Focusses on filtering for linear processes, and helps design linear stable unbiased filters that yield an estimation error with the lowest root-mean-square (RMS) norm. This book defines various hierarchical classes of filtering problems based on the availability of statistical knowledge regarding noise, disturbances, and other uncertainties.

This book is a revision and extension of the author's 1995 Sourcebook of Control Systems Engineering. Because of the extensions and other modifications, it has been re-titled Handbook of Control Systems Engineering, which it is intended to be for its prime audience: advanced undergraduate students, beginning graduate students, and practicing engineers needing an understandable review of the field or recent developments which may prove useful. New in This Edition. Two new chapters on aspects of nonlinear systems have been incorporated. In the first of these, selected material for nonlinear systems is concentrated on four aspects: showing the value of certain linear controllers, arguing the suitability of algebraic linearization, reviewing the semi-classical methods of harmonic balance, and introducing the nonlinear change of variable technique known as feedback linearization. In the second new chapter, the topic of variable structure control, often with sliding mode, is introduced. A third chapter introduces discrete event systems, including several approaches to their analysis. The chapters on robust control and intelligent control have been extensively revised. Modest revisions and extensions have also been made to other chapters, often to incorporate extensions to nonlinear systems. Many references have been updated to more recent books, although old standards are still cited. Also, some of the advances in computer and communications technology are reflected. The index has been revised and expanded. The structure of the book is as in the first edition. Briefly, the aim is to present the topics in a fairly modular manner with certain main groupings. The first several chapters areconcerned with the hardware and software of the control task as well as systems engineering associated with the selection of appropriate components. The next chapters look at the sources and representations of the mathematical models used in the theory. A number of chapters then are concerned with standard classical or transform domain material as is usually presented in a first level university course, including stability theory, root locus diagrams, and Bode plots. The next group of chapters concerns the standard modern or state space material usually met in a second level course. Included here are observers, pole placement, and optimal control. Overlapping into usual graduate level courses are the next several chapters on more advanced optimal control, Kalman filtering, system identification, and standard adaptive control. The final chapters introduce more advanced, research level subjects. Here are selected topics in nonlinear control, intelligent control, robust control, and discrete event systems. The topics covered are intended to represent the mainstream of control systems teaching. Examples are presented to illustrate the computability of the theory presented. Handbook of Controls Systems Engineering, Second Edition is suitable as a secondary text for upper level undergraduate students, beginning graduate students, and as a reference for researchers and practitioners in industry.

This book describes the active vibration control techniques which have been developed to suppress excessive vibrations of structures. It covers the fundamental principles of active control methods and their applications and shows how active vibration control techniques have replaced traditional passive vibration control. The book includes coverage of dynamic modeling, control design, sensing methodology, actuator mechanism and electronic circuit design, and the implementation of control algorithms via digital controllers. An in-depth approach has been taken to describe the modeling of structures for control design, the development of control algorithms suitable for structural control, and the implementation of control algorithms by means of Simulink block diagrams or C language. Details of currently available actuators and sensors and electronic circuits for signal conditioning and filtering have been provided based on the most recent advances in the field. The book is used as a textbook for students and a reference for researchers who are interested in studying cutting-edge technology. It will be a valuable resource for academic and industrial researchers and professionals involved in the design and manufacture of active vibration controllers for structures in a wide variety of fields and industries including the automotive, rail, aerospace, and civil engineering sectors.

The aim of this book is to explain in simple language what we know and what we do not know about information and entropy - two of the most frequently discussed topics in recent literature - and whether they are relevant to life and the entire universe.Entropy is commonly interpreted as a measure of disorder. This interpretation has caused a great amount of 'disorder' in the literature. One of the aims of this book is to put some 'order' in this 'disorder'.The book explains with minimum amount of mathematics what information theory is and how it is related to thermodynamic entropy. Then it critically examines the application of these concepts to the question of 'What is life?' and whether or not they can be applied to the entire universe.

At the start of the new millennium, mankind is challenged by a paradox: the greater the apparent knowledge becomes, the greater the uncertainty in understanding and predicting how the world works appears. This book presents the outline of a new basis of Systems Science and a methodology for its applications in complex environmental, economic, social, and technological systems.

It has been widely recognized nowadays the importance of introducing mathematical models that take into account possible sudden changes in the dynamical behavior of a high-integrity systems or a safety-critical system. Such systems can be found in aircraft control, nuclear power stations, robotic manipulator systems, integrated communication networks and large-scale flexible structures for space stations, and are inherently vulnerable to abrupt changes in their structures caused by component or interconnection failures. In this regard, a particularly interesting class of models is the so-called Markov jump linear systems (MJLS), which have been used in numerous applications including robotics, economics and wireless communication. Combining probability and operator theory, the present volume provides a unified and rigorous treatment of recent results in control theory of continuous-time MJLS. This unique approach is of great interest to experts working in the field of linear systems with Markovian jump parameters or in stochastic control. The volume focuses on one of the few cases of stochastic control problems with an actual explicit solution and offers material well-suited to coursework, introducing students to an interesting and active research area.

