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  • Format: PDF

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
…mehr

Produktbeschreibung
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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Autorenporträt
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.