An original, systematic-solution approach to uncertain nonlinear systems control and modeling using fuzzy equations and fuzzy differential equations There are various numerical and analytical approaches to the modeling and control of uncertain nonlinear systems. Fuzzy logic theory is an increasingly popular method used to solve inconvenience problems in nonlinear modeling. Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number presents a structured approach to the control and modeling of uncertain nonlinear systems in industry using fuzzy equations and fuzzy differential equations. The first major work to explore methods based on neural networks and Bernstein neural networks, this innovative volume provides a framework for control and modeling of uncertain nonlinear systems with applications to industry. Readers learn how to use fuzzy techniques to solve scientific and engineering problems and understand intelligent control design and applications. The text assembles the results of four years of research on control of uncertain nonlinear systems with dual fuzzy equations, fuzzy modeling for uncertain nonlinear systems with fuzzy equations, the numerical solution of fuzzy equations with Z-numbers, and the numerical solution of fuzzy differential equations with Z-numbers. Using clear and accessible language to explain concepts and principles applicable to real-world scenarios, this book: Presents the modeling and control of uncertain nonlinear systems with fuzzy equations and fuzzy differential equations Includes an overview of uncertain nonlinear systems for non-specialists Teaches readers to use simulation, modeling and verification skills valuable for scientific research and engineering systems development Reinforces comprehension with illustrations, tables, examples, and simulations Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number is suitable as a textbook for advanced students, academic and industrial researchers, and practitioners in fields of systems engineering, learning control systems, neural networks, computational intelligence, and fuzzy logic control.

The text provides a comprehensive overview of the design aspects of the internet of things devices and covers the fundamentals of big data and data science. It explores various scenarios such as what are the middleware and frameworks available and how to build a stable, standards-based, and Secure internet of things device. It discusses important concepts including embedded programming techniques, machine-to-machine architecture, and the internet of things for smart city applications. It will serve as an ideal design book for professionals, senior undergraduate, and graduate students in the fields including electrical engineering, electronics and communication engineering, and computer engineering. The book- Covers applications and architecture needed to deliver solutions to end customers and readers. Discusses practical aspects of implementing the internet of things in diverse areas including manufacturing, and software development. Highlights big data concepts and embedded programming techniques. Presents technologies including machine to machine, integrated sensors, and radio-frequency identification. Introduces global system for mobile communication and precise details of standards based on internet of things architecture models. The book focuses on practical design aspects such as how to finalize a processor integrated circuit, which operating system to use, etc. in a single volume. It will serve as an ideal text for professionals, senior undergraduate, and graduate students in diverse engineering domains including electrical, electronics and communication, computer.

This book discusses various methods for designing different kinds of observers, such as the Luenberger observer, unknown input observers, discontinuous observers, sliding mode observers, observers for impulsive systems, observers for nonlinear Takagi-Sugeno fuzzy systems, and observers for electrical machines. A hydraulic process system and a renewable energy system are provided as examples of applications.

This book presents the select proceedings of Control Instrumentation and System Conference, (CISCON 2020) held at Manipal Institute of Technology, MAHE, Manipal. It examines a wide spectrum covering the latest trends in the fields of instrumentation, sensors and systems, and industrial automation and control. The topics covered include image and signal processing, robotics, renewable energy, power systems and power drives, performance attributes of MEMS, multi-sensor data fusion, machine learning, optimization techniques, process control, safety monitoring, safety critical control, supervisory control, system modeling and virtual instrumentation. The book is a valuable reference for researchers and professionals interested in sensors, adaptive control, automation and control and allied fields.

This book discusses control units represented by the model of a finite state machine (FSM). It contains various original methods and takes into account the peculiarities of field-programmable gate arrays (FPGA) chips and a FSM model. It shows that one of the peculiarities of FPGA chips is the existence of embedded memory blocks (EMB). The book is devoted to the solution of problems of logic synthesis and reduction of hardware amount in control units. The book will be interesting and useful for researchers and PhD students in the area of Electrical Engineering and Computer Science, as well as for designers of modern digital systems.

Smart shipping is a future method for transporting ocean cargo and exploring the resources of oceans for medical drugs, food, energy resources, and other products. A smart ship is an integration of shipping with many fields such as fishing, manufacturing, navigation, communication, computing, control, sensing, etc., to provide better shipping and services. The purpose of this edited book is to provide state-of-the-art approaches and novel technologies for smart ships, covering a range of topics in these areas so that it will be an excellent reference book for the researchers, students, and professionals in these areas. It presents the fundamental technologies needed to build smart ships, and gives a clear explanation of them. This book will serve as a good reference for researchers to know the state of the art and to discover uncovered territory and develop new applications, as well as being a guideline for building future smart ships. Yang Xiao is a Full Professor in the Department of Computer Science at the University of Alabama, Tuscaloosa, Alabama, USA. Tieshan Li is a Full Professor in the School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.

