The author has spent approximately 50 years in the field of systems engineering. This Focus book provides a "looking back" at his 50-year run and the lessons he learned and would like to share with other engineers, so they can use these lessons in their day-to-day work in systems engineering and related fields. The book is written from a systems engineering perspective. It offers 50 lessons learned working for a variety of different companies, which can be used across many other engineering fields. The book will be of interested to students and engineers across many fields, as well as students and engineers working in business and management fields.

Thanks to rapid technological developments in terms of Computational Intelligence, smart tools have been playing active roles in daily life. It is clear that the 21st century has brought about many advantages in using high-level computation and communication solutions to deal with real-world problems; however, more technologies bring more changes to society. In this sense, the concept of smart cities has been a widely discussed topic in terms of society and Artificial Intelligence-oriented research efforts. The rise of smart cities is a transformation of both community and technology use habits, and there are many different research orientations to shape a better future. The objective of this book is to focus on Explainable Artificial Intelligence (XAI) in smart city development. As recently designed, advanced smart systems require intense use of complex computational solutions (i.e., Deep Learning, Big Data, IoT architectures), the mechanisms of these systems become 'black-box' to users. As this means that there is no clear clue about what is going on within these systems, anxieties regarding ensuring trustworthy tools also rise. In recent years, attempts have been made to solve this issue with the additional use of XAI methods to improve transparency levels. This book provides a timely, global reference source about cutting-edge research efforts to ensure the XAI factor in smart city-oriented developments. The book includes both positive and negative outcomes, as well as future insights and the societal and technical aspects of XAI-based smart city research efforts. This book contains nineteen contributions beginning with a presentation of the background of XAI techniques and sustainable smart-city applications. It then continues with chapters discussing XAI for Smart Healthcare, Smart Education, Smart Transportation, Smart Environment, Smart Urbanization and Governance, and Cyber Security for Smart Cities.

The book begins with an overview of automation history and followed by chapters on PLC, DCS, and SCADA -describing how such technologies have become synonymous in process instrumentation and control. The book then introduces the niche of Fieldbuses in process industries. It then goes on to discuss wireless communication in the automation sector and its applications in the industrial arena. The book also discusses theall-pervading IoT and its industrial cousin,IIoT, which is finding increasing applications in process automation and control domain. The last chapter introduces OPC technology which has strongly emerged as a defacto standard for interoperable data exchange between multi-vendor software applications and bridges the divide between heterogeneous automation worlds in a very effective way. Key features: Presents an overall industrial automation scenario as it evolved over the years Discusses the already established PLC, DCS, and SCADA in a thorough and lucid manner and their recent advancements Provides an insight into today's industrial automation field Reviews Fieldbus communication and WSNs in the context of industrial communication Explores IIoT in process automation and control fields Introduces OPC which has already carved out a niche among industrial communication technologies with its seamless connectivity in a heterogeneous automation world Dr. Chanchal Dey is Associate Professor in the Department of Applied Physics, Instrumentation Engineering Section, University of Calcutta. He is a reviewer of IEEE, Elsevier, Springer, Acta Press, Sage, and Taylor & Francis Publishers. He has more than 80 papers in international journals and conference publications. His research interests include intelligent process control using conventional, fuzzy, and neuro-fuzzy techniques. Dr. Sunit Kumar Sen is an ex-professor, Department of Applied Physics, Instrumentation Engineering Section, University of Calcutta. He was a coordinator of two projects sponsored by AICTE and UGC, Government of India. He has published around70 papers in international and national journals and conferences and has published three books - the last one was published by CRC Press in 2014. He is a reviewer of Measurement, Elsevier. His field of interest is new designs of ADCs and DACs.

This book presents theoretical and practical findings on the state estimation, diagnosis and control of complex systems, especially in the mathematical form of descriptor systems. The research is fully motivated by real-world applications (i.e., Barcelona's water distribution network), which require control systems capable of taking into account their specific features and the limits of operations in the presence of uncertainties stemming from modeling errors and component malfunctions. Accordingly, the book first introduces a complete set-based framework for explicitly describing the effects of uncertainties in the descriptor systems discussed. In turn, this set-based framework is used for state estimation and diagnosis. The book also presents a number of application results on economic model predictive control from actual water distribution networks and smart grids. Moreover, the book introduces a fault-tolerant control strategy based on virtual actuators and sensors for such systems in the descriptor form.

