Output Feedback Reinforcement Learning Con...

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Beschreibung

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.

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.

Inhaltsverzeichnis

Preface.- Introduction to Optimal Control and Reinforcement Learning.- Model-Free Design of Linear Quadratic Regulator.- Model-Free H-infinity Disturbance Rejection and Linear Quadratic Zero-Sum Games.- Model-Free Stabilization in the Presence of Actuator Saturation.- Model-Free Control of Time Delay Systems.- Model-Free Optimal Tracking Control and Multi-Agent Synchronization.- Index.

Details

Erscheinungsjahr:	2023
Fachbereich:	Allgemeines
Genre:	Mathematik , Medizin , Naturwissenschaften , Technik
Rubrik:	Naturwissenschaften & Technik
Medium:	Taschenbuch
Reihe:	Control Engineering
Inhalt:	xvi 294 S.
ISBN-13:	9783031158605
ISBN-10:	3031158601
Sprache:	Englisch
Einband:	Kartoniert / Broschiert
Autor:	Rizvi, Syed Ali Asad Lin, Zongli
Hersteller:	Birkhäuser Control Engineering
Verantwortliche Person für die EU:	Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, D-14197 Berlin, juergen.hartmann@springer.com
Maße:	235 x 155 x 17 mm
Von/Mit:	Syed Ali Asad Rizvi (u. a.)
Erscheinungsdatum:	14.12.2023
Gewicht:	0,476 kg