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Author: Jean-Paul Gauthier
Publisher: Cambridge University Press
Published: 2001-10-08
Total Pages: 250
ISBN-13: 9780521805933
DOWNLOAD EBOOKThis 2001 book presents a general theory as well as a constructive methodology to solve 'observation problems'.
Author: Gildas Besançon
Publisher: Springer
Published: 2007-10-11
Total Pages: 234
ISBN-13: 3540735038
DOWNLOAD EBOOKThe purpose of this fantastically useful book is to lay out an overview on possible tools for state reconstruction in nonlinear systems. Here, basic observability notions and observer structures are recalled, together with ingredients for advanced designs on this basis. The problem of state reconstruction in dynamical systems, known as observer problem, is crucial for controlling or even merely monitoring processes. For linear systems, the theory has been well established for several years, so this book attempts to tackle the problem for non-linear systems.
Author: Cong Wang
Publisher: CRC Press
Published: 2018-10-03
Total Pages: 167
ISBN-13: 1351837648
DOWNLOAD EBOOKDeterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation, and knowledge utilization in uncertain dynamic environments. It provides systematic design approaches for identification, recognition, and control of linear uncertain systems. Unlike many books currently available that focus on statistical principles, this book stresses learning through closed-loop neural control, effective representation and recognition of temporal patterns in a deterministic way. A Deterministic View of Learning in Dynamic Environments The authors begin with an introduction to the concepts of deterministic learning theory, followed by a discussion of the persistent excitation property of RBF networks. They describe the elements of deterministic learning, and address dynamical pattern recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation of oscillation faults, ECG/EEG pattern recognition, robot learning and control, and security analysis and control of power systems. A New Model of Information Processing This book elucidates a learning theory which is developed using concepts and tools from the discipline of systems and control. Fundamental knowledge about system dynamics is obtained from dynamical processes, and is then utilized to achieve rapid recognition of dynamical patterns and pattern-based closed-loop control via the so-called internal and dynamical matching of system dynamics. This actually represents a new model of information processing, i.e. a model of dynamical parallel distributed processing (DPDP).
Author: Alexandre Mauroy
Publisher: Springer Nature
Published: 2020-02-22
Total Pages: 568
ISBN-13: 3030357139
DOWNLOAD EBOOKThis book provides a broad overview of state-of-the-art research at the intersection of the Koopman operator theory and control theory. It also reviews novel theoretical results obtained and efficient numerical methods developed within the framework of Koopman operator theory. The contributions discuss the latest findings and techniques in several areas of control theory, including model predictive control, optimal control, observer design, systems identification and structural analysis of controlled systems, addressing both theoretical and numerical aspects and presenting open research directions, as well as detailed numerical schemes and data-driven methods. Each contribution addresses a specific problem. After a brief introduction of the Koopman operator framework, including basic notions and definitions, the book explores numerical methods, such as the dynamic mode decomposition (DMD) algorithm and Arnoldi-based methods, which are used to represent the operator in a finite-dimensional basis and to compute its spectral properties from data. The main body of the book is divided into three parts: theoretical results and numerical techniques for observer design, synthesis analysis, stability analysis, parameter estimation, and identification; data-driven techniques based on DMD, which extract the spectral properties of the Koopman operator from data for the structural analysis of controlled systems; and Koopman operator techniques with specific applications in systems and control, which range from heat transfer analysis to robot control. A useful reference resource on the Koopman operator theory for control theorists and practitioners, the book is also of interest to graduate students, researchers, and engineers looking for an introduction to a novel and comprehensive approach to systems and control, from pure theory to data-driven methods.
Author: Shimon Y. Nof
Publisher: Springer Nature
Published: 2023-06-16
Total Pages: 1533
ISBN-13: 3030967298
DOWNLOAD EBOOKThis handbook incorporates new developments in automation. It also presents a widespread and well-structured conglomeration of new emerging application areas, such as medical systems and health, transportation, security and maintenance, service, construction and retail as well as production or logistics. The handbook is not only an ideal resource for automation experts but also for people new to this expanding field.
Author: Claudio Bonivento
Publisher: Springer
Published: 2007-06-04
Total Pages: 310
ISBN-13: 3540707018
DOWNLOAD EBOOKThis volume is the outcome of the first CASY workshop on "Advances in Control Theory and Applications" which was held at University of Bologna on May 22-26, 2006. It consists of selected contributions by some of the invited speakers and contains recent results in control. The volume is intended for engineers, researchers, and students in control engineering.
