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.

This tutorial-style presentation of the fundamental techniques and algorithms in adaptive control is designed to meet the needs of a wide audience without sacrificing mathematical depth or rigor. The text explores the design, analysis, and application of a wide variety of algorithms that can be used to manage dynamical systems with unknown parameters. Topics include models for dynamic systems, stability, online parameter estimation, parameter identifiers, model reference adaptive control, adaptive pole placement control, and robust adaptive laws. Engineers and students interested in learning how to design, stimulate, and implement parameter estimators and adaptive control schemes will find that this treatment does not require a full understanding of the analytical and technical proofs. This volume will also serve graduate students who wish to examine the analysis of simple schemes and discover the steps involved in more complex proofs. Advanced students and researchers will find it a guide to the grasp of long and technical proofs. Numerous examples demonstrating design procedures and the techniques of basic analysis enrich the text.

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

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

A systematic and unified presentation of the fundamentals of adaptive control theory in both continuous time and discrete time 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. Adaptive Control Design and Analysis features: Introduction to systems and control Stability, operator norms, and signal convergence Adaptive parameter estimation State feedback adaptive control designs Parametrization of state observers for adaptive control Unified continuous and discrete-time adaptive control L1+a robustness theory for adaptive systems Direct and indirect adaptive control designs Benchmark comparison study of adaptive control designs Multivariate adaptive control Nonlinear adaptive control Adaptive compensation of actuator nonlinearities End-of-chapter discussion, problems, and advanced topics 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.

Control Applications of Adaptive covers the proceedings of the 197 Workshop on Applications of Adaptive Control, held in Yale University. This book is organized into five parts encompassing 18 chapters that summarize the potential application of adaptive control to many practical problems. Part I contains tutorials that bring together important result s in two of the most studied approaches to adaptive control, namely, self-tuning regulators and model reference adaptive control (MRAC), with a particular emphasis on the importance of error models in the stability analysis of MRAC. Part II examines the algorithms used for adaptive signal processing, while Part III describes the types of power systems problems that could benefit from application of adaptive control and how to apply adaptive control algorithms for controlling large electric generators. Part IV highlights adaptive control in aircraft systems. This part also considers how adaptive control fell into disfavor in the flight control community, illustrating the existence of residual negative bias. The desirability of cost elimination of air data sensors in less-sophisticated flight control systems is also discussed. Part V addresses the application of process control to chemical processes and to electromechanical systems. This part also shows the robustness and superior tracking and regulation properties of model reference adaptive control applied to liquid level control. Discussion on various classes of model reference adaptive controllers in a common framework from the viewpoint of microcomputer implementation is also included. This book will be of value to control system theorists and practitioners.

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.

Suitable for advanced undergraduates and graduate students, this text introduces theoretical and practical aspects of adaptive control. It offers an excellent perspective on techniques as well as an active knowledge of key approaches. Readers will acquire a well-developed sense of when to use adaptive techniques and when other methods are more appropriate. Starting with a broad overview, the text explores real-time estimation, self-tuning regulators and model-reference adaptive systems, stochastic adaptive control, and automatic tuning of regulators. Additional topics include gain scheduling, robust high-gain control and self-oscillating controllers, and suggestions for implementing adaptive controllers. Concluding chapters feature a summary of applications and a brief review of additional areas closely related to adaptive control. Both authors are Professors at the Lund Institute of Technology in Sweden, and this text has evolved from their many years of research and teaching. Their insights into properties, design procedures, and implementation of adaptive controllers are complemented by the numerous examples, simulations, and problems that appear throughout the book.