Facilities increasingly rely on computerized systems to optimize their buildings' systems operation and reduce the costs of maintenance and management. Therefore, facility managers and engineers must rise to the challenge of a new discipline-systems networking and integration-as more and more computerized systems become implemented.

The First International Conference on Signal and Information Processing, Networking and Computers (ICSINC) focuses on the key technologies and challenges of signal and information processing schemes, network application, computer theory and application, etc. Topics in this conference include: Information TheoryThe work contains state-of-the-art research work in the field of information theory from traditional media coding theory, compressing and streaming theory to the latest quantum theory & statistics and big data analytics, featuring the most active research interests in this field. Communication SystemAs a traditional and fundamental aspect of the conference in the field of signal processing and networking, ICSINC publications includes research works focusing on physical layer transmission theory such as MIMO transmission, adaptive antenna theory, and radar and satellite transmission, etc. Research works in the field of SDN, wireless security and 5G related theories are also included. Computer ScienceThe conference also encompasses relevant topics in computer science such as AI & neural network, patter recognition & learning, and medical image processing etc. Other topics such as internet application, biometric & authentication are also included. WorkshopICSINC features workshops hosted by experts from the industrial world. The workshop on Telecom Big Data based Research and Application promotes the in-depth exploration of the most recent research and development findings on the basis of telecom big data. This workshop provides participation of the industry to showcase and commercialize their relevant technology and application as well as products. All materials will be included in publication.

Dreamers may envision our future, but it is the pragmatists who build it. Solve the right problem in the right way, mankind moves forward. Solve the right problem in the wrong way or the wrong problem in the right way, however clever or ingenious the solution, neither credits mankind. Instead, this misfire demonstrates a failure to appreciate a crucial step in pragmatic problem solving: systems integration.

The first book to address the underlying premises of systems integration and how to exposit them in a practical and productive manner, Engineering Systems Integration: Theory, Metrics, and Methods looks at the fundamental nature of integration, exposes the subtle premises to achieve integration, and posits a substantial theoretical framework that is both simple and clear. Offering systems managers and systems engineers the framework from which to consider their decisions in light of systems integration metrics, the book isolates two basic questions, 1) Is there a way to express the interplay of human actions and the result of system interactions of a product with its environment?, and 2) Are there methods that combine to improve the integration of systems? The author applies the four axioms of General Systems Theory (holism, decomposition, isomorphism, and models) and explores the domains of history and interpretation to devise a theory of systems integration, develop practical guidance applying the three frameworks, and formulate the mathematical constructs needed for systems integration.

The practicalities of integrating parts when we build or analyze systems mandate an analysis and evaluation of existing integrative frameworks of causality and knowledge. Integration is not just a word that describes a best practice, an art, or a single discipline. The act of integrating is an approach, operative in all disciplines, in all we see, in all we do.

Drawing on the authors' two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing analytics, and other areas. It also discusses a variety of practical topics that are frequently missing from similar texts. The book begins with the statistical and linear algebra/matrix foundation of modeling methods, from distributions to cumulant and copula functions to Cornish-Fisher expansion and other useful but hard-to-find statistical techniques. It then describes common and unusual linear methods as well as popular nonlinear modeling approaches, including additive models, trees, support vector machine, fuzzy systems, clustering, naive Bayes, and neural nets. The authors go on to cover methodologies used in time series and forecasting, such as ARIMA, GARCH, and survival analysis. They also present a range of optimization techniques and explore several special topics, such as Dempster-Shafer theory. An in-depth collection of the most important fundamental material on predictive analytics, this self-contained book provides the necessary information for understanding various techniques for exploratory data analysis and modeling. It explains the algorithmic details behind each technique (including underlying assumptions and mathematical formulations) and shows how to prepare and encode data, select variables, use model goodness measures, normalize odds, and perform reject inference. Web ResourceThe book's website at www.DataMinerXL.com offers the DataMinerXL software for building predictive models. The site also includes more examples and information on modeling.