1. Understand the audit culture, challenges, and benefits of the CAE role in digitally transforming business environment in smart cities 2. Identify ways to advance the value of Internal Audit in digital era 3. Use and control the resources of the city efficiently, and to ensure that the system units work properly in an integrated way.

This book is designed as a reference book and presents a systematic approach to analyze evolutionary and nature-inspired population-based search algorithms. Beginning with an introduction to optimization methods and algorithms and various enzymes, the book then moves on to provide a unified framework of process optimization for enzymes with various algorithms. The book presents current research on various applications of machine learning and discusses optimization techniques to solve real-life problems. The book compiles the different machine learning models for optimization of process parameters for production of industrially important enzymes. The production and optimization of various enzymes produced by different microorganisms are elaborated in the book It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making Covers the best-performing methods and approaches for optimization sustainable enzymes production with AI integration in a real-time environment Featuring valuable insights, the book helps readers explore new avenues leading towards multidisciplinary research discussions The book is aimed primarily at advanced undergraduates and graduates studying machine learning, data science and industrial biotechnology. Researchers and professionals will also find this book useful.

One of the most difficult, yet important, questions regarding projects is "What advantages will this project create for the investors and key stakeholders?" Projects and programs should be treated as investments. This means that the focus of projects shifts from delivering within the triple constraints (time-cost-quality) towards some of the more fundamental questions: What is the purpose of this investment? What are the specific advantages expected? Are these benefits worth the investment? Implementing Project and Program Benefit Management is written for executives and practitioners within the portfolio, program, and project environment. It guides them through the important work that must be addressed as the investment progresses towards the realization of benefits. The processes discussed cover the strategic elements of benefits realization as well as the more detailed requirements, which are the domain of the program delivery teams and the operational users. Using real cases to explain complex situations, operational teams and wider groups of stakeholders, including communities affected by infrastructure projects, will be able to engage in the conversation with the sponsors and delivery teams. Covering an area of program and project management that is rapidly becoming more widely valued, this book blends theory with practical experience to present a clear process flow to managing the benefits life cycle. Best practices are defined, and pitfalls and traps are identified to enable practitioners to apply rigor and structure to this crucial discipline.

"Proceedings of the FISITA 2012 World Automotive Congress" are selected from nearly 2,000 papers submitted to the 34th FISITA World Automotive Congress, which is held by Society of Automotive Engineers of China (SAE-China) and the International Federation of Automotive Engineering Societies (FISITA). This proceedings focus on solutions for sustainable mobility in all areas of passenger car, truck and bus transportation. Volume 10: Chassis Systems and Integration Technology focuses on:
Chassis structure and Design
Chassis Controls and Integration
Tire and wheel Design/ Tire Properties and Modeling
Subjective and Objective Evaluation on Dynamic Performance
Dynamics Modeling, Simulation and Experimental Validation
Above all researchers, professional engineers and graduates in fields of automotive engineering, mechanical engineering and electronic engineering will benefit from this book.
SAE-China is a national academic organization composed of enterprises and professionals who focus on research, design and education in the fields of automotive and related industries. FISITA is the umbrella organization for the national automotive societies in 37 countries around the world. It was founded in Paris in 1948 with the purpose of bringing engineers from around the world together in a spirit of cooperation to share ideas and advance the technological development of the automobile."

This book presents a comprehensive overview of the recent advances in the domain of optimal guidance, exploring the characteristics of various optimal guidance algorithms and their pros and cons. Optimal guidance is based on the concept of trajectory optimization, which minimizes the meaningful performance index while satisfying certain terminal constraints, and by properly designing the cost function the guidance command can serve as a desired pattern for a variety of mission objectives. The book allows readers to gain a deeper understanding of how optimal guidance law can be utilized to achieve different mission objectives for missiles and UAVs, and also explores the physical meaning and working principle of different new optimal guidance laws. In practice, this information is important in ensuring confidence in the performance and reliability of the guidance law when implementing it in a real-world system, especially in aerospace engineering where reliability is the first priority.

This book focuses on unhealthy cyber-physical systems. Consisting of 14 chapters, it discusses recognizing the beginning of the fault, diagnosing the appearance of the fault, and stopping the system or switching to a special control mode known as fault-tolerant control. Each chapter includes the background, motivation, quantitative development (equations), and case studies/illustration/tutorial (simulations, experiences, curves, tables, etc.). Readers can easily tailor the techniques presented to accommodate their ad hoc applications.

