Visualisation of Control Software for Cyber-Physical Systems
Cyber-physical systems are typically composed of a physical system (<i>plant</i>) controlled by a software (<i>controller</i>). Such a controller, given a plant state <i>s</i> and a plant action <i>u</i>, returns 1 iff taking action <i>u</i>...
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MDPI AG
2021-04-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/12/5/178 |
| _version_ | 1797536829889576960 |
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| author | Igor Melatti Federico Mari Ivano Salvo Enrico Tronci |
| author_facet | Igor Melatti Federico Mari Ivano Salvo Enrico Tronci |
| author_sort | Igor Melatti |
| collection | DOAJ |
| description | Cyber-physical systems are typically composed of a physical system (<i>plant</i>) controlled by a software (<i>controller</i>). Such a controller, given a plant state <i>s</i> and a plant action <i>u</i>, returns 1 iff taking action <i>u</i> in state <i>s</i> leads to the physical system goal or at least one step closer to it. Since a controller <i>K</i> is typically stored in compressed form, it is difficult for a human designer to actually understand how “good” <i>K</i> is. Namely, natural questions such as “does <i>K</i> cover a wide enough portion of the system state space?”, “does <i>K</i> cover the most important portion of the system state space?” or “which actions are enabled by <i>K</i> in a given portion of the system space?” are hard to answer by directly looking at <i>K</i>. This paper provides a methodology to automatically generate a picture of <i>K</i> as a 2D diagram, starting from a canonical representation for <i>K</i> and relying on available open source graphing tools (e.g., Gnuplot). Such picture allows a software designer to answer to the questions listed above, thus achieving a better qualitative understanding of the controller at hand. |
| first_indexed | 2024-03-10T12:06:23Z |
| format | Article |
| id | doaj.art-18b4bf3c67eb4190be48dcce339d885d |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-10T12:06:23Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-18b4bf3c67eb4190be48dcce339d885d2023-11-21T16:32:48ZengMDPI AGInformation2078-24892021-04-0112517810.3390/info12050178Visualisation of Control Software for Cyber-Physical SystemsIgor Melatti0Federico Mari1Ivano Salvo2Enrico Tronci3Department of Computer Science, Sapienza University of Rome, Via Salaria 113, 00198 Rome, ItalyDepartment of Movement, Human and Health Sciences, University of Rome “Foro Italico”, Piazza Lauro De Bosis 15, 00135 Rome, ItalyDepartment of Computer Science, Sapienza University of Rome, Via Salaria 113, 00198 Rome, ItalyDepartment of Computer Science, Sapienza University of Rome, Via Salaria 113, 00198 Rome, ItalyCyber-physical systems are typically composed of a physical system (<i>plant</i>) controlled by a software (<i>controller</i>). Such a controller, given a plant state <i>s</i> and a plant action <i>u</i>, returns 1 iff taking action <i>u</i> in state <i>s</i> leads to the physical system goal or at least one step closer to it. Since a controller <i>K</i> is typically stored in compressed form, it is difficult for a human designer to actually understand how “good” <i>K</i> is. Namely, natural questions such as “does <i>K</i> cover a wide enough portion of the system state space?”, “does <i>K</i> cover the most important portion of the system state space?” or “which actions are enabled by <i>K</i> in a given portion of the system space?” are hard to answer by directly looking at <i>K</i>. This paper provides a methodology to automatically generate a picture of <i>K</i> as a 2D diagram, starting from a canonical representation for <i>K</i> and relying on available open source graphing tools (e.g., Gnuplot). Such picture allows a software designer to answer to the questions listed above, thus achieving a better qualitative understanding of the controller at hand.https://www.mdpi.com/2078-2489/12/5/178control software synthesiscontrol software visualisationcyberphysical systemsmodel checking |
| spellingShingle | Igor Melatti Federico Mari Ivano Salvo Enrico Tronci Visualisation of Control Software for Cyber-Physical Systems Information control software synthesis control software visualisation cyberphysical systems model checking |
| title | Visualisation of Control Software for Cyber-Physical Systems |
| title_full | Visualisation of Control Software for Cyber-Physical Systems |
| title_fullStr | Visualisation of Control Software for Cyber-Physical Systems |
| title_full_unstemmed | Visualisation of Control Software for Cyber-Physical Systems |
| title_short | Visualisation of Control Software for Cyber-Physical Systems |
| title_sort | visualisation of control software for cyber physical systems |
| topic | control software synthesis control software visualisation cyberphysical systems model checking |
| url | https://www.mdpi.com/2078-2489/12/5/178 |
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