Multivariable Feedback Control: Analysis and Design, Second Edition presents a rigorous, yet easily readable, introduction to the analysis and design of robust multivariable control systems. Focusing on practical feedback control and not on system theory in general, this book provides the reader with insights into the opportunities and limitations of feedback control.
Taking into account the latest developments in the field, this fully revised and updated second edition:
* features a new chapter devoted to the use of linear matrix inequalities (LMIs);
* presents current results on fundamental performance limitations introduced by RHP-poles and RHP-zeros;
* introduces updated material on the selection of controlled variables and self-optimizing control;
* provides simple IMC tuning rules for PID control;
* covers additional material including unstable plants, the feedback amplifier, the lower gain margin and a clear strategy for incorporating integral action into LQG control;
* includes numerous worked examples, exercises and case studies, which make frequent use of Matlab and the new Robust Control toolbox.
Multivariable Feedback Control: Analysis and Design, Second Edition is an excellent resource for advanced undergraduate and graduate courses studying multivariable control. It is also an invaluable tool for engineers who want to understand multivariable control, its limitations, and how it can be applied in practice. The analysis techniques and the material on control structure design should prove very useful in the new emerging area of systems biology.
Reviews of the first edition:
"Being rich in insights and practical tips on controller design, the book should also prove to be very beneficial to industrial control engineers, both as a reference book and as an educational tool." Applied Mechanics Reviews
"In summary, this book can be strongly recommended not only as a basic text in multivariable control techniques for graduate and undergraduate students, but also as a valuable source of information for control engineers." International Journal of Adaptive Control and Signal Processing

The arrival of the digital age has created the need to be able to store, manage, and digitally use an ever-increasing amount of video and audio material. Thus, video cataloguing has emerged as a requirement of the times. Video Cataloguing: Structure Parsing and Content Extraction explains how to efficiently perform video structure analysis as well as extract the basic semantic contents for video summarization, which is essential for handling large-scale video data. This book addresses the issues of video cataloguing, including video structure parsing and basic semantic word extraction, particularly for movie and teleplay videos. It starts by providing readers with a fundamental understanding of video structure parsing. It examines video shot boundary detection, recent research on video scene detection, and basic ideas for semantic word extraction, including video text recognition, scene recognition, and character identification. The book lists and introduces some of the most commonly used features in video analysis. It introduces and analyzes the most popular shot boundary detection methods and also presents recent research on movie scene detection as another important and critical step for video cataloguing, video indexing, and retrieval. The authors propose a robust movie scene recognition approach based on a panoramic frame and representative feature patch. They describe how to recognize characters in movies and TV series accurately and efficiently as well as how to use these character names as cataloguing items for an intelligent catalogue. The book proposes an interesting application of highlight extraction in basketball videos and concludes by demonstrating how to design and implement a prototype system of automatic movie and teleplay cataloguing (AMTC) based on the approaches introduced in the book.

This book examines the nature of emergence in context of man-made (i.e. engineered) systems, in general, and system of systems engineering applications, specifically. It investigates emergence to interrogate or explore the domain space from a modeling and simulation perspective to facilitate understanding, detection, classification, prediction, control, and visualization of the phenomenon. Written by leading international experts, the text is the first to address emergence from an engineering perspective. "System engineering has a long and proud tradition of establishing the integrative view of systems. The field, however, has not always embraced and assimilated well the lessons and implications from research on complex adaptive systems. As the editors' note, there have been no texts on Engineering Emergence: Principles and Applications. It is therefore especially useful to have this new, edited book that pulls together so many of the key elements, ranging from the theoretical to the practical, and tapping into advances in methods, tools, and ways to study system complexity. Drs. Rainey and Jamshidi are to be congratulated both for their vision of the book and their success in recruiting contributors with so much to say. Most notable, however, is that this is a book with engineering at its core. It uses modeling and simulation as the language in which to express principles and insights in ways that include tight thinking and rigor despite dealing with notably untidy and often surprising phenomena." - Paul K. Davis, RAND and Frederick S. Pardee RAND Graduate School The first chapter is an introduction and overview to the text. The book provides 12 chapters that have a theoretical foundation for this subject. Includes 7 specific example chapters of how various modeling and simulation paradigms/techniques can be used to investigate emergence in an engineering context to facilitate understanding, detection, classification, prediction, control and visualization of emergent behavior. The final chapter offers lessons learned and the proposed way-ahead for this discipline.