This book examines key issues in ensuring the operational reliability of energy facilities. In this regard, it analyzes mathematical models of diagnostic signals that arise during the operation of power equipment; reviews the main findings of research into their characteristics; presents diagnostics methods for selected types of electric power and heat engineering equipment; and covers a range of diagnostic and monitoring systems and devices for power equipment. Given its scope, the book offers a valuable resource for researchers, engineers and specialists, as well as instructors and graduate students at institutions of higher learning.

Discusses wide range of magnetic field assisted finishing processes in a comprehensive manner. Covers different process parameters by considering their effects on the finishing output. Provides process limitations to achieve optimal yield. Covers numerical explanations for better selection of process parameters. Discusses automation of processes with state-of-the-art technologies.

This is a comprehensive book on how to make complex decisions on energy systems problems involving different technologies, environmental effects, costs, benefits, risks, and safety issues. Using Industrial and Systems Engineering techniques for decision-making in Energy Systems, the book provides the background knowledge and methods to incorporate multiple criteria involved in solving energy system problems. It offers methods, examples, and case studies illustrating applications. Decision-Making in Energy Systems discusses subjective as well as objective methods, approaches, and techniques taken from the systems and industrial engineering domain and puts them to use in solving energy systems problems. It uses an integrated approach by including effects of all technical, economic, environmental, and safety considerations as well as costs and risks. The book is specially designed for practicing engineers from industrial/systems engineering who work in energy systems engineering industries. Aimed at graduate students, researchers, and managers involved in various energy generating, distributing, and consuming companies, the book helps the reader to understand, evaluate, and decide on solutions to their energy-related problems.

Provides a comprehensive review on new swarm intelligence Offers practical implementation of PSO with MATLAB code Presents statistical analysis techniques so that researchers can analyze their own experiment design Discusses swarm intelligence algorithms in social sector and oil and gas industries Covers recent findings and the implementation techniques to Machine Learning

This edited book analyses and discusses the current issues of integration of wind energy systems in the power systems. It collects recent studies in the area, focusing on numerous issues including unbalanced grid voltages, low-voltage ride-through and voltage stability of the grid. It also explores the impact of the emerging technologies of wind turbines and power converters in the integration of wind power systems in power systems. This book utilizes the editors' expertise in the energy sector to provide a comprehensive text that will be of interest to researchers, graduate students and industry professionals.

Considers both time-domain and frequency domain robust design techniques of partial differential systems Illustrates both theoretical robust design techniques and practical applications Discusses partial differential systems with both Dirichlet and Neuman boundary conditions in robust design procedure Addresses deterministic and stochastic partial differential systems Explores theoretical mathematical background, robust signal processing design, robust control system design and robust biological system design with application

The book intends to cover various problematic aspects of emerging smart computing and self-adapting technologies comprising of machine learning, artificial intelligence, deep learning, robotics, cloud computing, fog computing, data mining algorithms, including emerging intelligent and smart applications related to these research areas. Further coverage includes implementation of self-adaptation architecture for smart devices, self-adaptive models for smart cities and self-driven cars, decentralized self-adaptive computing at the edge networks, energy-aware AI-based systems, M2M networks, sensors, data analytics, algorithms and tools for engineering self-adaptive systems, and so forth. Acts as guide to Self-healing and Self-adaptation based fully automatic future technologies Discusses about Smart Computational abilities and self-adaptive systems Illustrates tools and techniques for data management and explains the need to apply, and data integration for improving efficiency of big data Exclusive chapter on the future of self-stabilizing and self-adaptive systems of systems Covers fields such as automation, robotics, medical sciences, biomedical and agricultural sciences, healthcare and so forth This book is aimed researchers and graduate students in machine learning, information technology, and artificial intelligence.

Examines all the major types of mechatronic systems used in railway applications Surveys rail vehicle mechatronic design processes with practical sources and references Outlines modelling approaches for rail vehicles, from concept to finishined prototype Analyzes system integration of complex railway mechatronic systems Presents numerical experiments and mechatronic models with railway transport applications

