Adaptive Robust Control Systems

Adaptive Robust Control Systems

Author: Anh Tuan Le

Publisher: BoD – Books on Demand

Published: 2018-03-07

Total Pages: 364

ISBN-13: 9535137964

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This book focuses on the applications of robust and adaptive control approaches to practical systems. The proposed control systems hold two important features: (1) The system is robust with the variation in plant parameters and disturbances (2) The system adapts to parametric uncertainties even in the unknown plant structure by self-training and self-estimating the unknown factors. The various kinds of robust adaptive controls represented in this book are composed of sliding mode control, model-reference adaptive control, gain-scheduling, H-infinity, model-predictive control, fuzzy logic, neural networks, machine learning, and so on. The control objects are very abundant, from cranes, aircrafts, and wind turbines to automobile, medical and sport machines, combustion engines, and electrical machines.


Robust Adaptive Control

Robust Adaptive Control

Author: Petros Ioannou

Publisher: Courier Corporation

Published: 2013-09-26

Total Pages: 850

ISBN-13: 0486320723

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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.


Robust and Adaptive Control

Robust and Adaptive Control

Author: Eugene Lavretsky

Publisher: Springer Science & Business Media

Published: 2012-11-13

Total Pages: 506

ISBN-13: 1447143965

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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.


Adaptive-Robust Control with Limited Knowledge on Systems Dynamics

Adaptive-Robust Control with Limited Knowledge on Systems Dynamics

Author: Spandan Roy

Publisher: Springer

Published: 2019-10-18

Total Pages: 0

ISBN-13: 9789811506390

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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.


Robust Control Systems

Robust Control Systems

Author: Uwe Mackenroth

Publisher: Springer Science & Business Media

Published: 2013-04-17

Total Pages: 524

ISBN-13: 3662097753

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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.


Adaptive Robust Control Systems

Adaptive Robust Control Systems

Author: Le Anh Tuan

Publisher:

Published: 2018

Total Pages: 362

ISBN-13: 9789535140702

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This book focuses on the applications of robust and adaptive control approaches to practical systems. The proposed control systems hold two important features: (1) The system is robust with the variation in plant parameters and disturbances (2) The system adapts to parametric uncertainties even in the unknown plant structure by self-training and self-estimating the unknown factors. The various kinds of robust adaptive controls represented in this book are composed of sliding mode control, model-reference adaptive control, gain-scheduling, H-infinity, model-predictive control, fuzzy logic, neural networks, machine learning, and so on. The control objects are very abundant, from cranes, aircrafts, and wind turbines to automobile, medical and sport machines, combustion engines, and electrical machines.


Adaptive Control Systems

Adaptive Control Systems

Author: Gang Feng

Publisher: Newnes

Published: 1999-06-08

Total Pages: 360

ISBN-13: 9780750639965

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List of contributors; Preface; Adaptive internal model control; An algorithm for robust adaptive control with less prior knowledge; Adaptive variable structure control; Indirect adaptive periodic control; Adaptive stabilization of uncertain discrete-time systems via switching control: the method of localization; Adaptive nonlinear control: passivation and small gain techniques; Active identification for control of discrete-time uncertain nonlinear systems; Optimal adaptive tracking for nonlinear systems; Stable adaptive systems in the presence of nonlinear parametrization; Adaptive inverse for actuator compensation; Stable multi-input multi-output adaptive fuzzy/neural control; Adaptive robust control scheme with an application to PM synchronous motors; Index.


Adaptive Robust Control for Planar Snake Robots

Adaptive Robust Control for Planar Snake Robots

Author: Joyjit Mukherjee

Publisher: Springer Nature

Published: 2021-05-11

Total Pages: 179

ISBN-13: 3030714608

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This book shows how a conventional multi-layered approach can be used to control a snake robot on a desired path while moving on a flat surface. To achieve robustness to unknown variations in surface conditions, it explores various adaptive robust control methods. The authors propose a sliding-mode control approach designed to achieve robust maneuvering for bounded uncertainty with a known upper bound. The control is modified by addition of an adaptation law to alleviate the overestimation problem of the switching gain as well as to circumvent the requirement for knowledge regarding the bounds of uncertainty. The book works toward non-conservativeness, achieving efficient tracking in the presence of slowly varying uncertainties with a specially designed framework for time-delayed control. It shows readers how to extract superior performance from their snake robots with an approach that allows robustness toward bounded time-delayed estimation errors. The book also demonstrates how the multi-layered control framework can be simplified by employing differential flatness for such a system. Finally, the mathematical model of a snake robot moving inside a uniform channel using only side-wall contact is discussed. The model has further been employed to demonstrate adaptive robust control design for such a motion. Using numerous illustrations and tables, Adaptive Robust Control for Planar Snake Robots will interest researchers, practicing engineers and postgraduate students working in the field of robotics and control systems.


Adaptive Control

Adaptive Control

Author: Shankar Sastry

Publisher: Courier Corporation

Published: 2011-01-01

Total Pages: 402

ISBN-13: 0486482022

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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.


Adaptive-Robust Control with Limited Knowledge on Systems Dynamics

Adaptive-Robust Control with Limited Knowledge on Systems Dynamics

Author: Spandan Roy

Publisher: Springer Nature

Published: 2019-10-08

Total Pages: 157

ISBN-13: 981150640X

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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.