Co-modelling and co-simulation in the engineering of systems of cyber-physical systems

Fitzgerald, JS; Pierce, Ken; Larsen, Peter Gorm

doi:10.1109/sysose.2014.6892465

Cited by 16 publications

(7 citation statements)

References 22 publications

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“…From a purely modeling point of view, the term co-modeling may also be appropriate to describe model coupling or co-simulation. However, this term is used more in the area of embedded systems [19], specifically hardware/software co-design, although it can sometimes also be found in connection with Cyber-Physical System (CPS) [42,101].…”

Section: Related Workmentioning

confidence: 99%

Methods for Hybrid Modeling and Simulation-Based Optimization in Energy-Aware Production Planning

Heinzl¹

2020

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Production Planning (PPC) optimization in the operation of industrial production plants enables to achieve energy savings and improve energy efficiency. To provide decision support in production planning, simulation-based methods are particularly well-suited for complex production system to assess different planning scenarios and evaluate them with regard to their energy demand. To this end, a hybrid discrete/continuous modeling approach based on the Discrete-Event System Specification (DEVS) is investigated in this thesis. Hybrid modeling allows to accurately capture material flows as discrete entities on one hand and continuous energy flows on the other hand, in the production as well as for other domains, such as heating or cooling, up to the thermal building envelope, including their dynamic interactions. A meta-heuristic optimization procedure for operative production planning evaluates energy efficiency together with other production goals (delivery tardiness, storage costs, etc.) as part of a multi-objective optimization. The procedure follows a hybrid Variable Neighborhood Search (VNS) meta-heuristic and uses the hybrid simulation for the energetic evaluation of production programs. The VNS uses special energy-related operators, for example to optimize the setup times of heating ovens, in order to save energy. Furthermore, to support the modeling process of such DEVS-based simulations in practical applications, a domain-specific model abstraction is designed, which allows to describe hybrid simulation models in an intuitive way. The method is based on a Model-Driven Engineering (MDE) process and defines a component-based meta-model for production systems. Concrete implementations can be derived from the abstract specification by means of model transformations. Proof-of-concept implementations are realized to evaluate the individual contributions and case studies from industry demonstrate the practical applicability. The hybrid simulation approach was implemented in its entirety as a simulator prototype, together with reusable model components, which can be used by practitioners to design new application models with reduced efforts. Altogether, these methods contribute to the integration of energy efficiency aspects into modern PPC systems and to increase energy efficiency in production. i Kurzfassung Im operativen Betrieb von industriellen Anlagen lassen sich durch optimierte Produktionsplanung und-steuerung (PPS) gezielt Energieeinsparungen erreichen und die Energieeffizienz verbessern. Zur Entscheidungsunterstützung bieten sich gerade bei komplexen Produktionssystemen simulationsbasierte Methoden an, die es ermöglichen, unterschiedliche Planungsszenarien zu vergleichen und hinsichtlich ihres Energieeinsatzes zu bewerten. Dafür wird in der vorliegenden Arbeit ein hybrider diskret/kontinuierlicher Modellierungsansatz untersucht, der auf der Discrete-Event System Specification (DEVS) basiert. Die hybride Modellierung erlaubt es einerseits die Materialflüsse als diskrete Entitäten, andererseits auch die zei...

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Section: Related Workmentioning

confidence: 99%

Methods for Hybrid Modeling and Simulation-Based Optimization in Energy-Aware Production Planning

Heinzl¹

2020

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“…As a similar approach, Crescendo tools are provided by DESTECS project [30]. The project also presents synchronization mechanism, called co-models, between software and plant models [31]. However, the co-models do not support the limitation of the verification time because the project focuses on the simulation.…”

Section: Related Workmentioning

confidence: 99%

Safety Verification Utilizing Model-based Development for Safety Critical Cyber-Physical Systems

Ishigooka

Saissi

Piper

et al. 2017

Journal of Information Processing

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Abstract:The application of cyber-physical systems (CPSs) in safety-critical application domain requires rigorous verification of their functional correctness and safety-relevant properties. We propose a practical verification process which enables to conduct safety verification of safety critical CPSs. The verification process consists of (a) a system model construction method, which generates a system model by combining software described in C and plant model code reused from model-based development, (b) a model transformation method, which transforms the plant models including differential algebraic equations (DAE) to approximate models without DAE to reduce verification complexity induced by DAE solver execution, (c) a model simplification framework, which enables the simplification of bond-graph plant models using domain-knowledge-based replacement of complex model components for further verification overhead reductions, and (d) a formal verification based on symbolic execution. We implemented the proposed methods and framework, and successfully applied the proposed verification process for safety verification of automotive brake control systems. The results of the study demonstrate that the verification detects a complex failure condition in a real-world brake control system from the generated system model and that the automated model transformations of the CPS models yield significant verification complexity reductions without impairing the ability to detect unsafe behavior.

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“…In the last years, cosimulation has become a powerful tool for the development of mechatronic systems [20][21][22]. It consists in application of specialized software packages that allow the use of more sophisticated models or virtual prototypes as mentioned in Ref.…”

Section: Introductionmentioning

confidence: 99%

Co-Simulation and Control of a Single-Wheel Pendulum Mobile Robot

Herrera-Cordero

Arias-Montiel

Ceccarelli

et al. 2021

Journal of Mechanisms and Robotics

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Co-simulation is widely used as a powerful tool for performance evaluation of systems design. This approach presents advantages over traditional design methodologies for saving money and time in the development process and the possibility of evaluating rapidly design alternatives by using virtual prototypes. This article presents an ADAMS/Matlab co-simulation for the dynamics and control of a Single-Wheel pendulum ROBot (SWROB) with inertial locomotion actuation to characterize design solutions by means of validation of analytical results. The obtained results by the proposed co-simulation show a significant performance based on the analytical and programming efforts in characterizing and simulating the designed system model. Moreover, open-loop experimental results are presented to validate both the analytical model and the virtual prototype.

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Co-modelling and co-simulation in the engineering of systems of cyber-physical systems

Cited by 16 publications

References 22 publications

Methods for Hybrid Modeling and Simulation-Based Optimization in Energy-Aware Production Planning

Methods for Hybrid Modeling and Simulation-Based Optimization in Energy-Aware Production Planning

Safety Verification Utilizing Model-based Development for Safety Critical Cyber-Physical Systems

Co-Simulation and Control of a Single-Wheel Pendulum Mobile Robot

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