Discrete H∞ Optimization
Discrete H∞ Optimization

Author: Charles K. Chui

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 271

ISBN-13: 3642591450

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Discrete H¿ Optimization is concerned with the study of H¿ optimization for digital signal processing and discrete-time control systems. The first three chapters present the basic theory and standard methods in digital filtering and systems from the frequency-domain approach, followed by a discussion of the general theory of approximation in Hardy spaces. AAK theory is introduced, first for finite-rank operators and then more generally, before being extended to the multi-input/multi-output setting. This mathematically rigorous book is self-contained and suitable for self-study. The advanced mathematical results derived here are applicable to digital control systems and digital filtering.

System Modelling and Optimization
System Modelling and Optimization

Author: J. Dolezal

Publisher: Springer

Published: 2013-06-05

Total Pages: 635

ISBN-13: 0387348972

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Proceedings volume contains carefully selected papers presented during the 17th IFIP Conference on System Modelling and Optimization. Optimization theory and practice, optimal control, system modelling, stochastic optimization, and technical and non-technical applications of the existing theory are among areas mostly addressed in the included papers. Main directions are treated in addition to several survey papers based on invited presentations of leading specialists in the respective fields. Publication provides state-of-the-art in the area of system theory and optimization and points out several new areas (e.g fuzzy set, neural nets), where classical optimization topics intersects with computer science methodology.

Optimal Control
Optimal Control

Author: Frank L. Lewis

Publisher: John Wiley & Sons

Published: 1995-11-03

Total Pages: 564

ISBN-13: 9780471033783

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This new, updated edition of Optimal Control reflects major changes that have occurred in the field in recent years and presents, in a clear and direct way, the fundamentals of optimal control theory. It covers the major topics involving measurement, principles of optimality, dynamic programming, variational methods, Kalman filtering, and other solution techniques. To give the reader a sense of the problems that can arise in a hands-on project, the authors have included new material on optimal output feedback control, a technique used in the aerospace industry. Also included are two new chapters on robust control to provide background in this rapidly growing area of interest. Relations to classical control theory are emphasized throughout the text, and a root-locus approach to steady-state controller design is included. A chapter on optimal control of polynomial systems is designed to give the reader sufficient background for further study in the field of adaptive control. The authors demonstrate through numerous examples that computer simulations of optimal controllers are easy to implement and help give the reader an intuitive feel for the equations. To help build the reader's confidence in understanding the theory and its practical applications, the authors have provided many opportunities throughout the book for writing simple programs. Optimal Control will also serve as an invaluable reference for control engineers in the industry. It offers numerous tables that make it easy to find the equations needed to implement optimal controllers for practical applications. All simulations have been performed using MATLAB and relevant Toolboxes. Optimal Control assumes a background in the state-variable representation of systems; because matrix manipulations are the basic mathematical vehicle of the book, a short review is included in the appendix. A lucid introductory text and an invaluable reference, Optimal Control will serve as a complete tool for the professional engineer and advanced student alike. As a superb introductory text and an indispensable reference, this new edition of Optimal Control will serve the needs of both the professional engineer and the advanced student in mechanical, electrical, and aerospace engineering. Its coverage encompasses all the fundamental topics as well as the major changes of recent years, including output-feedback design and robust design. An abundance of computer simulations using MATLAB and relevant Toolboxes is included to give the reader the actual experience of applying the theory to real-world situations. Major topics covered include: Static Optimization Optimal Control of Discrete-Time Systems Optimal Control of Continuous-Time Systems The Tracking Problem and Other LQR Extensions Final-Time-Free and Constrained Input Control Dynamic Programming Optimal Control for Polynomial Systems Output Feedback and Structured Control Robustness and Multivariable Frequency-Domain Techniques

Linear Discrete-Time Systems
Linear Discrete-Time Systems

Author: Zoran M. Buchevats

Publisher: CRC Press

Published: 2017-11-22

Total Pages: 454

ISBN-13: 1351707590

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This book covers crucial lacunae of the linear discrete-time time-invariant dynamical systems and introduces the reader to their treatment, while functioning under real, natural conditions, in forced regimes with arbitrary initial conditions. It provides novel theoretical tools necessary for the analysis and design of the systems operating in stated conditions. The text completely covers two well-known systems, IO and ISO, along with a new system, IIO. It discovers the concept of the full transfer function matrix F(z) in the z-complex domain, which incorporates the Z-transform of the system, input and another variable, vectors, all with arbitrary initial conditions. Consequently, it addresses the full system matrix P(z) and the full block diagram technique based on the use of F(z), which incorporates the Z-transform of the system, input and another variable, vectors, all with arbitrary initial conditions. The book explores the direct relationship between the system full transfer function matrix F(z) and the Lyapunov stability concept, definitions, and conditions, as well as with the BI stability concept, definitions, and conditions. The goal of the book is to unify the study and applications of all three classes of the linear discrete-time time-invariant system, for short systems.