The book emphasizes the predictive models of Big Data, Genetic Algorithm, and IoT with a case study. The book illustrates the predictive models with integrated fuel consumption models for smart and safe traveling. The text is a coordinated amalgamation of research contributions and industrial applications in the field of Intelligent Transportation Systems. The advanced predictive models and research results were achieved with the case studies, deployed in real transportation environments. Features: Provides a smart traffic congestion avoidance system with an integrated fuel consumption model. Predicts traffic in short-term and regular. This is illustrated with a case study. Efficient Traffic light controller and deviation system in accordance with the traffic scenario. IoT based Intelligent Transport Systems in a Global perspective. Intelligent Traffic Light Control System and Ambulance Control System. Provides a predictive framework that can handle the traffic on abnormal days, such as weekends, festival holidays. Bunch of solutions and ideas for smart traffic development in smart cities. This book focuses on advanced predictive models along with offering an efficient solution for smart traffic management system. This book will give a brief idea of the available algorithms/techniques of big data, IoT, and genetic algorithm and guides in developing a solution for smart city applications. This book will be a complete framework for ITS domain with the advanced concepts of Big Data Analytics, Genetic Algorithm and IoT. This book is primarily aimed at IT professionals. Undergraduates, graduates and researchers in the area of computer science and information technology will also find this book useful.

This book investigates statistical observables for anomalous and nonergodic dynamics, focusing on the dynamical behaviors of particles modelled by non-Brownian stochastic processes in the complex real-world environment. Statistical observables are widely used for anomalous and nonergodic stochastic systems, thus serving as a key to uncover their dynamics. This study explores the cutting edge of anomalous and nonergodic diffusion from the perspectives of mathematics, computer science, statistical and biological physics, and chemistry. With this interdisciplinary approach, multiple physical applications and mathematical issues are discussed, including stochastic and deterministic modelling, analyses of (stochastic) partial differential equations (PDEs), scientific computations and stochastic analyses, etc. Through regularity analysis, numerical scheme design and numerical experiments, the book also derives the governing equations for the probability density function of statistical observables, linking stochastic processes with PDEs. The book will appeal to both researchers of electrical engineering expert in the niche area of statistical observables and stochastic systems and scientists in a broad range of fields interested in anomalous diffusion, especially applied mathematicians and statistical physicists.

This book is for anyone who wants to gain an understanding of Blockchain technology and its potential. The book is research-oriented and covers different verticals of Blockchain technology. It discusses the characteristics and features of Blockchain, includes techniques, challenges, and future trends, along with case studies for deeper understanding. Blockchain Technology: Exploring Opportunities, Challenges, and Applications covers the core concepts related to Blockchain technology starting from scratch. The algorithms, concepts, and application areas are discussed according to current market trends and industry needs. It presents different application areas of industry and academia and discusses the characteristics and features of this technology. It also explores the challenges and future trends and provides an understanding of new opportunities. This book is for anyone at the beginner to intermediate level that wants to learn about the core concepts related to Blockchain technology.

Takes the reader on a journey across three broad developments in safety science Focuses on the individual including human error, risk, and the role of cognition in human performance Includes research in safety science that uses organizations as the basic unit of analysis Discusses questions about organizational decision making and the characteristics that dispose towards or against organizational failure Introduces perspectives based on systems science that address issues that arise out of complexity and interdependence

This book provides cutting edge insight into systems dynamics, as applied to engineering systems including control systems. The coverage is intended for both students and practicing engineers. Updated throughout in the second edition, it serves as a firm foundation to develop expertise in design, simulation, prototyping, control, instrumentation, experimentation, and performance analysis.

Providing a clear discussion of system dynamics, the book enables students and professionals to both understand and subsequently model mechanical, thermal, fluid, electrical, and multi-physics systems in a systematic, unified and integrated manner, which leads to a "unique" model. Concepts of through-and across-variables are introduced and applied, alongside tools of modeling and model-representation such as linear graphs and block diagrams. The book uses and illustrates popular software tools such as SIMULINK, throughout, and additionally makes use of innovative worked examples and case studies, alongside problems and exercises based on practical situations.

The book is a crucial companion to undergraduate and postgraduate mechanical engineering and other engineering students, alongside professionals in the field. Complete solutions to end-of-chapter problems are provided in a Solutions Manual that is available to instructors.

Table of Contents

Chapter 1 Introduction to Modeling

Chapter 2 Basic Model Elements

Chapter 3 Analytical Modeling

Chapter 4 Model Linearization

Chapter 5 Linear Graphs

Chapter 6 Frequency-Domain Models

Chapter 7 Transfer-Function Linear Graphs

Appendix A: Graph-Tree Concepts for Linear Graphs

Appendix B: MATLAB Toolbox for Linear Graphs

This book bridges fundamental gaps between control theory and formal methods. Although it focuses on discrete-time linear and piecewise affine systems, it also provides general frameworks for abstraction, analysis, and control of more general models. The book is self-contained, and while some mathematical knowledge is necessary, readers are not expected to have a background in formal methods or control theory. It rigorously defines concepts from formal methods, such as transition systems, temporal logics, model checking and synthesis. It then links these to the infinite state dynamical systems through abstractions that are intuitive and only require basic convex-analysis and control-theory terminology, which is provided in the appendix. Several examples and illustrations help readers understand and visualize the concepts introduced throughout the book.

