Iterative Learning Stabilization and Fault-Tolerant Control for Batch Processes

Nonfiction, Science & Nature, Technology, Automation, Computers, Advanced Computing, Artificial Intelligence
Cover of the book Iterative Learning Stabilization and Fault-Tolerant Control for Batch Processes by Limin Wang, Ridong Zhang, Furong Gao, Springer Singapore
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Author: Limin Wang, Ridong Zhang, Furong Gao ISBN: 9789811357909
Publisher: Springer Singapore Publication: March 14, 2019
Imprint: Springer Language: English
Author: Limin Wang, Ridong Zhang, Furong Gao
ISBN: 9789811357909
Publisher: Springer Singapore
Publication: March 14, 2019
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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