Discrete-time Stochastic Systems
Discrete-time Stochastic Systems

Author: Torsten Söderström

Publisher: Springer Science & Business Media

Published: 2002-07-26

Total Pages: 410

ISBN-13: 9781852336493

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This comprehensive introduction to the estimation and control of dynamic stochastic systems provides complete derivations of key results. The second edition includes improved and updated material, and a new presentation of polynomial control and new derivation of linear-quadratic-Gaussian control.

Optimization of Stochastic Systems
Optimization of Stochastic Systems

Author: Masanao Aoki

Publisher: Academic Press

Published: 1967-01-01

Total Pages: 374

ISBN-13: 0080955398

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Optimization of Stochastic Systems is an outgrowth of class notes of a graduate level seminar on optimization of stochastic systems. Most of the material in the book was taught for the first time during the 1965 Spring Semester while the author was visiting the Department of Electrical Engineering, University of California, Berkeley. The revised and expanded material was presented at the Department of Engineering, University of California, Los Angeles during the 1965 Fall Semester. The systems discussed in the book are mostly assumed to be of discrete-time type with continuous state variables taking values in some subsets of Euclidean spaces. There is another class of systems in which state variables are assumed to take on at most a denumerable number of values, i.e., these systems are of discrete-time discrete-space type. Although the problems associated with the latter class of systems are many and interesting, andalthough they are amenable to deep analysis on such topics as the limiting behaviors of state variables as time indexes increase to infinity, this class of systems is not included here, partly because there are many excellent books on the subjects and partly because inclusion of these materials would easily double the size of the book.

Optimization and Dynamical Systems
Optimization and Dynamical Systems

Author: Uwe Helmke

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 409

ISBN-13: 1447134672

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This work is aimed at mathematics and engineering graduate students and researchers in the areas of optimization, dynamical systems, control sys tems, signal processing, and linear algebra. The motivation for the results developed here arises from advanced engineering applications and the emer gence of highly parallel computing machines for tackling such applications. The problems solved are those of linear algebra and linear systems the ory, and include such topics as diagonalizing a symmetric matrix, singular value decomposition, balanced realizations, linear programming, sensitivity minimization, and eigenvalue assignment by feedback control. The tools are those, not only of linear algebra and systems theory, but also of differential geometry. The problems are solved via dynamical sys tems implementation, either in continuous time or discrete time , which is ideally suited to distributed parallel processing. The problems tackled are indirectly or directly concerned with dynamical systems themselves, so there is feedback in that dynamical systems are used to understand and optimize dynamical systems. One key to the new research results has been the recent discovery of rather deep existence and uniqueness results for the solution of certain matrix least squares optimization problems in geomet ric invariant theory. These problems, as well as many other optimization problems arising in linear algebra and systems theory, do not always admit solutions which can be found by algebraic methods.

Stochastic Multi-Stage Optimization
Stochastic Multi-Stage Optimization

Author: Pierre Carpentier

Publisher:

Published: 2015

Total Pages:

ISBN-13: 9783319181394

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The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on the role of information regarding optimization problems - it discusses the related discretization issues. There is a growing need to tackle uncertainty in applications of optimization. For example the massive introduction of renewable energies in power systems challenges traditional ways to manage them. This book lays out basic and advanced tools to handle and numerically solve such problems and thereby is building a bridge between Stochastic Programming and Stochastic Control. It is intended for graduates readers and scholars in optimization or stochastic control, as well as engineers with a background in applied mathematics.

Micromechatronics
Micromechatronics

Author: Victor Giurgiutiu

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 936

ISBN-13: 1439883106

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Focusing on recent developments in engineering science, enabling hardware, advanced technologies, and software, Micromechatronics: Modeling, Analysis, and Design with MATLAB, Second Edition provides clear, comprehensive coverage of mechatronic and electromechanical systems. It applies cornerstone fundamentals to the design of electromechanical syst

Data-Driven Iterative Learning Control for Discrete-Time Systems
Data-Driven Iterative Learning Control for Discrete-Time Systems

Author: Ronghu Chi

Publisher: Springer Nature

Published: 2022-11-15

Total Pages: 239

ISBN-13: 9811959501

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This book belongs to the subject of control and systems theory. It studies a novel data-driven framework for the design and analysis of iterative learning control (ILC) for nonlinear discrete-time systems. A series of iterative dynamic linearization methods is discussed firstly to build a linear data mapping with respect of the system’s output and input between two consecutive iterations. On this basis, this work presents a series of data-driven ILC (DDILC) approaches with rigorous analysis. After that, this work also conducts significant extensions to the cases with incomplete data information, specified point tracking, higher order law, system constraint, nonrepetitive uncertainty, and event-triggered strategy to facilitate the real applications. The readers can learn the recent progress on DDILC for complex systems in practical applications. This book is intended for academic scholars, engineers, and graduate students who are interested in learning control, adaptive control, nonlinear systems, and related fields.