Stochastic Analysis of Control Systems Subject to Communication and Computation Faults

Control theory allows one to design controllers that are robust to external disturbances, model simplification, and modelling inaccuracy. Researchers have investigated whether the robustness carries on to the controller’s digital implementation, mostly looking at how the controller reacts to either...

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Published inACM transactions on embedded computing systems Vol. 22; no. 5s; pp. 1 - 25
Main Authors Vreman, Nils, Maggio, Martina
Format Journal Article
LanguageEnglish
Published New York, NY ACM 09.09.2023
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ISSN1539-9087
1558-3465
DOI10.1145/3609123

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Abstract Control theory allows one to design controllers that are robust to external disturbances, model simplification, and modelling inaccuracy. Researchers have investigated whether the robustness carries on to the controller’s digital implementation, mostly looking at how the controller reacts to either communication or computational problems. Communication problems are typically modelled using random variables (i.e., estimating the probability that a fault will occur during a transmission), while computational problems are modelled using deterministic guarantees on the number of deadlines that the control task has to meet. These fault models allow the engineer to both design robust controllers and assess the controllers’ behaviour in the presence of isolated faults. Despite being very relevant for the real-world implementations of control system, the question of what happens when these faults occur simultaneously does not yet have a proper answer. In this paper, we answer this question in the stochastic setting, using the theory of Markov Jump Linear Systems to provide stability contracts with almost sure guarantees of convergence. For linear time-invariant Markov jump linear systems, mean square stability implies almost sure convergence – a property that is central to our investigation. Our research primarily emphasises the validation of this property for closed-loop systems that are subject to packet losses and computational overruns, potentially occurring simultaneously. We apply our method to two case studies from the recent literature and show their robustness to a comprehensive set of faults. We employ closed-loop system simulations to empirically derive performance metrics that elucidate the quality of the controller implementation, such as the system settling time and the integral absolute error.
AbstractList Control theory allows one to design controllers that are robust to external disturbances, model simplification, and modelling inaccuracy. Researchers have investigated whether the robustness carries on to the controller’s digital implementation, mostly looking at how the controller reacts to either communication or computational problems. Communication problems are typically modelled using random variables (i.e., estimating the probability that a fault will occur during a transmission), while computational problems are modelled using deterministic guarantees on the number of deadlines that the control task has to meet. These fault models allow the engineer to both design robust controllers and assess the controllers’ behaviour in the presence of isolated faults. Despite being very relevant for the real-world implementations of control system, the question of what happens when these faults occur simultaneously does not yet have a proper answer. In this paper, we answer this question in the stochastic setting, using the theory of Markov Jump Linear Systems to provide stability contracts with almost sure guarantees of convergence. For linear time-invariant Markov jump linear systems, mean square stability implies almost sure convergence – a property that is central to our investigation. Our research primarily emphasises the validation of this property for closed-loop systems that are subject to packet losses and computational overruns, potentially occurring simultaneously. We apply our method to two case studies from the recent literature and show their robustness to a comprehensive set of faults. We employ closed-loop system simulations to empirically derive performance metrics that elucidate the quality of the controller implementation, such as the system settling time and the integral absolute error.
ArticleNumber 144
Author Vreman, Nils
Maggio, Martina
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  surname: Maggio
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  email: maggio@cs.uni-saarland.de
  organization: Department of Computer Science, Saarland University, Germany
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Issue 5s
Keywords deadline misses
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packet dropouts
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Snippet Control theory allows one to design controllers that are robust to external disturbances, model simplification, and modelling inaccuracy. Researchers have...
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acm
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SubjectTerms Computer systems organization
Control Engineering
Electrical Engineering, Electronic Engineering, Information Engineering
Elektroteknik och elektronik
Embedded and cyber-physical systems
Embedded Systems
Engineering and Technology
Inbäddad systemteknik
Markov Jump Linear Systems
Real-Time Systems
Reglerteknik
Teknik
SubjectTermsDisplay Computer systems organization -- Embedded and cyber-physical systems
Computer systems organization -- Real-time systems
Title Stochastic Analysis of Control Systems Subject to Communication and Computation Faults
URI https://dl.acm.org/doi/10.1145/3609123
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Volume 22
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