Control Theory Tutorial
Control Theory Tutorial

Author: Steven A. Frank

Publisher: Springer

Published: 2018-05-29

Total Pages: 112

ISBN-13: 3319917072

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This open access Brief introduces the basic principles of control theory in a concise self-study guide. It complements the classic texts by emphasizing the simple conceptual unity of the subject. A novice can quickly see how and why the different parts fit together. The concepts build slowly and naturally one after another, until the reader soon has a view of the whole. Each concept is illustrated by detailed examples and graphics. The full software code for each example is available, providing the basis for experimenting with various assumptions, learning how to write programs for control analysis, and setting the stage for future research projects. The topics focus on robustness, design trade-offs, and optimality. Most of the book develops classical linear theory. The last part of the book considers robustness with respect to nonlinearity and explicitly nonlinear extensions, as well as advanced topics such as adaptive control and model predictive control. New students, as well as scientists from other backgrounds who want a concise and easy-to-grasp coverage of control theory, will benefit from the emphasis on concepts and broad understanding of the various approaches. Electronic codes for this title can be downloaded from https://extras.springer.com/?query=978-3-319-91707-8

Feedback Control of Computing Systems
Feedback Control of Computing Systems

Author: Joseph L. Hellerstein

Publisher: John Wiley & Sons

Published: 2004-09-21

Total Pages: 451

ISBN-13: 0471668818

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This is the first practical treatment of the design and application of feedback control of computing systems. MATLAB files for the solution of problems and case studies accompany the text throughout. The book discusses information technology examples, such as maximizing the efficiency of Lotus Notes. This book results from the authors' research into the use of control theory to model and control computing systems. This has important implications to the way engineers and researchers approach different resource management problems. This guide is well suited for professionals and researchers in information technology and computer science.

Control Theory for Humans
Control Theory for Humans

Author: Richard J. Jagacinski

Publisher: CRC Press

Published: 2018-10-08

Total Pages: 394

ISBN-13: 1410606767

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This textbook provides a tutorial introduction to behavioral applications of control theory. Control theory describes the information one should be sensitive to and the pattern of influence that one should exert on a dynamic system in order to achieve a goal. As such, it is applicable to various forms of dynamic behavior. The book primarily deals with manual control (e.g., moving the cursor on a computer screen, lifting an object, hitting a ball, driving a car), both as a substantive area of study and as a useful perspective for approaching control theory. It is the experience of the authors that by imagining themselves as part of a manual control system, students are better able to learn numerous concepts in this field. Topics include varieties of control theory, such as classical, optimal, fuzzy, adaptive, and learning control, as well as perception and decision making in dynamic contexts. The authors also discuss implications of control theory for how experiments can be conducted in the behavioral sciences. In each of these areas they have provided brief essays intended to convey key concepts that enable the reader to more easily pursue additional readings. Behavioral scientists teaching control courses will be very interested in this book.

Adaptive Control Tutorial
Adaptive Control Tutorial

Author: Petros Ioannou

Publisher: SIAM

Published: 2006-01-01

Total Pages: 401

ISBN-13: 0898716152

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Designed to meet the needs of a wide audience without sacrificing mathematical depth and rigor, Adaptive Control Tutorial presents the design, analysis, and application of a wide variety of algorithms that can be used to manage dynamical systems with unknown parameters. Its tutorial-style presentation of the fundamental techniques and algorithms in adaptive control make it suitable as a textbook. Adaptive Control Tutorial is designed to serve the needs of three distinct groups of readers: engineers and students interested in learning how to design, simulate, and implement parameter estimators and adaptive control schemes without having to fully understand the analytical and technical proofs; graduate students who, in addition to attaining the aforementioned objectives, also want to understand the analysis of simple schemes and get an idea of the steps involved in more complex proofs; and advanced students and researchers who want to study and understand the details of long and technical proofs with an eye toward pursuing research in adaptive control or related topics. The authors achieve these multiple objectives by enriching the book with examples demonstrating the design procedures and basic analysis steps and by detailing their proofs in both an appendix and electronically available supplementary material; online examples are also available. A solution manual for instructors can be obtained by contacting SIAM or the authors. Preface; Acknowledgements; List of Acronyms; Chapter 1: Introduction; Chapter 2: Parametric Models; Chapter 3: Parameter Identification: Continuous Time; Chapter 4: Parameter Identification: Discrete Time; Chapter 5: Continuous-Time Model Reference Adaptive Control; Chapter 6: Continuous-Time Adaptive Pole Placement Control; Chapter 7: Adaptive Control for Discrete-Time Systems; Chapter 8: Adaptive Control of Nonlinear Systems; Appendix; Bibliography; Index

