Iterative Learning Stabilization and Fault-Tolerant Control for Batch Processes - Limin Wang, Ridong Zhang, Furong Gao

Iterative Learning Stabilization and Fault-Tolerant Control for Batch Processes (eBook)

eBook Download: PDF
2019 | 1st ed. 2020
X, 323 Seiten
Springer Singapore (Verlag)
978-981-13-5790-9 (ISBN)
Systemvoraussetzungen
96,29 inkl. MwSt
  • Download sofort lieferbar
  • Zahlungsarten anzeigen
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.



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.


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.

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.

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.

Erscheint lt. Verlag 18.3.2019
Zusatzinfo X, 323 p. 66 illus., 58 illus. in color.
Verlagsort Singapore
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Netzwerke
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Mathematik Analysis
Mathematik / Informatik Mathematik Angewandte Mathematik
Mathematik / Informatik Mathematik Finanz- / Wirtschaftsmathematik
Naturwissenschaften
Technik Elektrotechnik / Energietechnik
Technik Nachrichtentechnik
Schlagworte 2D T-S Fuzzy Model Control • Average-dwell-time methods • Batch Processes • Batch process optimization • Fault-tolerant Control • Iterative Learning Stabilization • Time-varying Delays • Two-dimensional control
ISBN-10 981-13-5790-0 / 9811357900
ISBN-13 978-981-13-5790-9 / 9789811357909
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)
Größe: 5,9 MB

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich
der Praxis-Guide für Künstliche Intelligenz in Unternehmen - Chancen …

von Thomas R. Köhler; Julia Finkeissen

eBook Download (2024)
Campus Verlag
38,99
Wie du KI richtig nutzt - schreiben, recherchieren, Bilder erstellen, …

von Rainer Hattenhauer

eBook Download (2023)
Rheinwerk Computing (Verlag)
24,90