This book addresses a broad range of topics concerning machine learning, big data, the Internet of things (IoT), and security in the IoT. Its goal is to bring together several innovative studies on these areas, in order to help researchers, engineers, and designers in several interdisciplinary domains pursue related applications. It presents an overview of the various algorithms used, focusing on the advantages and disadvantages of each in the fields of machine learning and big data. It also covers next-generation computing paradigms that are expected to support wireless networking with high data transfer rates and autonomous decision-making capabilities. In turn, the book discusses IoT applications (e.g. healthcare applications) that generate a huge amount of sensor data and imaging data that must be handled correctly for further processing. In the traditional IoT ecosystem, cloud computing offers a solution for the efficient management of huge amounts of data, thanks to its ability to access shared resources and provide a common infrastructure in a ubiquitous manner. Though these new technologies are invaluable, they also reveal serious IoT security challenges. IoT applications are vulnerable to various types of attack such as eavesdropping, spoofing and false data injection, the man-in-the-middle attack, replay attack, denial-of-service attack, jamming attack, flooding attack, etc. These and other security issues in the Internet of things are explored in detail. In addition to highlighting outstanding research and recent advances from around the globe, the book reports on current challenges and future directions in the IoT. Accordingly, it offers engineers, professionals, researchers, and designers an applied-oriented resource to support them in a broad range of interdisciplinary areas.

This book aims at providing an overview of state-of-the-art in both the theory and methods of intuitionistic fuzzy logic, partial differential equations and numerical methods in informatics. It covers topics such as fuzzy intuitionistic Hilbert spaces, intuitionistic fuzzy differential equations, fuzzy intuitionistic metric spaces, and numerical methods for differential equations. It reports on applications such as fuzzy real time scheduling, intelligent control, diagnostics and time series prediction. Chapters were carefully selected among contributions presented at the second edition of the International Conference on Intuitionistic Fuzzy Sets and Mathematical Science, ICIFSMAS, held on April 11-13, 2018, at Al Akhawayn University of Ifrane, in Morocco.

This proceedings volume highlights a selection of papers presented at the 7th International Conference on High Performance Scientific Computing, which took place in Hanoi, Vietnam, during March 19-23, 2018. The conference has been organized by the Institute of Mathematics of the Vietnam Academy of Science and Technology, the Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University and the Vietnam Institute for Advanced Study in Mathematics. The contributions cover a broad, interdisciplinary spectrum of scientific computing and showcase recent advances in theory, methods, and practical applications. Subjects covered include numerical simulation, methods for optimization and control, machine learning, parallel computing and software development, as well as the applications of scientific computing in mechanical engineering, airspace engineering, environmental physics, decision making, hydrogeology, material science and electric circuits.

The idea behind this book is to simplify the journey of aspiring readers and researchers to understand the convergence of Big Data with the Cloud. This book presents the latest information on the adaptation and implementation of Big Data technologies in various cloud domains and Industry 4.0. Synergistic Interaction of Big Data with Cloud Computing for Industry 4.0 discusses how to develop adaptive, robust, scalable, and reliable applications that can be used in solutions for day-to-day problems. It focuses on the two frontiers - Big Data and Cloud Computing - and reviews the advantages and consequences of utilizing Cloud Computing to tackle Big Data issues within the manufacturing and production sector as part of Industry 4.0. The book unites some of the top Big Data experts throughout the world who contribute their knowledge and expertise on the different aspects, approaches, and concepts related to new technologies and novel findings. Based on the latest technologies, the book offers case studies and covers the major challenges, issues, and advances in Big Data and Cloud Computing for Industry 4.0. By exploring the basic and high-level concepts, this book serves as a guide for those in the industry, while also helping beginners and more advanced learners understand both basic and more complex aspects of the synergy between Big Data and Cloud Computing.

The book provides general knowledge of automatic control engineering and its applications. Providing an overview of control theory and systems, the chapters introduce transfer functions, modeling of control systems, automatic control systems, block diagrams, and signal flow graphs. While control system analysis and design are accompanied by root-locus methods and frequency response analyses, distributed control systems, nonlinarity in control systems including Z-transformation are also presented. With straightforward demonstrations, examples, and multiple-choice questions, this book can be used as a reference textbook for electrical and electronics engineering, computer control engineering, automation engineering, mechatronics engineering, mechanics, robotics, AI control systems, hydraulics, process engineering, safety control engineering, aeronautical and aerospace engineering, auto-pilot system, decision-making system, and stock exchange, and will be suitable for majors, non-majors, and experts in the field of science and technology.

