This textbook aims to provide a clear understanding of the various tools of analysis and design for robust stability and performance of uncertain dynamic systems. In model-based control design and analysis, mathematical models can never completely represent the “real world” system that is being modeled, and thus it is imperative to incorporate and accommodate a level of uncertainty into the models. This book directly addresses these issues from a deterministic uncertainty viewpoint and focuses on the interval parameter characterization of uncertain systems. Various tools of analysis and design are presented in a consolidated manner. This volume fills a current gap in published works by explicitly addressing the subject of control of dynamic systems from linear state space framework, namely using a time-domain, matrix-theory based approach. This book also: Presents and formulates the robustness problem in a linear state space model framework. Illustrates various systems level methodologies with examples and applications drawn from aerospace, electrical and mechanical engineering. Provides connections between lyapunov-based matrix approach and the transfer function based polynomial approaches. Robust Control of Uncertain Dynamic Systems: A Linear State Space Approach is an ideal book for first year graduate students taking a course in robust control in aerospace, mechanical, or electrical engineering.
This book is a collection of 34 papers presented by leading researchers at the International Workshop on Robust Control held in San Antonio, Texas in March 1991. The common theme tying these papers together is the analysis, synthesis, and design of control systems subject to various uncertainties. The papers describe the latest results in parametric understanding, H8 uncertainty, l1 optical control, and Quantitative Feedback Theory (QFT). The book is the first to bring together all the diverse points of view addressing the robust control problem and should strongly influence development in the robust control field for years to come. For this reason, control theorists, engineers, and applied mathematicians should consider it a crucial acquisition for their libraries.
The first comprehensive, self-contained text on nonlinear analysis and robust control Increasingly, robust control plays a greater role in achieving high performance for systems that are too complex to be modeled accurately. Using Lyapunov's direct method to develop design procedures, compare different controls, and give the reader a definite feel for stability analysis and robust control for nonlinear systems with significant uncertainty, this unique text: * Presents the complete set of robust control design procedures for nonlinear uncertain systems * Introduces the recursive interlacing design method that will generate robust control for uncertain systems with cascaded, feedback, and feedforward dynamics * Covers a broad range of robust control designs, including state feedback and input-output, continuous-time and digital, and static and dynamic controls * Gives advice on selecting design parameters according to their impact on stability and performance * Features illustrations as well as end-of-chapter exercises and references
A Course in Robust Control Theory
Author: Geir E. Dullerud, Fernando Paganini
Publisher: Springer Science & Business Media
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.
Mathematical Systems Theory I
Author: Diederich Hinrichsen, Anthony J. Pritchard
Publisher: Springer Science & Business Media
This book presents the mathematical foundations of systems theory in a self-contained, comprehensive, detailed and mathematically rigorous way. It is devoted to the analysis of dynamical systems and combines features of a detailed introductory textbook with that of a reference source. The book contains many examples and figures illustrating the text which help to bring out the intuitive ideas behind the mathematical constructions.
Author: Jürgen Ackermann
Publisher: Springer Science & Business Media
Many plants have large variations in operating conditions. To ensure smooth running it is essential to find a simple fixed gain controller that guarantees rapidly decaying and well-damped transients for all admissible operating conditions. Robust Control presents design tools, developed by the authors, for the solution of this design problem. Examples of simple and complex cases such as a crane, a flight control problem and the automatic and active four-wheel steering of a car illustrate the use of these tools. This book is intended for anyone who has taken an undergraduate course in feedback control systems and who seeks an advanced treatment of robust control with applications. Drawing on the resources and authoritative research of a leading aerospace institute, it will mainly be of interest to mechanical and electrical engineers in universities, institutes and industrial research centres.
A complete, up-to-date textbook on an increasingly important subject Robust Systems Theory and Applications covers both the techniques used in linear robust control analysis/synthesis and in robust (control-oriented) identification. The main analysis and design methods are complemented by elaborated examples and a group of worked-out applications that stress specific practical issues: nonlinearities, robustness against changes in operating conditions, uncertain infinite dimensional plants, and actuator and sensor limitations. Designed expressly as a textbook for master's and first-year PhD students, this volume: * Introduces basic robustness concepts in the context of SISO systems described by Laplace transforms, establishing connections with well-known classical control techniques * Presents the internal stabilization problem from two different points of view: algebraic and state --space * Introduces the four basic problems in robust control and the Loop shaping design method Presents the optimal *2 control problem from a different viewpoint, including an analysis of the robustness properties of *2 controllers and a treatment of the generalized *2 problem * Presents the *2 control problem using both the state-space approach developed in the late 1980s and a Linear Matrix Inequality approach (developed in the mid 1990s) that encompasses more general problems * Discusses more general types of uncertainties (parametric and mixed type) and ??-synthesis as a design tool * Presents an overview of optimal ,1 control theory and covers the fundamentals of its star-norm approximation * Presents the basic tools of model order reduction * Provides a tutorial on robust identification * Offers numerous end-of-chapter problems and worked-out examples of robust control
Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.
