Design and Implementation of A Building Control System in Real-Time Devs

Earle, Ben; Bjornson, Kyle; Boi-Ukeme, Joseph; Wainer, Gabriel

doi:10.23919/springsim.2019.8732922

Cited by 6 publications

(5 citation statements)

References 12 publications

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“…The DEVS formalism decomposes complex systems into atomic and coupled models, where the atomic models specify the behavior, and the coupled model specifies the structure [17]. Various real-time systems have been successfully developed using DEVS [18,19,20]. However, while the different methods developed to adapt DEVS methodology or other discrete event methods set the right foundation for CPS design, they are not formalized to handle faults within the modeling framework.…”

Section: Figure 1 Components Of a Cps [6]mentioning

confidence: 99%

“…DEVS provides a rich structural representation of components and can explicitly specify timing, which makes it easily adaptable for realtime systems. Various real-time systems have been successfully developed using DEVS [18][19] [20]. In DEVS, a cyber-physical system can be modeled by specifying atomic and coupled models.…”

Section: Discrete Event System Specificationmentioning

confidence: 99%

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A Robust Discrete Event Method for the Design of Cyber-Physical Systems

Boi-Ukeme¹

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The technological advancement in Cyber-Physical Systems (CPS) has seen more sophisticated hardware, leading to systems that are complex, interconnected, and require automation. This trend has made modern CPS fragile and susceptible to faults. Traditional methods for fault detection and diagnosis are unable to adequately scale up to handle the faults that occur in CPS because of the tight interconnectivity between the physical and cyber parts of CPS. Also, real-time requirements present new challenges that are not sufficiently addressed by traditional fault-tolerant design approaches, therefore more intelligent methods are now needed to deal with these faults. To address these issues, we propose an approach to formally define faults, detect, and diagnose faults, and accommodate faults for fault tolerance.For fault detection and diagnosis, we propose a generic fault detection and diagnosis (FDD) scheme capable of diagnosing CPS faults in real-time. The scheme is developed to accommodate different modeling methods but for clarity of explanation, we adapt it to the DEVS formalism. To test the scheme, we implemented a library to store fault codes in a data structure and developed intelligent logic to ensure faults are correctly detected and isolated. We also propose a purely data-driven approach to detect faults in CPS where we have no control over the design of the control system. Our data-driven methods thrive on setting rigorous processes and workflows to ensure that representative data is collected for CPS to ensure that FDD techniques perform optimally.

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Section: Figure 1 Components Of a Cps [6]mentioning

confidence: 99%

Section: Discrete Event System Specificationmentioning

confidence: 99%

A Robust Discrete Event Method for the Design of Cyber-Physical Systems

Boi-Ukeme¹

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“…The existing toolchain used to implement Discrete-Event Modeling of Embedded Systems, ECD++, had some shortcomings that were addressed and improved in Real-Time Cadmium (RT-Cadmium). RT-Cadmium is a Real-Time (RT) DEVS kernel developed on top of the Cadmium DEVS Simulator: (Earle, Bjornson and Ruiz-Martin, et al 2020). RT-Cadmium allows users to switch between simulating and deploying their models with ease.…”

Section: Devs and Rt-devsmentioning

confidence: 99%

“…In (Earle, Bjornson and Boi-Ukeme, et al 2019), the authors presented a building controller built using the E-CD Boost library, which uses a DEVS model to control the lights and emergency systems of a building based on room occupancy and other inputs. These modelbased control systems were developed to optimize energy consumption in buildings.…”

Section: Devs and Rt-devsmentioning

confidence: 99%

Formalization of Cyber-Physical System Interface using Discrete Event System Specifications

