Premium
A 3 M: an agent architecture for automated manufacturing
Author(s) -
Di Stefano Antonella,
Santoro Corrado
Publication year - 2009
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.894
Subject(s) - control reconfiguration , heuristics , computer science , distributed computing , process (computing) , field (mathematics) , task (project management) , computation , controller (irrigation) , embedded system , real time computing , engineering , algorithm , operating system , agronomy , mathematics , systems engineering , pure mathematics , biology
This paper proposes a software architecture based on mobile agents for distributed process control applications. A set of agents is employed to handle, in a single manufacturing cell, automatic assignment of control tasks to controllers, monitoring of cell functionalities and dynamic cell reconfiguration. The agents operate in a two‐layered structure: at the highest level, the planning agents analyse the inputs of the system designer and automatically create the field agents , which operate at the lowest level and embed the control tasks to be executed. Field agents, which are mobile, are able to reach autonomously the controllers of the cell, in order to perform the control activity there. Exploiting the mobility enables a field agent to change its running device when the variation of the design parameters or a system fault requires a new task distribution. A load‐balancing algorithm is introduced, with the objective of assigning each field agent to a controller of the manufacturing cell in order to fairly distribute the computation load. The algorithm uses a branch‐and‐bound technique to explore all possible solutions and applies two heuristics to throw away non‐feasible solutions and select the best branch to analyse. The algorithm is designed to run on‐line in order to allow a fast task redistribution when a fault condition occurs in the process control environment. Copyright © 2008 John Wiley & Sons, Ltd.