Feedback Control Theory
Feedback Control Theory

Author: John C. Doyle

Publisher: Courier Corporation

Published: 2013-04-09

Total Pages: 264

ISBN-13: 0486318338

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An excellent introduction to feedback control system design, this book offers a theoretical approach that captures the essential issues and can be applied to a wide range of practical problems. Its explorations of recent developments in the field emphasize the relationship of new procedures to classical control theory, with a focus on single input and output systems that keeps concepts accessible to students with limited backgrounds. The text is geared toward a single-semester senior course or a graduate-level class for students of electrical engineering. The opening chapters constitute a basic treatment of feedback design. Topics include a detailed formulation of the control design program, the fundamental issue of performance/stability robustness tradeoff, and the graphical design technique of loopshaping. Subsequent chapters extend the discussion of the loopshaping technique and connect it with notions of optimality. Concluding chapters examine controller design via optimization, offering a mathematical approach that is useful for multivariable systems.

Designing Control Loops for Linear and Switching Power Supplies
Designing Control Loops for Linear and Switching Power Supplies

Author: Christophe P. Basso

Publisher: Artech House

Published: 2012

Total Pages: 614

ISBN-13: 1608075575

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Loop control is an essential area of electronics engineering that todays professionals need to master. Rather than delving into extensive theory, this practical book focuses on what you really need to know for compensating or stabilizing a given control system. You can turn instantly to practical sections with numerous design examples and ready-made formulas to help you with your projects in the field. You also find coverage of the underpinnings and principles of control loops so you can gain a more complete understanding of the material. This authoritative volume explains how to conduct analysis of control systems and provides extensive details on practical compensators. It helps you measure your system, showing how to verify if a prototype is stable and features enough design margin. Moreover, you learn how to secure high-volume production by bench-verified safety margins.

A Course in Robust Control Theory
A Course in Robust Control Theory

Author: Geir E. Dullerud

Publisher: Springer Science & Business Media

Published: 2013-03-14

Total Pages: 427

ISBN-13: 1475732902

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During the 90s robust control theory has seen major advances and achieved a new maturity, centered around the notion of convexity. The goal of this book is to give a graduate-level course on this theory that emphasizes these new developments, but at the same time conveys the main principles and ubiquitous tools at the heart of the subject. Its pedagogical objectives are to introduce a coherent and unified framework for studying the theory, to provide students with the control-theoretic background required to read and contribute to the research literature, and to present the main ideas and demonstrations of the major results. The book will be of value to mathematical researchers and computer scientists, graduate students planning to do research in the area, and engineering practitioners requiring advanced control techniques.

L1 Adaptive Control Theory
L1 Adaptive Control Theory

Author: Naira Hovakimyan

Publisher: SIAM

Published: 2010-09-30

Total Pages: 333

ISBN-13: 0898717043

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Contains results not yet published in technical journals and conference proceedings.

Learning-Based Control
Learning-Based Control

Author: Zhong-Ping Jiang

Publisher: Now Publishers

Published: 2020-12-07

Total Pages: 122

ISBN-13: 9781680837520

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The recent success of Reinforcement Learning and related methods can be attributed to several key factors. First, it is driven by reward signals obtained through the interaction with the environment. Second, it is closely related to the human learning behavior. Third, it has a solid mathematical foundation. Nonetheless, conventional Reinforcement Learning theory exhibits some shortcomings particularly in a continuous environment or in considering the stability and robustness of the controlled process. In this monograph, the authors build on Reinforcement Learning to present a learning-based approach for controlling dynamical systems from real-time data and review some major developments in this relatively young field. In doing so the authors develop a framework for learning-based control theory that shows how to learn directly suboptimal controllers from input-output data. There are three main challenges on the development of learning-based control. First, there is a need to generalize existing recursive methods. Second, as a fundamental difference between learning-based control and Reinforcement Learning, stability and robustness are important issues that must be addressed for the safety-critical engineering systems such as self-driving cars. Third, data efficiency of Reinforcement Learning algorithms need be addressed for safety-critical engineering systems. This monograph provides the reader with an accessible primer on a new direction in control theory still in its infancy, namely Learning-Based Control Theory, that is closely tied to the literature of safe Reinforcement Learning and Adaptive Dynamic Programming.