Reinforcement Learning for Optimal Feedback Control / Communications and Control Engineering (PDF)
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To yield an approximate optimal controller, the authors focus on theories and methods that fall under the umbrella of actor-critic methods for machine learning. They concentrate on establishing stability during the learning phase and the execution phase, and adaptive model-based and data-driven reinforcement learning, to assist readers in the learning process, which typically relies on instantaneous input-output measurements.
This monograph provides academic researchers with backgrounds in diverse disciplines from aerospace engineering to computer science, who are interested in optimal reinforcement learning functional analysis and functional approximation theory, with a good introduction to the use of model-based methods. The thorough treatment of an advanced treatment to control will also interest practitioners working in the chemical-process and power-supply industry.
Dr. Joel Rosenfeld is a postdoctoral researcher in the Department of Electrical Engineering and Computer Science at Vanderbilt University in the VeriVital Laboratory. He received his PhD in Mathematics at the University of Florida in 2013 under the direction of Dr. Michael T. Jury. His doctoral work concerned densely defined operators over reproducing kernel Hilbert spaces (RKHS), where he established characterizations of densely defined multiplication operators for several RKHSs. Dr. Rosenfeld then spent four years as a postdoctoral researcher in the Nonlinear Controls and Robotics Laboratory under Dr. Warren E. Dixon where he worked on problems in Numerical Analysis and Optimal Control Theory. Working together with Dr. Dixon and Dr. Kamalapurkar, he developed the numerical approach represented by the state following (StaF) method, which enables the implementation of online optimal control methods that were previously intractable.
Prof. Warren Dixon received his Ph.D. in 2000 from the Department of Electrical and Computer
- Autoren: Rushikesh Kamalapurkar , Patrick Walters , Joel Rosenfeld , Warren Dixon
- 2018, 1st ed. 2018, 293 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 331978384X
- ISBN-13: 9783319783840
- Erscheinungsdatum: 10.05.2018
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- Dateiformat: PDF
- Grösse: 15 MB
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