Nonlinear and adaptive control design

Author: Miroslav Krstić
Publisher: Wiley-Interscience
ISBN:
Format: PDF, Docs
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Using a pedagogical style along with detailed proofs and illustrative examples, this book opens a view to the largely unexplored area of nonlinear systems with uncertainties. The focus is on adaptive nonlinear control results introduced with the new recursive design methodology--adaptive backstepping. Describes basic tools for nonadaptive backstepping design with state and output feedbacks.

Nonlinear and Adaptive Control with Applications

Author: Alessandro Astolfi
Publisher: Springer Science & Business Media
ISBN: 9781848000667
Format: PDF, ePub
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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.

Adaptive Control Design and Analysis

Author: Gang Tao
Publisher: John Wiley & Sons
ISBN: 9780471274520
Format: PDF, ePub, Docs
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Annotation "Today, adaptive control theory has grown to be a rigorous and mature discipline. As the advantages of adaptive systems for developing advanced applications grow apparent, adaptive control is becoming more popular in many fields of engineering and science. Using a simple, balanced, and harmonious style, this book provides a convenient introduction to the subject and improves one's understanding of adaptive control theory." "As either a textbook or reference, this self-contained tutorial of adaptive control design and analysis is ideal for practicing engineers, researchers, and graduate students alike."--BOOK JACKET. Title Summary field provided by Blackwell North America, Inc. All Rights Reserved.

Performance of Nonlinear Approximate Adaptive Controllers

Author: Mark French
Publisher: John Wiley & Sons
ISBN: 9780471498094
Format: PDF, Kindle
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In recent years there has been a wide interest in non-linear adaptive control using approximate models, either for tracking or regulation, and usually under the banner of neural network based control. The authors present a unique critical evaluation of the approximate model philosophy and its setting, rigorously comparing the performance of such controls against competing designs. Analysing a very topical aspect of contemporary research and control practice this book highlights the situations in which approximate model based designs are most appropriate and indicates scenarios in which other designs could be used more productively. Throughout the text concepts are illustrated using a variety of examples, both academic problems and those based on physical examples. The work is designed to open the door to realistic applications. * Unified coverage of the theory and application of a wide range of control systems areas including neural network based control and control using the approximate model * Presents a mathematically well founded introduction to the area of intelligent control * A varied selecion of practical examples drawn from a variety of fields, including robotics and aerospace, illustrate theoretical principles * Clear compaisons of a variety of control designs * Cross disciplinary approach to this leading edge topic A valuable reference for control practitioners and theorists, artificial intelligence researchers and applied mathematicians, as well as graduate students and researchers with an interest in adaptive control and stability.

Nonlinear Control Systems Design 1992

Author: M. Fliess
Publisher: Elsevier
ISBN: 1483298752
Format: PDF, ePub, Docs
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This volume represents most aspects of the rich and growing field of nonlinear control. These proceedings contain 78 papers, including six plenary lectures, striking a balance between theory and applications. Subjects covered include feedback stabilization, nonlinear and adaptive control of electromechanical systems, nonholonomic systems. Generalized state space systems, algebraic computing in nonlinear systems theory, decoupling, linearization and model-matching and robust control are also covered.

Induction Motor Control Design

Author: Riccardo Marino
Publisher: Springer Science & Business Media
ISBN: 9781849962841
Format: PDF, Mobi
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This book provides the most important steps and concerns in the design of estimation and control algorithms for induction motors. A single notation and modern nonlinear control terminology is used to make the book accessible, although a more theoretical control viewpoint is also given. Focusing on the induction motor with, the concepts of stability and nonlinear control theory given in appendices, this book covers: speed sensorless control; design of adaptive observers and parameter estimators; a discussion of nonlinear adaptive controls containing parameter estimation algorithms; and comparative simulations of different control algorithms. The book sets out basic assumptions, structural properties, modelling, state feedback control and estimation algorithms, then moves to more complex output feedback control algorithms, based on stator current measurements, and modelling for speed sensorless control. The induction motor exhibits many typical and unavoidable nonlinear features.

Nonlinear Adaptive Controller Design for Air breathing Hypersonic Vehicles

Author: Lisa Fiorentini
Publisher:
ISBN:
Format: PDF, Kindle
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Abstract: This dissertation presents the design of two nonlinear robust controllers for an air-breathing hypersonic vehicle model capable of providing stable tracking of velocity and altitude (or flight-path angle) reference trajectories. To overcome the analytical intractability of a dynamical model derived from first principles, a simplified control-oriented model is used for control design. The control-oriented model retains the most important features of the model from which it was derived, including the non-minimum phase characteristic of the flight-path angle dynamics and strong couplings between the engine and flight dynamics. The first control design considers as control inputs the fuel equivalence ratio and the elevator and canard deflections. A combination of nonlinear sequential loop-closure and adaptive dynamic inversion has been adopted for the design of a dynamic state-feedback controller. An important contribution given by this work is the complete characterization of the internal dynamics of the model has been derived for Lyapunov-based stability analysis of the closed-loop system, which includes the structural dynamics. The results obtained address the issue of stability robustness with respect to both parametric model uncertainty, which naturally arises in adopting reduced-complexity models for control design, and dynamic perturbations due to the flexible dynamics. In the second control design a first step has been taken in extending those results in the case in which only two control inputs are available, namely the fuel equivalence ratio and the elevator deflection. The extension of these results to this new framework is not trivial since several issues arise. First of all, the vehicle dynamics are characterized by exponentially unstable zero-dynamics when longitudinal velocity and flight-path angle are selected as regulated output. This non-minimum phase behavior arises as a consequence of elevator-to-lift coupling. In the previous design the canard was strategically used to adaptively decouple lift from elevator command, thus rendering the system minimum phase. Moreover, the canard input was also employed to enforce the equilibrium at the desired trim condition and to provide a supplementary stabilizing action. As a result, when this control input is not assumed to be available, the fact that the system needs to be augmented with an integrator (to reconstruct the desired equilibrium) and the non-minimum phase behavior have a strong impact on the control design. In these preliminary results the flexible effects are not taken into account in the stability analysis but are considered as a perturbation and included in the simulation model. The approach considered utilizes a combination of adaptive and robust design methods based on both classical and recently developed nonlinear design tools. As a result, the issue of robustness with respect to parameter uncertainties is addressed also in this control design. Simulation results on the full nonlinear model show the effectiveness of both controllers.

Modeling and Adaptive Nonlinear Control of Electric Motors

Author: Farshad Khorrami
Publisher: Springer Science & Business Media
ISBN: 9783540009368
Format: PDF, ePub
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In this book, modeling and control design of electric motors, namely step motors, brushless DC motors and induction motors, are considered. The book focuses on recent advances on feedback control designs for various types of electric motors, with a slight emphasis on stepper motors. For this purpose, the authors explore modeling of these devices to the extent needed to provide a high-performance controller, but at the same time one amenable to model-based nonlinear designs. The control designs focus primarily on recent robust adaptive nonlinear controllers to attain high performance. It is shown that the adaptive robust nonlinear controller on its own achieves reasonably good performance without requiring the exact knowledge of motor parameters. While carefully tuned classical controllers often achieve required performance in many applications, it is hoped that the advocated robust and adaptive designs will lead to standard universal controllers with minimal need for fine tuning of control parameters.