Arduino programming for the absolute beginner, with project-based learning Adventures in Arduino is the beginner's guide to Arduino programming, designed specifically for 11-to 15-year olds who want to learn about Arduino, but don't know where to begin. Starting with the most basic concepts, this book coaches you through nine great projects that gradually build your skills as you experiment with electronics. The easy-to-follow design and clear, plain-English instructions make this book the ideal guide for the absolute beginner, geared toward those with no computing experience. Each chapter includes a video illuminating the material, giving you plenty of support on your journey to electronics programming. Arduino is a cheap, readily available hardware development platform based around an open source, programmable circuit board. Combining these chips with sensors and servos allows you to gain experience with prototyping as you build interactive electronic crafts to bring together data and even eTextiles. Adventures in Arduino gets you started on the path of scientists, programmers, and engineers, showing you the fun way to learn electronic programming and interaction design. * Discover how and where to begin Arduino programming * Develop the skills and confidence to tackle other projects * Make the most of Arduino with basic programming concepts * Work with hardware and software to create interactive electronic devices There's nothing like watching your design come to life and interact with the real world, and Arduino gives you the capability to do that time and again. The right knowledge combined with the right tools can create an unstoppable force of innovation, and your curiosity is the spark that ignites the flame. Adventures in Arduino gets you started on the right foot, but the path is totally up to you.

Most biometric books are either extraordinarily technical for technophiles or extremely elementary for the lay person. Striking a balance between the two, Biometric Technology: Authentication, Biocryptography, and Cloud-Based Architecture is ideal for business, IT, or security managers that are faced with the task of making purchasing, migration, or adoption decisions. It brings biometrics down to an understandable level, so that you can immediately begin to implement the concepts discussed. Exploring the technological and social implications of widespread biometric use, the book considers the science and technology behind biometrics as well as how it can be made more affordable for small and medium-sized business. It also presents the results of recent research on how the principles of cryptography can make biometrics more secure. Covering biometric technologies in the cloud, including security and privacy concerns, the book includes a chapter that serves as a "how-to manual" on procuring and deploying any type of biometric system. It also includes specific examples and case studies of actual biometric deployments of localized and national implementations in the U.S. and other countries. The book provides readers with a technical background on the various biometric technologies and how they work. Examining optimal application in various settings and their respective strengths and weaknesses, it considers ease of use, false positives and negatives, and privacy and security issues. It also covers emerging applications such as biocryptography. Although the text can be understood by just about anybody, it is an ideal resource for corporate-level executives who are considering implementing biometric technologies in their organizations.

Process engineering spans industrial applications in the manufacturing sector from petrochemical to polymer to mineral production. From Plant Data to Process Control covers the most up-to-date techniques and algorithms in the area of process identification (PID) and process control, two key components of process engineering, essential for optimizing production systems. It examines both the theoretical advances in process design and control theory, and a wide variety of implementations. A wide variety of approaches are presented for building models of dynamical systems based on observed data (process identification) and for making the output of a system behave in a desired fashion by properly selecting the process input (process control).

What do financial data prediction, day-trading rule development, and bio-marker selection have in common? They are just a few of the tasks that could potentially be resolved with genetic programming and machine learning techniques. Written by leaders in this field, Applied Genetic Programming and Machine Learning delineates the extension of Genetic Programming (GP) for practical applications. Reflecting rapidly developing concepts and emerging paradigms, this book outlines how to use machine learning techniques, make learning operators that efficiently sample a search space, navigate the search process through the design of objective fitness functions, and examine the search performance of the evolutionary system. It provides a methodology for integrating GP and machine learning techniques, establishing a robust evolutionary framework for addressing tasks from areas such as chaotic time-series prediction, system identification, financial forecasting, classification, and data mining. The book provides a starting point for the research of extended GP frameworks with the integration of several machine learning schemes. Drawing on empirical studies taken from fields such as system identification, finanical engineering, and bio-informatics, it demonstrates how the proposed methodology can be useful in practical inductive problem solving.

Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis. Written by active, distinguished researchers in this area, the book helps readers make informed choices of the most suitable clustering approach for their problem and make better use of existing cluster analysis tools. The book is organized according to the traditional core approaches to cluster analysis, from the origins to recent developments. After an overview of approaches and a quick journey through the history of cluster analysis, the book focuses on the four major approaches to cluster analysis. These approaches include methods for optimizing an objective function that describes how well data is grouped around centroids, dissimilarity-based methods, mixture models and partitioning models, and clustering methods inspired by nonparametric density estimation. The book also describes additional approaches to cluster analysis, including constrained and semi-supervised clustering, and explores other relevant issues, such as evaluating the quality of a cluster. This handbook is accessible to readers from various disciplines, reflecting the interdisciplinary nature of cluster analysis. For those already experienced with cluster analysis, the book offers a broad and structured overview. For newcomers to the field, it presents an introduction to key issues. For researchers who are temporarily or marginally involved with cluster analysis problems, the book gives enough algorithmic and practical details to facilitate working knowledge of specific clustering areas.

Modern Directional Statistics collects important advances in methodology and theory for directional statistics over the last two decades. It provides a detailed overview and analysis of recent results that can help both researchers and practitioners. Knowledge of multivariate statistics eases the reading but is not mandatory. The field of directional statistics has received a lot of attention over the past two decades, due to new demands from domains such as life sciences or machine learning, to the availability of massive data sets requiring adapted statistical techniques, and to technological advances. This book covers important progresses in distribution theory,high-dimensional statistics, kernel density estimation, efficient inference on directional supports, and computational and graphical methods. Christophe Ley is professor of mathematical statistics at Ghent University. His research interests include semi-parametrically efficient inference, flexible modeling, directional statistics and the study of asymptotic approximations via Stein's Method. His achievements include the Marie-Jeanne Laurent-Duhamel prize of the Societe Francaise de Statistique and an elected membership at the International Statistical Institute. He is associate editor for the journals Computational Statistics & Data Analysis and Econometrics and Statistics. Thomas Verdebout is professor of mathematical statistics at Universite libre de Bruxelles (ULB). His main research interests are semi-parametric statistics, high- dimensional statistics, directional statistics and rank-based procedures. He has won an annual prize of the Belgian Academy of Sciences and is an elected member of the International Statistical Institute. He is associate editor for the journals Statistics and Probability Letters and Journal of Multivariate Analysis.

Written by some major contributors to the development of this class of graphical models, Chain Event Graphs introduces a viable and straightforward new tool for statistical inference, model selection and learning techniques. The book extends established technologies used in the study of discrete Bayesian Networks so that they apply in a much more general setting As the first book on Chain Event Graphs, this monograph is expected to become a landmark work on the use of event trees and coloured probability trees in statistics, and to lead to the increased use of such tree models to describe hypotheses about how events might unfold. Features: introduces a new and exciting discrete graphical model based on an event tree focusses on illustrating inferential techniques, making its methodology accessible to a very broad audience and, most importantly, to practitioners illustrated by a wide range of examples, encompassing important present and future applications includes exercises to test comprehension and can easily be used as a course book introduces relevant software packages Rodrigo A. Collazo is a methodological and computational statistician based at the Naval Systems Analysis Centre (CASNAV) in Rio de Janeiro, Brazil. Christiane Goergen is a mathematical statistician at the Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany. Jim Q. Smith is a professor of statistics at the University of Warwick, UK. He has published widely in the field of statistics, AI, and decision analysis and has written two other books, most recently Bayesian Decision Analysis: Principles and Practice (Cambridge University Press 2010).

