Robust And Adaptive Control
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Author |
: Eugene Lavretsky |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 506 |
Release |
: 2012-11-13 |
ISBN-10 |
: 9781447143963 |
ISBN-13 |
: 1447143965 |
Rating |
: 4/5 (63 Downloads) |
Synopsis Robust and Adaptive Control by : Eugene Lavretsky
Robust and Adaptive Control shows the reader how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications the focus of the book is primarily on continuous-dynamical systems. The text is a three-part treatment, beginning with robust and optimal linear control methods and moving on to a self-contained presentation of the design and analysis of model reference adaptive control (MRAC) for nonlinear uncertain dynamical systems. Recent extensions and modifications to MRAC design are included, as are guidelines for combining robust optimal and MRAC controllers. Features of the text include: · case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; · detailed background material for each chapter to motivate theoretical developments; · realistic examples and simulation data illustrating key features of the methods described; and · problem solutions for instructors and MATLAB® code provided electronically. The theoretical content and practical applications reported address real-life aerospace problems, being based on numerous transitions of control-theoretic results into operational systems and airborne vehicles that are drawn from the authors’ extensive professional experience with The Boeing Company. The systems covered are challenging, often open-loop unstable, with uncertainties in their dynamics, and thus requiring both persistently reliable control and the ability to track commands either from a pilot or a guidance computer. Readers are assumed to have a basic understanding of root locus, Bode diagrams, and Nyquist plots, as well as linear algebra, ordinary differential equations, and the use of state-space methods in analysis and modeling of dynamical systems. Robust and Adaptive Control is intended to methodically teach senior undergraduate and graduate students how to construct stable and predictable control algorithms for realistic industrial applications. Practicing engineers and academic researchers will also find the book of great instructional value.
Author |
: Petros Ioannou |
Publisher |
: Courier Corporation |
Total Pages |
: 850 |
Release |
: 2013-09-26 |
ISBN-10 |
: 9780486320724 |
ISBN-13 |
: 0486320723 |
Rating |
: 4/5 (24 Downloads) |
Synopsis Robust Adaptive Control by : Petros Ioannou
Presented in a tutorial style, this comprehensive treatment unifies, simplifies, and explains most of the techniques for designing and analyzing adaptive control systems. Numerous examples clarify procedures and methods. 1995 edition.
Author |
: Shankar Sastry |
Publisher |
: Courier Corporation |
Total Pages |
: 402 |
Release |
: 2011-01-01 |
ISBN-10 |
: 9780486482026 |
ISBN-13 |
: 0486482022 |
Rating |
: 4/5 (26 Downloads) |
Synopsis Adaptive Control by : Shankar Sastry
This volume surveys the major results and techniques of analysis in the field of adaptive control. Focusing on linear, continuous time, single-input, single-output systems, the authors offer a clear, conceptual presentation of adaptive methods, enabling a critical evaluation of these techniques and suggesting avenues of further development. 1989 edition.
Author |
: Alessandro Astolfi |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 302 |
Release |
: 2007-12-06 |
ISBN-10 |
: 9781848000667 |
ISBN-13 |
: 1848000669 |
Rating |
: 4/5 (67 Downloads) |
Synopsis Nonlinear and Adaptive Control with Applications by : Alessandro Astolfi
The authors here provide a detailed treatment of the design of robust adaptive controllers for nonlinear systems with uncertainties. They employ a new tool based on the ideas of system immersion and manifold invariance. New algorithms are delivered for the construction of robust asymptotically-stabilizing and adaptive control laws for nonlinear systems. The methods proposed lead to modular schemes that are easier to tune than their counterparts obtained from Lyapunov redesign.
Author |
: Uwe Mackenroth |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 524 |
Release |
: 2013-04-17 |
ISBN-10 |
: 9783662097755 |
ISBN-13 |
: 3662097753 |
Rating |
: 4/5 (55 Downloads) |
Synopsis Robust Control Systems by : Uwe Mackenroth
Self-contained introduction to control theory that emphasizes on the most modern designs for high performance and robustness. It assumes no previous coursework and offers three chapters of key topics summarizing classical control. To provide readers with a deeper understanding of robust control theory than would be otherwise possible, the text incorporates mathematical derivations and proofs. Includes many elementary examples and advanced case studies using MATLAB Toolboxes.
Author |
: Spandan Roy |
Publisher |
: Springer |
Total Pages |
: 0 |
Release |
: 2019-10-18 |
ISBN-10 |
: 9811506396 |
ISBN-13 |
: 9789811506390 |
Rating |
: 4/5 (96 Downloads) |
Synopsis Adaptive-Robust Control with Limited Knowledge on Systems Dynamics by : Spandan Roy
The book investigates the role of artificial input delay in approximating unknown system dynamics, referred to as time-delayed control (TDC), and provides novel solutions to current design issues in TDC. Its central focus is on designing adaptive-switching gain-based robust control (ARC) for a class of Euler–Lagrange (EL) systems with minimal or no knowledge of the system dynamics parameters. The newly proposed TDC-based ARC tackles the commonly observed over- and under-estimation issues in switching gain. The consideration of EL systems lends a practical perspective on the proposed methods, and each chapter is supplemented by relevant experimental data. The book offers a unique resource for researchers in the areas of ARC and TDC alike, and covers the state of the art, new algorithms, and future directions.
Author |
: Naira Hovakimyan |
Publisher |
: SIAM |
Total Pages |
: 333 |
Release |
: 2010-09-30 |
ISBN-10 |
: 9780898717044 |
ISBN-13 |
: 0898717043 |
Rating |
: 4/5 (44 Downloads) |
Synopsis L1 Adaptive Control Theory by : Naira Hovakimyan
Contains results not yet published in technical journals and conference proceedings.
Author |
: Karl J. Åström |
Publisher |
: Courier Corporation |
Total Pages |
: 596 |
Release |
: 2013-04-26 |
ISBN-10 |
: 9780486319148 |
ISBN-13 |
: 0486319148 |
Rating |
: 4/5 (48 Downloads) |
Synopsis Adaptive Control by : Karl J. Åström
Suitable for advanced undergraduates and graduate students, this overview introduces theoretical and practical aspects of adaptive control, with emphasis on deterministic and stochastic viewpoints. 1995 edition.
Author |
: Alexander Weinmann |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 699 |
Release |
: 2012-12-06 |
ISBN-10 |
: 9783709167113 |
ISBN-13 |
: 3709167116 |
Rating |
: 4/5 (13 Downloads) |
Synopsis Uncertain Models and Robust Control by : Alexander Weinmann
This coherent introduction to the theory and methods of robust control system design clarifies and unifies the presentation of significant derivations and proofs. The book contains a thorough treatment of important material of uncertainties and robust control otherwise scattered throughout the literature.
Author |
: Aniruddha Datta |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 166 |
Release |
: 2012-12-06 |
ISBN-10 |
: 9780857293312 |
ISBN-13 |
: 0857293311 |
Rating |
: 4/5 (12 Downloads) |
Synopsis Adaptive Internal Model Control by : Aniruddha Datta
Written in a self-contained tutorial fashion, this monograph successfully brings the latest theoretical advances in the design of robust adaptive systems to the realm of industrial applications. It provides a theoretical basis for verifying some of the reported industrial successes of existing adaptive control schemes and enables readers to synthesize adaptive versions of their own robust internal model control schemes.