Authors:
Jukka Kortela
1
;
Yared Tadesse
2
and
Kim Miikki
2
Affiliations:
1
Aalto University School of Chemical Engineering, P.O. Box 16100, FI-00076 Aalto, Espoo, Finland
;
2
Bellmer Finland Oy, Vanha Messiläntie 6, 15860 Hollola, Finland
Keyword(s):
Cyber Physical System, Industrial Internet of Things, Rami, Iira, Model Predictive Control, Three Tank System, Model, Experiment, Fault Detection, Fault Diagnosis, Parity Equations.
Abstract:
This paper presents the model predictive control and fault detection and diagnosis system of a three-tank pilot within a novel cloud-integrated industrial automation framework. The system architecture includes a state-of-the-art NodeJS-based gateway facilitating communication between the cloud service and the automation system. OPC DA has not been updated to function with the latest programming libraries and operating systems, which significantly reduces the performance of automation systems. The optimized signal path through the OPC DA is developed and compared to the OPC UA tunneller implementation through experiments on a real three-tank pilot system with an industrial ABB 800xA automation system. The results demonstrate that the optimized signal path significantly reduces the control interval by a factor of 5, leading to a quicker controller response. In fault detection and diagnosis, the delay is only 22 milliseconds with an optimized signal path compared to 408 milliseconds whe
n using OPC UA tunneler software.
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