Plug-and-Play Monitoring and Performance Optimization for Industrial Automation Processes [electronic resource] /
By: Luo, Hao [author.].
Contributor(s): SpringerLink (Online service).
Publisher: Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Vieweg, 2017Edition: 1st ed. 2017.Description: XVII, 149 p. 67 illus., 49 illus. in color. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9783658159283.Subject(s): Mechanical Engineering
| Control, Robotics, Mechatronics | Industrial and Production EngineeringDDC classification: 629.8 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.)
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Springer Nature eBookSummary: Dr.-Ing. Hao Luo demonstrates the developments of advanced plug-and-play (PnP) process monitoring and control systems for industrial automation processes. With aid of the so-called Youla parameterization, a novel PnP process monitoring and control architecture (PnP-PMCA) with modularized components is proposed. To validate the developments, a case study on an industrial rolling mill benchmark is performed, and the real-time implementation on a laboratory brushless DC motor is presented. Contents PnP Process Monitoring and Control Architecture Real-Time Configuration Techniques for PnP Process Monitoring Real-Time Configuration Techniques for PnP Performance Optimization Benchmark Study and Real-Time Implementation Target Groups Researchers and students of Automation and Control Engineering Practitioners in the area of Industrial and Production Engineering The Author Hao Luo received the Ph.D. degree at the Institute for Automatic Control and Complex Systems (AKS) at the University of Duisburg-Essen, Germany, in 2016. His research interests include model-based and data-driven fault diagnosis, fault-tolerant systems and their industrial applications.
Dr.-Ing. Hao Luo demonstrates the developments of advanced plug-and-play (PnP) process monitoring and control systems for industrial automation processes. With aid of the so-called Youla parameterization, a novel PnP process monitoring and control architecture (PnP-PMCA) with modularized components is proposed. To validate the developments, a case study on an industrial rolling mill benchmark is performed, and the real-time implementation on a laboratory brushless DC motor is presented. Contents PnP Process Monitoring and Control Architecture Real-Time Configuration Techniques for PnP Process Monitoring Real-Time Configuration Techniques for PnP Performance Optimization Benchmark Study and Real-Time Implementation Target Groups Researchers and students of Automation and Control Engineering Practitioners in the area of Industrial and Production Engineering The Author Hao Luo received the Ph.D. degree at the Institute for Automatic Control and Complex Systems (AKS) at the University of Duisburg-Essen, Germany, in 2016. His research interests include model-based and data-driven fault diagnosis, fault-tolerant systems and their industrial applications.
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