Black-box identification algorithms process an input/output sequence recorded for a long period of time during the functioning of a closed-loop controlled system and return a model of the system. However, even if these models simulate well the recorded sequence, they are not very accurate. The method proposed here aims to make more accurate these models by discovering the observable behaviour of a controlled system and the timed relationships between inputs and outputs.
Identification of timed input/output relationships for industrial automation systems using timed interpreted petri nets
Basile F.
;
2019
Abstract
Black-box identification algorithms process an input/output sequence recorded for a long period of time during the functioning of a closed-loop controlled system and return a model of the system. However, even if these models simulate well the recorded sequence, they are not very accurate. The method proposed here aims to make more accurate these models by discovering the observable behaviour of a controlled system and the timed relationships between inputs and outputs.File in questo prodotto:
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