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Novel methodology for obtaining design structure matrices using network identification

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Design structure matrices (DSMs) are used to comprehensively represent complex systems. They visualize and describe the dependencies between various variables, processes, states, and events. As such they are used in several system engineering approaches, such as requirement and interface management, fault detection, and supervisory control. Currently, a DSM is typically built from knowledge of experts. This may lead to an incomplete or imbalanced DSMs. For instance, elements and links might be missing or superfluous. In this article, we propose a novel method to acquire the DSM using state-of-the-art network identification methods. This demonstrates a proof-of-principle of identifying DSMs from data as an additional tool to the standard heuristic approach. In the future, we plan to embed DSMs in system design and supervisory controllers. We apply this technique to identify the DSM of a fusion reactor modelled by a five-chamber plasma model describing the transport in a tokamak.

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