The book is addressed to researchers working in control and signal processing engineering. Prerequisites include a solid background in classical linear control theory, basic familiarity with continuous-time Markov chains and probability theory, and some elementary knowledge of operator theory.

The aim of this book is to explain in simple language what we know and what we do not know about information and entropy - two of the most frequently discussed topics in recent literature - and whether they are relevant to life and the entire universe.Entropy is commonly interpreted as a measure of disorder. This interpretation has caused a great amount of 'disorder' in the literature. One of the aims of this book is to put some 'order' in this 'disorder'.The book explains with minimum amount of mathematics what information theory is and how it is related to thermodynamic entropy. Then it critically examines the application of these concepts to the question of 'What is life?' and whether or not they can be applied to the entire universe.

Introduction to Theory of Control in Organizations explains how methodologies from systems analysis and control theory, including game and graph theory, can be applied to improve organizational management. The theory presented extends the traditional approach to management science by introducing the optimization and game-theoretical tools required to account for the special nature of human beings being viewed as control objects. The book introduces a version of mechanism design that has been customized to solve the problems that today's managers must contend with. All mathematical models and mechanisms studied are motivated by the most common problems encountered by managers in firms and non-profit organizations. Requiring no prior knowledge of game theory or mechanism design, the book includes a systematic introduction to the underlying methodology of modern theory of control in organizations. The authors use formal methods to construct robust and efficient decision-making procedures which support all aspects and stages of management activity over all decision horizons-from operational to strategic management. The mathematical and methodological backgrounds of the organizational mechanisms discussed are not limited to game theory but also include systems analysis, control theory, operations research, and discrete mathematics. The book includes a set of exercises in each chapter-from simple to advanced-that provide the reader with the understanding required to integrate advanced methods of optimization, game theory, and mechanism design into daily managerial practice.

This is an examination of information policy in environmental sustainability. It covers issues such as information, knowledge and models; environmental regulation; and information policy.

Continuous-Time Systems is a description of linear, nonlinear, time-invariant, and time-varying electronic continuous-time systems. As an assemblage of physical or mathematical components organized and interacting to convert an input signal (also called excitation signal or driving force) to an output signal (also called response signal), an electronic system can be described using different methods offered by the modern systems theory. To make possible for readers to understand systems, the book systematically covers major foundations of the systems theory.

Time-delays are fundamental to understand phenomena in control applications as networked systems, traffic management, control of vibrations, and supply chains. The need for a performance and reliability on these systems has to overcome challenges related to the constraints in the controlled systems. These constraints can be physical, such as input magnitude saturation on actuators, or technological, such as the limited bandwidth in a networked system or the fixed structure in a control architecture, where only a few parameters can be set. This volume provides a wide-ranging collection of methods for the analysis and design of control laws for delay systems with constraints. These methods cover fundamental analytical aspects as, for instance, the stability analysis of Positive Delay systems or the achievable performance of PID controls for delay systems. The book gives valuable material for researchers and graduate students in Automatic Control.

The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies, and prepared them for careers in deep learning, machine learning, and artificial intelligence in top companies in industry and academia. The book begins by covering the foundations of deep learning, followed by key deep learning architectures. Subsequent parts on generative models and reinforcement learning may be used as part of a deep learning course or as part of a course on each topic. The book includes state-of-the-art topics such as Transformers, graph neural networks, variational autoencoders, and deep reinforcement learning, with a broad range of applications. The appendices provide equations for computing gradients in backpropagation and optimization, and best practices in scientific writing and reviewing. The text presents an up-to-date guide to the field built upon clear visualizations using a unified notation and equations, lowering the barrier to entry for the reader. The accompanying website provides complementary code and hundreds of exercises with solutions.

The organizational world today has been characterized in various terms - turmoil, chaos, the age of paradox and unreason. Common to all these characterizations is that the conventional wisdom fails in responding to novel challenges triggered by the pervasive and radical change of organizations. Information, knowledge, information worker and information technology are at the epicenter of these changes and surprises. This book explores new organizational designs, such as, the network and virtual organization from the information perspective. In addition, proposed is a model of the nontraditional organization in which information work evolves around teams that directly serve customers. This model was put on a test, and elements of the nontraditional organization were identified in firms that have been around for quite some time - the public accounting industry, and specifically its technologically most advanced segment. The book aims at transferring experience and facilitating interest for methods of organizing suitable for the information age.