Jiresal¹

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Cyber-Physical systems are complex engineered systems that integrate embedded computing into the physical environment. These systems are considered to be "safetycritical" due to their application in the field of medical, transportation, or building control.CPS is composed of tight coupling of the physical and cyber worlds, and the interfaces are interactions that are defined as a bridge between these worlds. The interface is a fundamental characteristic of a CPS and CPS cannot function without it.In this thesis, we propose an architecture of the CPS interface in Discrete EVent System Specification (DEVS) that mimics the functionality of CPS interactions. DEVS provides a formal platform for M&S of discrete event dynamic systems. We propose a DEVS simulation model named DCIF (DEVS CPS Interface Framework) that portrays the complete working of the CPS interface. Later, we also implement and evaluate this interface on real-time hardware. The architecture is verified by creating a synthetic environment that includes multiple test cases in the simulation as well as real-time implementation. Additionally, we apply this framework to a practical case study in the field of building information modeling. Chapter 1: IntroductionCyber-physical systems (CPS) are next-generation engineered systems that integrate embedded computing into the physical environment. Cyber-physical systems are embedded systems where the importance is to be more on an intense link between the computational and physical elements. CPS has been defined by various researchers from different perspectives. For instance, (Marwedel 2006) defines CPS as "embedded systems together with their physical environment" while (Helen 2008) describes CPS as "physical, and engineered systems whose operations are integrated, monitored, and controlled by a computational core". CPSs are made up of the physical world, interfaces, and cyber world (Gunes 2014). Some examples of the application of CPS include air traffic control systems, medical devices, and equipment, railway cross control systems, automotive airbag, smart homes, building systems, etc. (Khaitan and McCalley 2015).The physical components of a CPS are responsible to convert physical quantities from one form to other and interact with the cyber world for analog/digital signal transfers. The cyber-world, on the other hand, consists of embedded computational devices that process information and communication in a virtual environment. This world is often referred to as the computational core. The interfaces are interactions that are defined as a bridge between the cyber world and the physical world.CPS consists of two interfaces -physical interfaces and cyber interfaces (Fromel 2016).The sensors and the actuators are physical devices that perform physical interfacing tasks.While the embedded computational devices interface at a cyber level with the exchange of information. These physical and cyber interactions are fundamental characteristics in a

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“…We also must consider additional features provided by each simulator, as these can be very convenient depending on the use case. For example, adevs supports using QEMU [229], Cadmium integrates a DEVS-based Real-Time (RT) kernel for embedded systems [230], and xDEVS provides tools for model unit testing [231].…”

Section: Improving the Performance Of Simulation Algorithms143mentioning

confidence: 99%

Integrative Modeling, Simulation, and Optimization Techniques for Efficient Data-Intensive Applications in Edge Computing Infrastructures

Cardenas Rodriguez

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The fusion of technologies that characterizes the Fourth Industrial Revolution (4IR) is blurring the boundaries between the physical and digital worlds. New solutions are increasingly complex and involve expertise in multiple domains. Thus, they are no longer considered stand-alone but as a System of Systems (SoS) comprising devices, users, and other supporting systems. The conception, design, and deployment of today's SoS require an exhaustive analysis of the scenario for succeeding. Modeling and Simulation-Based Systems Engineering (MSBSE) techniques are a variant of Systems Engineering (SE) that apply advanced Modeling and Simulation (M&S) procedures to ensure a logical, robust, and reliable incremental design, allowing us to assess the technical risks of the system while decreasing the operational and capital costs of the solution under development. However, these methods still present deficiencies that require further research to cover more use cases and achieve greater adoption in industry and academia. Using a monolithic computational model for describing the entire system usually incurs high simulation times. Usually, simulating a single scenario of a complex system takes considerably longer than the simulated time interval. Therefore, an in-depth exploration of all the possible hypotheses becomes unbearable. For that reason, we need to establish a new Modeling, Simulation, and Optimization (M&S&O) workflow for assisting in the conception, design, implementation, and operation phases of modern complex systems that tackle the problems presented above without compromising the robustness of the solution.

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Design and Implementation of A Building Control System in Real-Time Devs

Cited by 6 publications

References 12 publications

A Robust Discrete Event Method for the Design of Cyber-Physical Systems

A Robust Discrete Event Method for the Design of Cyber-Physical Systems

Formalization of Cyber-Physical System Interface using Discrete Event System Specifications

Integrative Modeling, Simulation, and Optimization Techniques for Efficient Data-Intensive Applications in Edge Computing Infrastructures

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