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Output Feedback Reinforcement Learning Control for Linear Systems

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Output Feedback Reinforcement Learning Control for Linear Systems

Zongli Lin, Syed Ali Asad Rizvi

Birkhäuser
Collection: Control Engineering
Publication date : 2022-11-29

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This monograph explores the analysis and design of model-free optimal control systems based on reinforcement learning (RL) theory, presenting new methods that overcome recent challenges faced by RL. New developments in the design of sensor data efficient RL algorithms are demonstrated that not only reduce the requirement of sensors by means of output feedback, but also ensure optimality and stability guarantees. A variety of practical challenges are considered, including disturbance rejection, control constraints, and communication delays. Ideas from game theory are incorporated to solve output feedback disturbance rejection problems, and the concepts of low gain feedback control are employed to develop RL controllers that achieve global stability under control constraints.

Output Feedback Reinforcement Learning Control for Linear Systems will be a valuable reference for graduate students, control theorists working on optimal control systems, engineers, and applied mathematicians.

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About the book

Author

Zongli Lin , Syed Ali Asad Rizvi

Imprint

Birkhäuser

Collection

Control Engineering

Publication date

2022-11-29

Pages

294 pages

Print ISBN

9783031158575

Language

English

Ebook informations

EAN PDF

9783031158582

Price

£129.50

Copy count 2

Print count 29

File size 6103 Ko

Informations accessibility

EAN EPUB

9783031158582

Price

£129.50

Copy count 2

Print count 29

File size 24996 Ko

Informations accessibility

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About author(s)

Zongli Lin

Syed Ali Asad Rizvi

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