Auction theory is now an important component of an economist's training. The techniques and insights gained from the study of auction theory provide a useful starting point for those who want to venture into the economics of information, mechanism design, and regulatory economics. This book provides a step-by-step, self-contained treatment of the theory of auctions. It allows students and readers with a calculus background to work through all the basic results, covering the basic independent-private-model; the effects of introducing correlation in valuations on equilibrium behaviour and the seller's expected revenue; mechanism design; and the theory of multi-object auctions.

Provides well-written self-contained chapters, including problem sets and exercises, making it ideal for the classroom setting; Introduces applied optimization to the hazardous waste blending problem; Explores linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control and stochastic optimal control; Includes an extensive bibliography at the end of each chapter and an index; GAMS files of case studies for Chapters 2, 3, 4, 5, and 7 are linked to http://www.springer.com/math/book/978-0-387-76634-8; Solutions manual available upon adoptions.

The reach of algebraic curves in cryptography goes far beyond elliptic curve or public key cryptography yet these other application areas have not been systematically covered in the literature. Addressing this gap, Algebraic Curves in Cryptography explores the rich uses of algebraic curves in a range of cryptographic applications, such as secret sharing, frameproof codes, and broadcast encryption. Suitable for researchers and graduate students in mathematics and computer science, this self-contained book is one of the first to focus on many topics in cryptography involving algebraic curves. After supplying the necessary background on algebraic curves, the authors discuss error-correcting codes, including algebraic geometry codes, and provide an introduction to elliptic curves. Each chapter in the remainder of the book deals with a selected topic in cryptography (other than elliptic curve cryptography). The topics covered include secret sharing schemes, authentication codes, frameproof codes, key distribution schemes, broadcast encryption, and sequences. Chapters begin with introductory material before featuring the application of algebraic curves.

This book opens a novel dimension in the 50 year history of mathematical theory of "information" since the birth of Shannon theory. First of all, it introduces, in place of the traditional notion of entropy and mutual information, the completely new and highly unconventional approach of "information-spectrum" as a basic but powerful tool for constructing the general theory of information. Reconstructing step-by-step all the essential major topics in information theory from the viewpoint of such an "information-spectrum", this comprehensive work provides an accessible introduction to the new type of mathematical theory of information that focuses mainly on general nonstationary and /or nonergodic sources and channels, in clear contrast with the traditional theories of information. This book is a new non-traditional theoretical reference for communication professionals and statisticians specializing in information theory.

This volume contains a selection of original contributions from internationally reputed scholars in the field of risk management in socio?technical systems with high hazard potential. Its first major section addresses fundamental psychological and socio?technical concepts in the field of risk perception, risk management and learning systems for safety improvement. The second section deals with the variety of procedures for system safety analysis. It covers strategies of analyzing automation problems and of safety culture as well as the analysis of social dynamics in field settings and of field experiments. Its third part then illustrates the utilization of basic concepts and analytic approaches by way of case studies of designing man?machine systems and in various industrial sectors such as intensive care wards, aviation, offfshore oil drilling and chemical industry. In linking basic theoretical conceptual notions and analytic strategies to detailed case studies in the area of hazardous work organizations the volume differs from and complements more theoretical works such as Human Error (J. Reason, 1990) and more general approaches such as New Technologies and Human Error (J. Rasmussen, K. Duncan, J. Leplat, Eds.)

This monograph focuses on those stochastic quickest detection tasks in disorder problems that arise in the dynamical analysis of statistical data. These include quickest detection of randomly appearing targets, of spontaneously arising effects, and of arbitrage (in financial mathematics). There is also currently great interest in quickest detection methods for randomly occurring intrusions in information systems and in the design of defense methods against cyber-attacks. The author shows that the majority of quickest detection problems can be reformulated as optimal stopping problems where the stopping time is the moment the occurrence of disorder is signaled. Thus, considerable attention is devoted to the general theory of optimal stopping rules, and to its concrete problem-solving methods. The exposition covers both the discrete time case, which is in principle relatively simple and allows step-by-step considerations, and the continuous-time case, which often requires more technical machinery such as martingales, supermartingales, and stochastic integrals. There is a focus on the well-developed apparatus of Brownian motion, which enables the exact solution of many problems. The last chapter presents applications to financial markets. Researchers and graduate students interested in probability, decision theory and statistical sequential analysis will find this book useful.

This book provides a comprehensive guideline on dynamic analysis and vibration control of axially moving systems. First, the mathematical models of various axially moving systems describing the string, beam, belt, and plate models are developed. Accordingly, dynamical issues such as the equilibrium configuration, critical velocity, stability, bifurcation, and further chaotic dynamics are analyzed. Second, this book covers the design of the control schemes based on the hitherto control strategies for axially moving systems: feedback control using the transfer function, variable structure control, control by regulating the axial velocity, wave cancellation approach, boundary control using the Lyapunov method, adaptive control, and hybrid control methods. Finally, according to the contents discussed in the book, specific aspects are outlined for initiating future research endeavors to be undertaken concerning axially moving systems. This book is useful to graduate students and researchers in industrial sectors such as continuous manufacturing systems, transport systems, power transmission systems, and lifting systems not to mention in academia.

