systems under LTL specifications
File(s)
Accepted version
Author(s)
Zhou, Can
Yu, Pian
Parisini, Thomas
Abate, Alessandro
Gao, Yulong
Type
Conference Paper
Abstract
Uncertainties are inevitable for control of dynamical systems of practical relevance. The conventional robust
control methods assume persistent worst-case realisations of uncertainties, which leads to conservative solutions. To relax this assumption, we exploit the fairness notion in formal verification to qualitatively capture realistic epistemic disturbance behaviours. We study the fair control problem, that is, to maximise the probability of satisfying an Linear Temporal Logic subject to an action-based fairness constraint for uncertain dynamical systems. The action-based fairness of epistemic disturbances can be defined flexibly: by their observed behaviour and/or
by their interaction with control input, enabling both input-
dependent and independent disturbance modelling. We develop a sound and complete methodology to perform correct-by-design synthesis. We show that this optimal control problem is equivalent to a reachability problem in the fairness-realisable sub-product Markov decision process. We validate our results over a case study of room temperature regulation.
control methods assume persistent worst-case realisations of uncertainties, which leads to conservative solutions. To relax this assumption, we exploit the fairness notion in formal verification to qualitatively capture realistic epistemic disturbance behaviours. We study the fair control problem, that is, to maximise the probability of satisfying an Linear Temporal Logic subject to an action-based fairness constraint for uncertain dynamical systems. The action-based fairness of epistemic disturbances can be defined flexibly: by their observed behaviour and/or
by their interaction with control input, enabling both input-
dependent and independent disturbance modelling. We develop a sound and complete methodology to perform correct-by-design synthesis. We show that this optimal control problem is equivalent to a reachability problem in the fairness-realisable sub-product Markov decision process. We validate our results over a case study of room temperature regulation.
Date Issued
2026-01-12
Date Acceptance
2025-07-16
Citation
2025 IEEE 64th Conference on Decision and Control (CDC), 2026, pp.3940-3945
ISBN
979-8-3315-2627-6
Publisher
IEEE
Start Page
3940
End Page
3945
Journal / Book Title
2025 IEEE 64th Conference on Decision and Control (CDC)
Copyright Statement
Copyright © 2025, IEEE. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Source
64th IEEE Conference on Decision and Control
Publication Status
Published
Start Date
2025-12-10
Finish Date
2025-12-12
Coverage Spatial
Rio de Janeiro, Brazil