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Dynamic and hybrid architecture for the optimal reconfiguration of control systems : application to manufacturing control

Abstract : Discrete-event control systems have the opportunity to resolve significant challenges of modern society. In particular, these represent a fundamental solution to manage and control the new technological advances in compliance to the increased consciousness of sustainable development. The parameterization, configuration and decision-making of these control systems are critical aspects that impact the performance and productivity required. Dynamic control architecture approaches, such as reconfigurable control systems, have been proposed for modelling such systems. However, such approaches have failed to address the recovery of the reconfiguration process as these focus on the continuity of execution rather than on the optimisation of the reconfiguration. This dissertation proposes a reference architecture for a reconfigurable control system, named Pollux, designed to manage and adjust optimally and in real time the architecture of a control system, either to guide operational execution or to respond to a system perturbation. Considering a proposed framework of an optimal configuration of control architectures based on shared governance, this proposed approach aims to orchestrate a flexible and customizable decisional entity, a representation that characterize the unique configuration and control solution of the control architecture, and a three-module reconfiguration mechanism that integrates the optimality-based principles into the reconfiguration process, to ensure a recovery of global performance and/or minimise the degradation caused by perturbations. Our approach is applied in the manufacturing domain and is validated in a simulation and a real flexible manufacturing system cell located at the University of Valenciennes, France. The validation conducted in three experimental scenarios verified the benefits of our approach and encourage us to continue research in this direction.
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Submitted on : Wednesday, December 20, 2017 - 10:27:26 AM
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Jose-Fernando Jiménez. Dynamic and hybrid architecture for the optimal reconfiguration of control systems : application to manufacturing control. Artificial Intelligence [cs.AI]. Université de Valenciennes et du Hainaut-Cambresis, 2017. English. ⟨NNT : 2017VALE0031⟩. ⟨tel-01668578⟩

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