Debayan Roy, Licong Zhang, Wanli Chang, Dip Goswami, B. Vogel‐Heuser, S. Chakraborty
{"title":"分布式嵌入式控制器自动合成的工具集成","authors":"Debayan Roy, Licong Zhang, Wanli Chang, Dip Goswami, B. Vogel‐Heuser, S. Chakraborty","doi":"10.1145/3477499","DOIUrl":null,"url":null,"abstract":"\n Controller design and their software implementations are usually done in isolated design spaces using respective COTS design tools. However, this separation of concerns can lead to long debugging and integration phases. This is because assumptions made about the implementation platform during the design phase—e.g., related to timing—might not hold in practice, thereby leading to unacceptable control performance. In order to address this, several\n control/architecture co-design\n techniques have been proposed in the literature. However, their adoption in practice has been hampered by the lack of design flows using commercial tools. To the best of our knowledge, this is the first article that implements such a\n co-design\n method using commercially available design tools in an automotive setting, with the aim of minimally disrupting existing design flows practiced in the industry. The goal of such co-design is to\n jointly\n determine controller and platform parameters in order to avoid any\n design-implementation gap\n , thereby minimizing implementation time testing and debugging. Our setting involves distributed implementations of control algorithms on automotive\n electronic control units\n (\n ECUs\n ) communicating via a FlexRay bus. The co-design and the associated toolchain\n Co-Flex\n jointly determines controller and FlexRay parameters (that impact signal delays) in order to optimize specified design metrics. Co-Flex seamlessly integrates the modeling and analysis of control systems in MATLAB/Simulink with platform modeling and configuration in SIMTOOLS/SIMTARGET that is used for configuring FlexRay bus parameters. It automates the generation of multiple\n Pareto-optimal\n design options with respect to the quality of control and the resource usage, that an engineer can choose from. In this article, we outline a step-by-step software development process based on Co-Flex tools for distributed control applications. While our exposition is automotive specific, this design flow can easily be extended to other domains.\n","PeriodicalId":120188,"journal":{"name":"ACM Trans. Cyber Phys. Syst.","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Tool Integration for Automated Synthesis of Distributed Embedded Controllers\",\"authors\":\"Debayan Roy, Licong Zhang, Wanli Chang, Dip Goswami, B. Vogel‐Heuser, S. Chakraborty\",\"doi\":\"10.1145/3477499\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Controller design and their software implementations are usually done in isolated design spaces using respective COTS design tools. However, this separation of concerns can lead to long debugging and integration phases. This is because assumptions made about the implementation platform during the design phase—e.g., related to timing—might not hold in practice, thereby leading to unacceptable control performance. In order to address this, several\\n control/architecture co-design\\n techniques have been proposed in the literature. However, their adoption in practice has been hampered by the lack of design flows using commercial tools. To the best of our knowledge, this is the first article that implements such a\\n co-design\\n method using commercially available design tools in an automotive setting, with the aim of minimally disrupting existing design flows practiced in the industry. The goal of such co-design is to\\n jointly\\n determine controller and platform parameters in order to avoid any\\n design-implementation gap\\n , thereby minimizing implementation time testing and debugging. Our setting involves distributed implementations of control algorithms on automotive\\n electronic control units\\n (\\n ECUs\\n ) communicating via a FlexRay bus. The co-design and the associated toolchain\\n Co-Flex\\n jointly determines controller and FlexRay parameters (that impact signal delays) in order to optimize specified design metrics. Co-Flex seamlessly integrates the modeling and analysis of control systems in MATLAB/Simulink with platform modeling and configuration in SIMTOOLS/SIMTARGET that is used for configuring FlexRay bus parameters. It automates the generation of multiple\\n Pareto-optimal\\n design options with respect to the quality of control and the resource usage, that an engineer can choose from. In this article, we outline a step-by-step software development process based on Co-Flex tools for distributed control applications. While our exposition is automotive specific, this design flow can easily be extended to other domains.\\n\",\"PeriodicalId\":120188,\"journal\":{\"name\":\"ACM Trans. Cyber Phys. 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Tool Integration for Automated Synthesis of Distributed Embedded Controllers
Controller design and their software implementations are usually done in isolated design spaces using respective COTS design tools. However, this separation of concerns can lead to long debugging and integration phases. This is because assumptions made about the implementation platform during the design phase—e.g., related to timing—might not hold in practice, thereby leading to unacceptable control performance. In order to address this, several
control/architecture co-design
techniques have been proposed in the literature. However, their adoption in practice has been hampered by the lack of design flows using commercial tools. To the best of our knowledge, this is the first article that implements such a
co-design
method using commercially available design tools in an automotive setting, with the aim of minimally disrupting existing design flows practiced in the industry. The goal of such co-design is to
jointly
determine controller and platform parameters in order to avoid any
design-implementation gap
, thereby minimizing implementation time testing and debugging. Our setting involves distributed implementations of control algorithms on automotive
electronic control units
(
ECUs
) communicating via a FlexRay bus. The co-design and the associated toolchain
Co-Flex
jointly determines controller and FlexRay parameters (that impact signal delays) in order to optimize specified design metrics. Co-Flex seamlessly integrates the modeling and analysis of control systems in MATLAB/Simulink with platform modeling and configuration in SIMTOOLS/SIMTARGET that is used for configuring FlexRay bus parameters. It automates the generation of multiple
Pareto-optimal
design options with respect to the quality of control and the resource usage, that an engineer can choose from. In this article, we outline a step-by-step software development process based on Co-Flex tools for distributed control applications. While our exposition is automotive specific, this design flow can easily be extended to other domains.