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 in | ACM transactions on embedded computing systems Vol. 22; no. 5s; pp. 1 - 25 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
New York, NY
ACM
09.09.2023
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Online Access | Get full text |
ISSN | 1539-9087 1558-3465 |
DOI | 10.1145/3609123 |
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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. |
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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 |
Author_xml | – sequence: 1 givenname: Nils orcidid: 0000-0002-6732-9500 surname: Vreman fullname: Vreman, Nils email: nils.vreman@control.lth.se organization: Department of Automatic Control, Lund Unversity, Sweden – sequence: 2 givenname: Martina orcidid: 0000-0002-1143-1127 surname: Maggio fullname: Maggio, Martina email: maggio@cs.uni-saarland.de organization: Department of Computer Science, Saarland University, Germany |
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Cites_doi | 10.1145/3192366.3192406 10.4230/LIPIcs.ECRTS.2020.21 10.1109/ACC.2002.1025245 10.4230/LIPIcs.ECRTS.2018.6 10.1109/JPROC.2006.887306 10.1145/3139258.3139276 10.1109/TAC.2011.2107631 10.1109/RTCSA.2018.00028 10.4230/LIPIcs.ECRTS.2018.15 10.1080/00207177508922037 10.1109/CDC.2002.1184681 10.4230/LITES-v006-i001-a003 10.1109/CDC.2018.8619831 10.1109/RTAS54340.2022.00010 10.1109/TAC.2002.800674 10.1109/CDC.2002.1184698 10.4230/LIPIcs.ECRTS.2019.1 10.1016/j.automatica.2013.11.037 10.1109/2.386982 10.1016/j.automatica.2010.06.017 10.1109/RTSS52674.2021.00029 10.4230/LIPIcs.ECRTS.2021.15 10.1016/j.ifacol.2021.08.481 10.1145/2220336.2220340 10.1145/3126497 10.1080/00207179408923131 10.1109/CDC.2017.8264364 10.1109/TCAD.2022.3198905 10.1016/j.automatica.2010.03.007 10.4230/LIPIcs.ECRTS.2018.10 10.23919/DATE.2018.8342212 10.1016/j.ifacol.2020.12.307 10.4230/LIPIcs.ECRTS.2021.16 10.1109/ECC.2016.7810677 10.23919/DATE.2019.8714908 10.5555/248504 10.1145/2220336.2220340 10.1109/12.919277 10.1145/3192366.3192406 10.1109/TAC.2008.2010999 10.1007/b138575 10.1145/3139258.3139276 10.5555/248979 10.1109/ACCESS.2022.3144217 10.1109/JPROC.2002.805825 10.1145/3126497 |
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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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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 |
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