Based on the many approaches available for dealing with large-scale systems (LSS), Decentralized Control and Filtering in Interconnected Dynamical Systems supplies a rigorous framework for studying the analysis, stability, and control problems of LSS. Providing an overall assessment of LSS theories, it addresses model order reduction, parametric uncertainties, time delays, and control estimator gain perturbations. Taking readers on a guided tour through LSS, the book examines recent trends and approaches and reviews past methods and results from a contemporary perspective. It traces the progress of research along three eras: 1. Fundamental era in which the basic conceptual frameworks, major ideas, and operational methodologies are laid down 2. Contemporary era in which several of the workable methods and techniques are established and applied to many application areas 3. Advanced era in which different high-level schemes and configurations are being developed to meet accelerated technological advancements Focusing on robust, reliable, and/or resilient decentralized design methods based on linear matrix inequalities framework, the author offers suggestions for improvements to current approaches. He addresses the dominating sources of difficulties due to dimensionality, information structure constraints, uncertainties, and time delays. Drawing attention to key issues, the text is supported by proofs, efficient computational methods, end-of-chapter problems, and approximately 1,300 equations.

Describing state-of-the-art solutions in distributed system architectures, Integration of Services into Workflow Applications presents a concise approach to the integration of loosely coupled services into workflow applications. It discusses key challenges related to the integration of distributed systems and proposes solutions, both in terms of theoretical aspects such as models and workflow scheduling algorithms, and technical solutions such as software tools and APIs. The book provides an in-depth look at workflow scheduling and proposes a way to integrate several different types of services into one single workflow application. It shows how these components can be expressed as services that can subsequently be integrated into workflow applications. The workflow applications are often described as acyclic graphs with dependencies which allow readers to define complex scenarios in terms of basic tasks. Presents state-of-the-art solutions to challenges in multi-domain workflow application definition, optimization, and execution Proposes a uniform concept of a service that can represent executable components in all major distributed software architectures used today Discusses an extended model with determination of data flows among parallel paths of a workflow application Since workflow applications often process big data, the book explores the dynamic management of data with various storage constraints during workflow execution. It addresses several practical problems related to data handling, including data partitioning for parallel processing next to service selection and scheduling, processing data in batches or streams, and constraints on data sizes that can be processed at the same time by service instances. Illustrating several workflow applications that were proposed, implemented, and benchmarked in a real BeesyCluster environment, the book includes templates for

This book provides an extended overview and fundamental knowledge in industrial automation, while building the necessary knowledge level for further specialization in advanced concepts of industrial automation. It covers a number of central concepts of industrial automation, such as basic automation elements, hardware components for automation and process control, the latch principle, industrial automation synthesis, logical design for automation, electropneumatic automation, industrial networks, basic programming in PLC, and PID in the industry.

Widely used across industrial and manufacturing automation, Programmable Logic Controllers (PLCs) perform a broad range of electromechanical tasks with multiple input and output arrangements, designed specifically to cope in severe environmental conditions such as automotive and chemical plants. Programmable Logic Controllers: A Practical Approach using CoDeSys is a hands-on guide to rapidly gain proficiency in the development and operation of PLCs based on the IEC 61131-3 standard. Using the freely-available* software tool CoDeSys, which is widely used in industrial design automation projects, the author takes a highly practical approach to PLC design using real-world examples. The design tool, CoDeSys, also features a built in simulator/soft PLC enabling the reader to undertake exercises and test the examples. Key features: * Introduces to programming techniques using IEC 61131-3 guidelines in the five PLC-recognised programming languages. * Focuses on a methodical approach to programming, based on Boolean algebra, flowcharts, sequence diagrams and state-diagrams. * Contains a useful methodology to solve problems, develop a structured code and document the programming code. * Covers I/O like typical sensors, signals, signal formats, noise and cabling. * Features Power Point slides covering all topics, example programs and solutions to end-of-chapter exercises via companion website. No prior knowledge of programming PLCs is assumed making this text ideally suited to electronics engineering students pursuing a career in electronic design automation. Experienced PLC users in all fields of manufacturing will discover new possibilities and gain useful tips for more efficient and structured programming. * Register at www.codesys.com www.wiley.com/go/hanssen/logiccontrollers

