Design patterns: elements of reusable object-oriented software
Design patterns: elements of reusable object-oriented software
Doing hard time: developing real-time systems with UML, objects, frameworks, and patterns
Doing hard time: developing real-time systems with UML, objects, frameworks, and patterns
An experimental benchmarking of two multi-agent architectures for production scheduling and control
Computers in Industry - Special issue on intelligent manufacturing systems
The TINI Specification and Developer's Guide
The TINI Specification and Developer's Guide
Simulation with Arena
Real-Time Design Patterns: Robust Scalable Architecture for Real-Time Systems
Real-Time Design Patterns: Robust Scalable Architecture for Real-Time Systems
A proxy design pattern to support real-time distributed control system benchmarking
HoloMAS'05 Proceedings of the Second international conference on Holonic and Multi-Agent Systems for Manufacturing
Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Toward Real-Time Distributed Intelligent Control: A Survey of Research Themes and Applications
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
International Journal of Information and Communication Technology
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In this paper, we describe the design and development of a simulation-agent interface for real-time distributed control system benchmarking. This work is motivated by the need to test the feasibility of extending agent-based systems to the physical device level in manufacturing and other industrial automation systems. Our work focuses on the development of hybrid physical/simulation environment that can be used to perform tests at both the physical device level, as well as the planning and scheduling level of control. As part of this work, we have extended the proxy design pattern for this application. This paper focuses on the resulting software design pattern for distributed control system benchmarking and provides examples of its use in our hybrid physical/simulation environment.