Iterative Learning Stabilization and Fault-Tolerant Control for Batch Processes

1. Auflage 2020
ISBN: 978-981-13-5789-3
Verlag: Springer Nature Singapore

Buch, Englisch, 323 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 670 g

This book is based on the authors’ research on the stabilization and fault-tolerant control of batch processes, which are flourishing topics in the field of control system engineering. It introduces iterative learning control for linear/nonlinear single/multi-phase batch processes; iterative learning optimal guaranteed cost control; delay-dependent iterative learning control; and iterative learning fault-tolerant control for linear/nonlinear single/multi-phase batch processes. Providing important insights and useful methods and practical algorithms that can potentially be applied in batch process control and optimization, it is a valuable resource for researchers, scientists, and engineers in the field of process system engineering and control engineering.

Zielgruppe

Research

Autoren/Hrsg.

Wang, Limin

Gao, Furong

Zhang, Ridong

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Introduction.- Iterative learning control of linear batch processes.- Iterative learning control of nonlinear batch processes.- Iterative learning optimal guaranteed cost control of batch processes.- Iterative learning control of multi-phase batch processes.- Delay-dependent iterative learning control of multi-phase batch processes.- Iterative learning fault-tolerant control of linear batch processes.- Iterative learning fault-tolerant control of nonlinear batch processes.- Iterative learning fault-tolerant control of multi-phase batch processes.- Further ideas on constrained infinite horizon fault-tolerant control of batch processes.

Über Autor(innen)

Limin Wang is currently a professor at the School of Mathematics and Statistics, Hainan Normal University. She is a member of the Fault Diagnosis and Safety Professional Committee of the China Association of Automation. She received her Ph.D. degree in Operations Research and Cybernetics from Dalian University of Technology in 2009. Her current research interests include batch process control, fault-tolerant control and fault diagnosis. She worked as a postdoctoral fellow at the Hong Kong University of Science and Technology, Zhejiang University, and Tsinghua University, researching on advanced control methods, fault diagnosis and fault tolerant control of batch processes and published a series of original results in international journals, such as the Journal of Process Control, AIChE Journal, Industrial & Engineering Chemistry Research, and Control Engineering Practice.

Ridong Zhang received his Ph.D. degree in control science and engineering from Zhejiang University in 2007. From 2007 to 2015, he was a professor at the Institute of Information and Control, Hangzhou Dianzi University. Since 2015, he has been a visiting professor at the Chemical and Biomolecular Engineering Department, the Hong Kong University of Science and Technology. He has published more than 40 journal papers in the fields of process modeling and control. His research interests include process modeling, model predictive control, and nonlinear systems.

Furong Gao received his B.Eng. degree in automation from the China University of Petroleum in 1985 and M. Eng. and Ph.D. degrees in chemical engineering from McGill University, Canada, in 1989 and 1993 respectively. He worked as a senior research engineer at Moldflow International Company Ltd. Since 1995, he has been working at the Hong Kong University of Science and Technology, where he is currently the chair professor in the Department of Chemical and Biomolecular Engineering. His research interests include process monitoring, control and polymer processing.