As a powerful approach to data reasoning, rough set theory has proven to be invaluable in knowledge acquisition, decision analysis and forecasting, and knowledge discovery. With the ability to enhance the advantages of other soft technology theories, hybrid rough set theory is quickly emerging as a method of choice for decision making under uncertain conditions.

Keeping the complicated mathematics to a minimum, Hybrid Rough Sets and Applications in Uncertain Decision-Making provides a systematic introduction to the methods and application of the hybridization for rough set theory with other related soft technology theories, including probability, grey systems, fuzzy sets, and artificial neural networks. It also:

• Addresses the variety of uncertainties that can arise in the practical application of knowledge representation systems
• Unveils a novel hybrid model of probability and rough sets
• Introduces grey variable precision rough set models
• Analyzes the advantages and disadvantages of various practical applications

The authors examine the scope of application of the rough set theory and discuss how the combination of variable precision rough sets and dominance relations can produce probabilistic preference rules out of preference attribute decision tables of preference actions. Complete with numerous cases that illustrate the specific application of hybrid methods, the text adopts the latest achievements in the theory, method, and application of rough sets.

The first-ever complete guide to project management for facilities managers covers: how to write specifications, evaluate bids, and solve problems; all control and automation systems for new and retrofit buildings; cost-effective, energy-efficient solutions for all HVAC systems; and has complete coverage of single-building systems as well as multibuilding complexes.

A Firsthand Look at the Role of the Industrial Engineer The industrial engineer helps decide how best to utilize an organization's resources to achieve company goals and objectives. Introduction to Industrial Engineering, Second Edition offers an in-depth analysis of the industrial engineering profession. While also providing a historical perspective chronicling the development of the profession, this book describes the standard duties performed, the tools and terminologies used, and the required methods and processes needed to complete the tasks at hand. It also defines the industrial engineer's main areas of operation, introduces the topic of information systems, and discusses their importance in the work of the industrial engineer. The authors explain the information system concept, and the need for integrated processes, supported by modern information systems. They also discuss classical organizational structures (functional organization, project organization, and matrix organization), along with the advantages and disadvantages of their use. The book includes the technological aspects (data collection technologies, databases, and decision-support areas of information systems), the logical aspects (forecasting models and their use), and aspects of principles taken from psychology, sociology, and ergonomics that are commonly used in the industry. What's New in this Edition: The second edition introduces fields that are now becoming a part of the industrial engineering profession, alongside conventional areas (operations management, project management, quality management, work measurement, and operations research). In addition, the book: Provides an understanding of current pathways for professional development Helps students decide which area to specialize in during the advanced stages of their studies Exposes students to ergonomics used in the context of workspace design Presents key factors in human resource management Describes frequently used methods of teaching in the field Covers basic issues relative to ergonomics and human-machine interface Introduces the five basic processes that exist in many organizations Introduction to Industrial Engineering, Second Edition establishes industrial engineering as the organization of people and resources, describes the development and nature of the profession, and is easily accessible to anyone needing to learn the basics of industrial engineering. The book is an indispensable resource for students and industry professionals.

Many types of security technologies are currently in use, with biometrics being one of the latest and most cutting-edge forms that has been produced for mass application. Biometrics, while intriguing, is often broached with hesitation and poor understanding. Adopting Biometric Technology: Challenges and Solutions advocates increased implementation of biometric technology areas of the world where it has been least accepted, particularly in the United States. This book looks at several specific applications of biometric technology, challenging issues that have obstructed the use of biometrics in security and offering realistic solutions for increasing its worldwide utilization. It is divided into three sections, with the first discussing societal barriers against the adoption of biometric technology in security. The second section presents case studies of specific applications, such as e-passports and e-voting, that have already been implemented and could be expanded into regions where usage is low. The third section lays out a case for the general practicality and value that biometrics offers to relevant business sectors, including the benefits of implementing the currently controversial technology in place of the conventional forms of verification. While biometric technology has been poorly accepted and adopted in the United States as well as other developed nations, it is already a popular tool in developing nations in Asia, Africa, and Eastern Europe. Adopting Biometric Technology examines the societal resistance hindering the broader usage of biometrics and provides practical solutions for overcoming those barriers while showing how its increased application would be overall advantageous.

