Robust Engineering Designs of Partial Differential Systems and Their Applications
Language: English
Published by CRC Press, 2024
- Softcover
- New
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- Title
- Robust Engineering Designs of Partial Differential Systems and Their Applications
- Author
- Bor-Sen Chen
- Publisher
- CRC Press
- Publication year
- 2024
- Condition
- New
- Binding
- PAP
- Language
- English
- ISBN 10
- 1032134453
- ISBN 13
- 9781032134451
- Item weight
- 707 grams
Most systems in science, engineering, and biology are of partial differential systems (PDSs) modeled by partial differential equations. Many books about partial differential equations have been written by mathematicians and mainly address some fundamental mathematic backgrounds and discuss some mathematic properties of partial differential equations. Only a few books on PDSs have been written by engineers; however, these books have focused mainly on the theoretical stabilization analysis of PDSs, especially mechanical systems. This book investigates both robust stabilization control design and robust filter design and reference tracking control design in mechanical, signal processing, and control systems to fill a gap in the study of PDSs.
Robust Engineering Designs of Partial Differential Systems and Their Applications offers some fundamental background in the first two chapters. The rest of the chapters focus on a specific design topic with a corresponding deep investigation into robust H∞ filtering, stabilization, or tracking design for more complex and practical PDSs under stochastic fluctuation and external disturbance.
This book is aimed at engineers and scientists and addresses the gap between the theoretical stabilization results of PDSs in academic and practical engineering designs more focused on the robust H∞ filtering, stabilization, and tracking control problems of linear and nonlinear PDSs under intrinsic random fluctuation and external disturbance in industrial applications.
Part I provides backgrounds on PDSs, such as Galerkin’s, and finite difference methods to approximate PDSs and a fuzzy method to approximate nonlinear PDSs. Part II examines robust H∞ filter designs for the robust state estimation of linear and nonlinear stochastic PDSs. And Part III treats robust H∞ stabilization and tracking control designs of linear and nonlinear PDSs. Every chapter focuses on an engineering design topic with both theoretical design analysis and practical design examples.
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About the Author
Dr. Bor-Sen Chen received B.S. degree in electrical engineering from Tatung Institute of Technology, Taipei, Taiwan, in 1970, and M.S. degree of geophysics from the National Central University, Chungli, Taiwan in 1973, and Ph.D degree from University of Southern California, Los Angeles, CA, USA, in 1973. From 1973 to 1987, he had been a lecturer, associate professor, and professor of Tatung Institute of Technology. From 1987, he has been a professor, chair professor and Tsing Hua distinguished chair professor with the Department of Electrical Engineering of National Tsing Hua University, Hsinchu, Taiwan. His research interests include robust control theory and engineering design, robust signal processing and communication system design, and systems biology. He has published more than 300 journal papers, including 130 papers in control, 70 papers in signal processing and communication, and 100 papers in systems biology. He has also published 10 monographs. He was the recipient of numerous awards for his academic accomplishments in robust control, fuzzy control, H∞ control, stochastic control, signal processing and systems biology, including 4 Outstanding Research Awards of National Science Council, Academic Award in Engineering from Ministry of Education, National Chair Professor of the Ministry of Education, Best Impact Award of IEEE Taiwan Section for his most SCI citations of IEEE members in Taiwan, etc. His current research interest focuses on the H∞ team formation network tracking control of large-scale UAVs, large-scale biped robots and their team cooperation, deep neural network (DNN)-based control design of nonlinear dynamic systems, systems medicine design based on design specifications and deep learning schemes, etc. He is a life fellow of IEEE.
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