1. Understand the audit culture, challenges, and benefits of the CAE role in digitally transforming business environment in smart cities 2. Identify ways to advance the value of Internal Audit in digital era 3. Use and control the resources of the city efficiently, and to ensure that the system units work properly in an integrated way.

This book provides its reader with a good understanding of the stabilization of switched nonlinear systems (SNS), systems that are of practical use in diverse situations: design of fault-tolerant systems in space- and aircraft; traffic control; and heat propagation control of semiconductor power chips. The practical background is emphasized throughout the book; interesting practical examples frequently illustrate the theoretical results with aircraft and spacecraft given particular prominence.

Stabilization of Switched Nonlinear Systems with Unstable Modes treats several different subclasses of SNS according to the characteristics of the individual system (time-varying and distributed parameters, for example), the state composition of individual modes and the degree and distribution of instability in its various modes. Achievement and maintenance of stability across the system as a whole is bolstered by trading off between individual modes which may be either stable or unstable or by exploiting areas of partial stability within all the unstable modes.

The book can be used as a reference for academic research on switched systems or used by graduate students of control theory and engineering. Readers should have studied linear and nonlinear system theory and have some knowledge of switched and hybrid systems to get the most from this monograph.

The methods are more practical than the common probabilistic based algorithms, since these can be appiled in unknown but bounded noisy environment.

This book presents advanced control techniques that use neural networks to deal with grid disturbances in the context renewable energy sources, and to enhance low-voltage ride-through capacity, which is a vital in terms of ensuring that the integration of distributed energy resources into the electrical power network. It presents modern control algorithms based on neural identification for different renewable energy sources, such as wind power, which uses doubly-fed induction generators, solar power, and battery banks for storage. It then discusses the use of the proposed controllers to track doubly-fed induction generator dynamics references: DC voltage, grid power factor, and stator active and reactive power, and the use of simulations to validate their performance. Further, it addresses methods of testing low-voltage ride-through capacity enhancement in the presence of grid disturbances, as well as the experimental validation of the controllers under both normal and abnormal grid conditions. The book then describes how the proposed control schemes are extended to control a grid-connected microgrid, and the use of an IEEE 9-bus system to evaluate their performance and response in the presence of grid disturbances. Lastly, it examines the real-time simulation of the entire system under normal and abnormal conditions using an Opal-RT simulator.

Defines concepts and processes of software and software development, such as agile processes, requirements engineering, and software architecture, design, construction Uncovers and answers various misconceptions about the software development process and presents an up-to-date reflection on the state of practice in the industry Details how non-software engineers can better communicate their needs to software engineers and more effectively participate in design and testing to ultimately lower software development and maintenance costs Helps answer the question: How can I better leverage embedded software in my design? Adds new chapters on software architecture, software engineering and systems, and software engineering and disruptive technologies, as well as information on cybersecurity Features new appendices that describe a sample automation system, covering software requirements, architecture, and design

The methods are more practical than the common probabilistic based algorithms, since these can be appiled in unknown but bounded noisy environment.

This book aims at the tiny machine learning (TinyML) software and hardware synergy for edge intelligence applications. This book presents on-device learning techniques covering model-level neural network design, algorithm-level training optimization and hardware-level instruction acceleration. Analyzing the limitations of conventional in-cloud computing would reveal that on-device learning is a promising research direction to meet the requirements of edge intelligence applications. As to the cutting-edge research of TinyML, implementing a high-efficiency learning framework and enabling system-level acceleration is one of the most fundamental issues. This book presents a comprehensive discussion of the latest research progress and provides system-level insights on designing TinyML frameworks, including neural network design, training algorithm optimization and domain-specific hardware acceleration. It identifies the main challenges when deploying TinyML tasks in the real world and guides the researchers to deploy a reliable learning system. This book will be of interest to students and scholars in the field of edge intelligence, especially to those with sufficient professional Edge AI skills. It will also be an excellent guide for researchers to implement high-performance TinyML systems.

Geometric control theory is concerned with the evolution of systems subject to physical laws but having some degree of freedom through which motion is to be controlled. This book describes the mathematical theory inspired by the irreversible nature of time evolving events. The first part of the book deals with the issue of being able to steer the system from any point of departure to any desired destination. The second part deals with optimal control, the question of finding the best possible course. An overlap with mathematical physics is demonstrated by the Maximum principle, a fundamental principle of optimality arising from geometric control, which is applied to time-evolving systems governed by physics as well as to man-made systems governed by controls. Applications are drawn from geometry, mechanics, and control of dynamical systems. The geometric language in which the results are expressed allows clear visual interpretations and makes the book accessible to physicists and engineers as well as to mathematicians.