Overview
- Investigates optimal control problems subject to uncertain dynamic systems
- Focuses not only on the expected value-based model but also on the optimistic value-based model, which is a novel approach for optimal control theory
- Shows applications of uncertain optimal control in portfolio selection, engineering, and games
Part of the book series: Springer Uncertainty Research (SUR)
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Table of contents (9 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book introduces the theory and applications of uncertain optimal control, and establishes two types of models including expected value uncertain optimal control and optimistic value uncertain optimal control. These models, which have continuous-time forms and discrete-time forms, make use of dynamic programming. The uncertain optimal control theory relates to equations of optimality, uncertain bang-bang optimal control, optimal control with switched uncertain system, and optimal control for uncertain system with time-delay. Uncertain optimal control has applications in portfolio selection, engineering, and games.
The book is a useful resource for researchers, engineers, and students in the fields of mathematics, cybernetics, operations research, industrial engineering, artificial intelligence, economics, and management science.
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Authors and Affiliations
About the author
Yuanguo Zhu received his B.S. degree in 1984 and M.S. degree in 1988, both from Jiangxi Normal University, and his Ph.D. degree in 2004 from Tsinghua University. He joined Nanjing University of Science and Technology as a Professor of Mathematics in 2001. Dr. Zhu’s research includes optimization, optimal control, uncertainty, and intelligent computing.
Bibliographic Information
Book Title: Uncertain Optimal Control
Authors: Yuanguo Zhu
Series Title: Springer Uncertainty Research
DOI: https://doi.org/10.1007/978-981-13-2134-4
Publisher: Springer Singapore
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2019
Hardcover ISBN: 978-981-13-2133-7Published: 18 September 2018
Softcover ISBN: 978-981-13-4737-5Published: 16 December 2018
eBook ISBN: 978-981-13-2134-4Published: 29 August 2018
Series ISSN: 2199-3807
Series E-ISSN: 2199-3815
Edition Number: 1
Number of Pages: IX, 208
Number of Illustrations: 8 b/w illustrations, 8 illustrations in colour
Topics: Computational Intelligence, Optimization, Control, Robotics, Mechatronics, Artificial Intelligence, Operations Research/Decision Theory