First published in 1999, this volume examined how increasing cockpit automation in commercial fleets across the world has had a profound impact on the cognitive work that is carried out on the flight deck. Pilots have largely been transformed into supervisory controllers, managing a suite of human and automated resources. Operational and training requirements have changed, and the potential for human error and system breakdown has shifted. This compelling book critically examines how airlines, regulators, educators and manufacturers cope with these and other consequences of advanced aircraft automation.

From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dynamic systems, its practical value was limited by algorithms that lacked the capacity to scale up to realistic problems. However, in recent years, dramatic developments in Reinforcement Learning (RL), the model-free counterpart of DP, changed our understanding of what is possible. Those developments led to the creation of reliable methods that can be applied even when a mathematical model of the system is unavailable, allowing researchers to solve challenging control problems in engineering, as well as in a variety of other disciplines, including economics, medicine, and artificial intelligence. Reinforcement Learning and Dynamic Programming Using Function Approximators provides a comprehensive and unparalleled exploration of the field of RL and DP. With a focus on continuous-variable problems, this seminal text details essential developments that have substantially altered the field over the past decade. In its pages, pioneering experts provide a concise introduction to classical RL and DP, followed by an extensive presentation of the state-of-the-art and novel methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, they elaborate on their work with illustrative examples and insightful comparisons. Three individual chapters are dedicated to representative algorithms from each of the major classes of techniques: value iteration, policy iteration, and policy search. The features and performance of these algorithms are highlighted in extensive experimental studies on a range of control applications. The recent development of applications involving complex systems has led to a surge of interest in RL and DP methods and the subsequent need for a quality resource on the subject. For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work. Access the authors' website at www.dcsc.tudelft.nl/rlbook/ for additional material, including computer code used in the studies and information concerning new developments.

Currently, many smart materials exhibit one or multifunctional capabilities that are being effectively exploited in various engineering applications, but these are only a hint of what is possible. Newer classes of smart materials are beginning to display the capacity for self-repair, self-diagnosis, self-multiplication, and self-degradation. Ultimately, what will make them practical and commercially viable are control devices that provide sufficient speed and sensitivity. While there are other candidates, piezoelectric actuators and sensors are proving to be the best choice.
Piezoelectric Actuators: Control Applications of Smart Materials details the authors? cutting-edge research and development in this burgeoning area. It presents their insights into optimal control strategies, reflecting their latest collection of refereed international papers written for a number of prestigious journals.

Piezoelectric materials are incorporated in devices used to control vibration in flexible structures. Applications include beams, plates, and shells; sensors and actuators for cabin noise control; and position controllers for structural systems such as the flexible manipulator, engine mount, ski, snowboard, robot gripper, ultrasonic motors, and various type of sensors including accelerometer, strain gage, and sound pressure gages.

The contents and design of this book make it useful as a professional reference for scientists and practical engineers who would like to create new machines or devices featuring smart material actuators and sensors integrated with piezoelectric materials. With that goal in mind, this book:

• Describes the piezoelectric effect from a microscopic point of view
• Addresses vibration control for flexible structures and other methods that use active mount
• Covers control of flexible robotic manipulators
• Discusses application to fine-motion and hydraulic control systems
• Explores piezoelectric shunt technology

This book is exceptionally valuable as a reference for professional engineers working at the forefront of numerous industries. With its balanced presentation of theory and application, it will also be of special interest to graduate students studying control methodology.