Author: Antonio Loría
Publisher: Springer Science & Business Media
Published: 2006-02-09
Total Pages: 312
ISBN-13: 9781846283130
DOWNLOAD EBOOKThis book includes selected contributions by lecturers at the third annual Formation d’Automatique de Paris. It provides a well-integrated synthesis of the latest thinking in nonlinear optimal control, observer design, stability analysis and structural properties of linear systems, without the need for an exhaustive literature review. The internationally known contributors to this volume represent many of the most reputable control centers in Europe.
Author: Andreu Cecilia
Publisher: Springer Nature
Published: 2023-08-28
Total Pages: 235
ISBN-13: 3031389247
DOWNLOAD EBOOKThis book reports on a set of advances relating to nonlinear observer design, with a special emphasis on high-gain observers. First, it covers the design of filters and their addition to the observer for reducing noise, a topic that has been so far neglected in the literature. Further, it describes the adaptive re-design of nonlinear observers to reduce the effect of parametric uncertainty. It discusses several limitations of classical methods, presenting a set of successfull solutions, which are mathematically formalised through Lyapunov stability analysis, and in turn validated via numerical simulations. In the second part of the book, two applications of the adaptive nonlinear observers are described, such in the estimation of the liquid water in a hydrogen fuel cell and in the solution of a common cybersecurity problem, i.e. false data injection attacks in DC microgrids. All in all, this book offers a comprehensive report on the state-of-the-art in nonlinear observer design for energy systems, including mathematical demonstrations, and numerical and and experimental validations.
Author: Hassan H. Khalil
Publisher: SIAM
Published: 2017-06-23
Total Pages: 330
ISBN-13: 1611974860
DOWNLOAD EBOOKFor over a quarter of a century, high-gain observers have been used extensively in the design of output feedback control of nonlinear systems. This book presents a clear, unified treatment of the theory of high-gain observers and their use in feedback control. Also provided is a discussion of the separation principle for nonlinear systems; this differs from other separation results in the literature in that recovery of stability as well as performance of state feedback controllers is given. The author provides a detailed discussion of applications of high-gain observers to adaptive control and regulation problems and recent results on the extended high-gain observers. In addition, the author addresses two challenges that face the implementation of high-gain observers: high dimension and measurement noise. Low-power observers are presented for high-dimensional systems. The effect of measurement noise is characterized and techniques to reduce that effect are presented. The book ends with discussion of digital implementation of the observers. Readers will find comprehensive coverage of the main results on high-gain observers; rigorous, self-contained proofs of all results; and numerous examples that illustrate and provide motivation for the results. The book is intended for engineers and applied mathematicians who design or research feedback control systems.
Author: Pauline Bernard
Publisher: Springer
Published: 2019-02-01
Total Pages: 185
ISBN-13: 3030111466
DOWNLOAD EBOOKObserver Design for Nonlinear Systems deals with the design of observers for the large class of nonlinear continuous-time models. It contains a unified overview of a broad range of general designs, including the most recent results and their proofs, such as the homogeneous and nonlinear Luenberger design techniques. The book starts from the observation that most observer designs consist in looking for a reversible change of coordinates transforming the expression of the system dynamics into some specific structures, called normal forms, for which an observer is known. Therefore, the problem of observer design is broken down into three sub-problems: • What are the available normal forms and their associated observers?• Under which conditions can a system be transformed into one of these forms and through which transformation? • How can an inverse transformation that recovers an estimate in the given initial coordinates be achieved? This organisation allows the book to structure results within a united framework, highlighting the importance of the choice of the observer coordinates for nonlinear systems. In particular, the first part covers state-affine forms with their Luenberger or Kalman designs, and triangular forms with their homogeneous high-gain designs. The second part addresses the transformation into linear forms through linearization by output injection or in the context of a nonlinear Luenberger design, and into triangular forms under the well-known uniform and differential observability assumptions. Finally, the third part presents some recently developed methods for avoiding the numerically challenging inversion of the transformation. Observer Design for Nonlinear Systems addresses students and researchers looking for an introduction to or an overview of the state of the art in observer design for nonlinear continuous-time dynamical systems. The book gathers the most important results focusing on a large and diffuse literature on general observer designs with global convergence, and is a valuable source of information for academics and practitioners.