Hydroelectric power stations are a major source of electricity around the world; understanding their dynamics is crucial to achieving good performance. The electrical power generated is normally controlled by individual feedback loops on each unit. The reference input to the power loop is the grid frequency deviation from its set point, thus structuring an external frequency control loop. The book discusses practical and well-documented cases of modelling and controlling hydropower stations, focused on a pumped storage scheme based in Dinorwig, North Wales. These accounts are valuable to specialist control engineers who are working in this industry. In addition, the theoretical treatment of modern and classic controllers will be useful for graduate and final year undergraduate engineering students. This book reviews SISO and MIMO models, which cover the linear and nonlinear characteristics of pumped storage hydroelectric power stations. The most important dynamic features are discussed. The verification of these models by hardware in the loop simulation is described. To show how the performance of a pumped storage hydroelectric power station can be improved, classical and modern controllers are applied to simulated models of Dinorwig power plant, that include PID, Fuzzy approximation, Feed-Forward and Model Based Predictive Control with linear and hybrid prediction models.

This book addresses a special topic in the field of nonlinear dynamical systems, develops a new research direction of surface chaos and surface bifurcation. It provides a clear watershed for original nonlinear chaos and bifurcation research. The novel content of this book makes nonlinear system research more systematical and personalized. This book introduces the chaos and bifurcation behavior of surface dynamics in the sense of Li Yorke, the basic properties, Lyapunov exponent and Feigenbaum constant of nonlinear behavior of surface, and obtained the wave behavior of chaotic process in surface motion, the control of surface chaos and bifurcation, and the wide application of surface chaos in engineering technology. Through this book, readers can obtain more abundant and novel contents about surface chaos and surface bifurcation than the existing mixed fitting bifurcation of plane curve and space curve, which can also expand the realm and vision of research.

An electric machine is a device that converts mechanical energy into electrical energy or vice versa. It can take the form of an electric generator, electric motor, or transformer. Electric generators produce virtually all electric power we use all over the world. Electric machine blends the three major areas of electrical engineering: power, control and power electronics. This book presents the relation of power quantities for the machine as the current, voltage power flow, power losses, and efficiency. This book will provide a good understanding of the behavior and its drive, beginning with the study of salient features of electrical dc and ac machines.

Marine Systems Identification, Modelling and Control is a concise, standalone resource covering the theory and practice of dynamic systems and control for marine engineering students and professionals.

Developed from a distance learning CPD course on marine control taught by the authors, the book presents the essentials of the subject, including system representation and transfer, feedback control and closed loop stability. Simulation code and worked examples are provided for both Scilab and MATLAB, making it suitable for both those without access to expensive software and those using MATLAB in a professional setting.

Marine Systems Identification, Modelling and Control considers the key topics without superfluous detail and is illustrated with marine industry examples, providing a marine-focused alternative to more general control engineering tomes that lack context and are intended for broader control study or work.
Concise and practical, covering the relevant theory without excessive detail alongside industry-specific examples and applications for marine engineering students and professionals.
Clearly presents the key topics of the subject, including system representation and transfer, feedback control and closed loop stability, making it ideal for self-study or reference.
Simulation code and worked examples using Scilab and MATLAB provided on the book s companion website."

The book focuses on symplectic pseudospectral methods for nonlinear optimal control problems and their applications. Both the fundamental principles and engineering practice are addressed. Symplectic pseudospectral methods for nonlinear optimal control problems with complicated factors (i.e., inequality constraints, state-delay, unspecific terminal time, etc.) are solved under the framework of indirect methods. The methods developed here offer a high degree of computational efficiency and accuracy when compared with popular direct pseudospectral methods. The methods are applied to solve optimal control problems arising in various engineering fields, particularly in path planning problems for autonomous vehicles. Given its scope, the book will benefit researchers, engineers and graduate students in the fields of automatic control, path planning, ordinary differential equations, etc.

Discusses core concepts and principles of deep learning in gaming and animation with applications. Covers application of neural networks for intelligent video game character. Discusses automated video generation and real time animation. Covers technological advancements in virtual reality (VR), and augmented reality (AR).

With the rapidly advancing fields of Data Analytics and Computational Statistics, it's important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.