Robust Control System Design: Advanced State Space Techniques, Second Edition expands upon a groundbreaking and combinatorial approach to state space control system design that fully realizes the critical loop transfer function and robustness properties of state/generalized state feedback control. This edition offers many new examples and exercises to illustrate and clarify new design concepts, approaches, and procedures while highlighting the fact that state/generalized state feedback control can improve system performance and robustness more effectively than other forms of control. Revised and expanded throughout, the second edition presents an improved eigenstructure assignment design method that enhances system performance and robustness more directly and effectively and allows for adjustment of design formulations based on design testing and simulation. The author proposes the systematic controller order adjustment for the tradeoff between performance and robustness based on the complete unification of the state feedback control and static output feedback control. The book also utilizes a more accurate robust stability measure to guide control designs.
Advanced Control Engineering provides a complete course in control engineering for undergraduates of all technical disciplines. Starting with a basic overview of elementary control theory this text quickly moves on to a rigorous examination of more advanced and cutting edge date aspects such as robust and intelligent control, including neural networks and genetic algorithms. With examples from aeronautical, marine and many other types of engineering, Roland Burns draws on his extensive teaching and practical experience presents the subject in an easily understood and applied manner. Control Engineering is a core subject in most technical areas. Problems in each chapter, numerous illustrations and free Matlab files on the accompanying website are brought together to provide a valuable resource for the engineering student and lecturer alike. Complete Course in Control Engineering Real life case studies Numerous problems
A comprehensive development of interpolating control, this monograph demonstrates the reduced computational complexity of a ground-breaking technique compared with the established model predictive control. The text deals with the regulation problem for linear, time-invariant, discrete-time uncertain dynamical systems having polyhedral state and control constraints, with and without disturbances, and under state or output feedback. For output feedback a non-minimal state-space representation is used with old inputs and outputs as state variables. Constrained Control of Uncertain, Time-Varying, Discrete-time Systems details interpolating control in both its implicit and explicit forms. In the former at most two linear-programming or one quadratic-programming problem are solved on-line at each sampling instant to yield the value of the control variable. In the latter the control law is shown to be piecewise affine in the state, and so the state space is partitioned into polyhedral cells so that at each sampling interval the cell to which the measured state belongs must be determined. Interpolation is performed between vertex control, and a user-chosen control law in its maximal admissible set surrounding the origin. Novel proofs of recursive feasibility and asymptotic stability of the vertex control law, and of the interpolating control law are given. Algorithms for implicit and explicit interpolating control are presented in such a way that the reader may easily realize them. Each chapter includes illustrative examples, and comparisons with model predictive control in which the disparity in computational complexity is shown to be particularly in favour of interpolating control for high-order systems, and systems with uncertainty. Furthermore, the performance of the two methods proves similar except in those cases when a solution cannot be found with model predictive control at all. The book concludes with two high dimensional examples and a benchmark robust model predictive control problem: the non-isothermal continuously-stirred-tank reactor. For academic control researchers and students or for control engineers interested in implementing constrained control systems Constrained Control of Uncertain, Time-Varying, Discrete-time Systems will provide an attractive low-complexity control alternative for cases in which model predictive control is currently attempted.
Provides a useful reference source on system structure and control. Covers, linear systems, nonlinear systems, robust control, implicit system, chaotic systems, singular and time-varying systems.
Actuator Saturation Control
Author: Vikram Kapila, Karolos Grigoriadis
Publisher: CRC Press
Compiling the most significant advances from nearly a decade of research, this reference compares and evaluates a wide variety of techniques for the design, analysis, and implementation of control methodologies for systems with actuator saturation. The book presents efficient computational algorithms and new control paradigms for application in the mechanical, electrical, and aerospace industries. Offering real-world solutions to manage system constraints, Actuator Saturation Control provides concise tutorials on recent breakthroughs in the field; novel procedures to achieve global stability, optimal performance, and dynamic anti-windup; practical strategies to model and predict actuator dynamics; effective methods to reduce system sensitivity to external disturbances; equations within the stochastic linearization framework for actuator saturation control; current approaches to ensure graceful performance degradation in the presence of saturation phenomena; linear parameter-varying (LPV) formulations of state and output feedback controllers, and a comprehensive survey of optimal windup and directionality compensation.
Robust and Adaptive Control
Author: Eugene Lavretsky, Kevin Wise
Publisher: Springer Science & Business Media
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.
In this book the authors reduce a wide variety of problems arising in system and control theory to a handful of convex and quasiconvex optimization problems that involve linear matrix inequalities. These optimization problems can be solved using recently developed numerical algorithms that not only are polynomial-time but also work very well in practice; the reduction therefore can be considered a solution to the original problems. This book opens up an important new research area in which convex optimization is combined with system and control theory, resulting in the solution of a large number of previously unsolved problems.