Towards Hypermedia Environments for Adaptive Coordination in Industrial Automation
Ganesh Ramanathan, Simon Mayer, Andrei Ciortea

TL;DR
This paper proposes a hypermedia-driven, autonomous agent approach for adaptive, decentralized coordination in industrial automation systems, reducing coupling and enabling runtime adaptation based on semantic models.
Contribution
It introduces a novel hypermedia-based interaction method for autonomous agents to dynamically coordinate physical components in industrial automation.
Findings
Reduces system coupling through hypermedia-driven interactions.
Enables runtime adaptation to changing system features.
Demonstrates effective autonomous coordination in electromechanical systems.
Abstract
Electromechanical systems manage physical processes through a network of inter-connected components. Today, programming the interactions required for coordinating these components is largely a manual process. This process is time-consuming and requires manual adaptation when system features change. To overcome this issue, we use autonomous software agents that process semantic descriptions of the system to determine coordination requirements and constraints; on this basis, they then interact with one another to control the system in a decentralized and coordinated manner.Our core insight is that coordination requirements between individual components are, ultimately, largely due to underlying physical interdependencies between the components, which can be (and, in many cases, already are) semantically modeled in automation projects. Agents then use hypermedia to discover, at run time,…
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Taxonomy
TopicsBusiness Process Modeling and Analysis · Scheduling and Optimization Algorithms · Flexible and Reconfigurable Manufacturing Systems