The volume that you have before you is the result of a growing realization that fluctuations in nonequilibrium systems playa much more important role than was 1 first believed. It has become clear that in nonequilibrium systems noise plays an active, one might even say a creative, role in processes involving self-organization, pattern formation, and coherence, as well as in biological information processing, energy transduction, and functionality. Now is not the time for a comprehensive summary of these new ideas, and I am certainly not the person to attempt such a thing. Rather, this short introductory essay (and the book as a whole) is an attempt to describe where we are at present and how the viewpoint that has evolved in the last decade or so differs from those of past decades. Fluctuations arise either because of the coupling of a particular system to an ex ternal unknown or "unknowable" system or because the particular description we are using is only a coarse-grained description which on some level is an approxima tion. We describe the unpredictable and random deviations from our deterministic equations of motion as noise or fluctuations. A nonequilibrium system is one in which there is a net flow of energy. There are, as I see it, four basic levels of sophistication, or paradigms, con cerning fluctuations in nature. At the lowest level of sophistication, there is an implicit assumption that noise is negligible: the deterministic paradigm."

This book presents computationally efficient MPC solutions. The classical model predictive control (MPC) approach to control dynamical systems described by the Wiener model uses an inverse static block to cancel the influence of process nonlinearity. Unfortunately, the model's structure is limited, and it gives poor control quality in the case of an imperfect model and disturbances. An alternative is to use the computationally demanding MPC scheme with on-line nonlinear optimisation repeated at each sampling instant. A linear approximation of the Wiener model or the predicted trajectory is found on-line. As a result, quadratic optimisation tasks are obtained. Furthermore, parameterisation using Laguerre functions is possible to reduce the number of decision variables. Simulation results for ten benchmark processes show that the discussed MPC algorithms lead to excellent control quality. For a neutralisation reactor and a fuel cell, essential advantages of neural Wiener models are demonstrated.

Originally published in 1995, Large Deviations for Performance Analysis consists of two synergistic parts. The first half develops the theory of large deviations from the beginning, through recent results on the theory for processes with boundaries, keeping to a very narrow path: continuous-time, discrete-state processes. By developing only what is needed for the applications, the theory is kept to a manageable level, both in terms of length and in terms of difficulty. Within its scope, the treatment is detailed, comprehensive and self-contained. As the book shows, there are sufficiently many interesting applications of jump Markov processes to warrant a special treatment. The second half is a collection of applications developed at Bell Laboratories. The applications cover large areas of the theory of communication networks: circuit switched transmission, packet transmission, multiple access channels, and the M/M/1 queue. Aspects of parallel computation are covered as well including, basics of job allocation, rollback-based parallel simulation, assorted priority queueing models that might be used in performance models of various computer architectures, and asymptotic coupling of processors. These applications are thoroughly analysed using the tools developed in the first half of the book.

This review volume consists of a set of chapters written by leading scholars, most of them founders of their fields. It explores the connections of Randomness to other areas of scientific knowledge, especially its fruitful relationship to Computability and Complexity Theory, and also to areas such as Probability, Statistics, Information Theory, Biology, Physics, Quantum Mechanics, Learning Theory and Artificial Intelligence. The contributors cover these topics without neglecting important philosophical dimensions, sometimes going beyond the purely technical to formulate age old questions relating to matters such as determinism and free will.The scope of Randomness Through Computation is novel. Each contributor shares their personal views and anecdotes on the various reasons and motivations which led them to the study of Randomness. Using a question and answer format, they share their visions from their several distinctive vantage points.

Complex system studies are a growing area of central importance to a wide range of disciplines, ranging from physics to politics and beyond. Adopting this interdisciplinary approach, Systems, Self-Organisation and Information presents and discusses a range of ground-breaking research in complex systems theory. Building upon foundational concepts, the volume introduces a theory of Self-Organization, providing definitions of concepts including system, structure, organization, functionality, and boundary. Biophysical and cognitive approaches to Self-Organization are also covered, discussing the complex dynamics of living beings and the brain, and self-organized adaptation and learning in computational systems. The convergence of Peircean philosophy with the study of Self-Organization also provides an original pathway of research, which contributes to a dialogue between pragmatism, semeiotics, complexity theory, and self-organizing systems. As one of the few interdisciplinary works on systems theory, relating Self-Organization and Information Theory, Systems, Self-Organisation and Information is an invaluable resource for researchers and postgraduate students interested in complex systems theory from related disciplines including philosophy, physics, and engineering.