Iterative Learning Control (ILC) differs from most existing control methods in the sense that, it exploits every possibility to incorporate past control informa tion, such as tracking errors and control input signals, into the construction of the present control action. There are two phases in Iterative Learning Control: first the long term memory components are used to store past control infor mation, then the stored control information is fused in a certain manner so as to ensure that the system meets control specifications such as convergence, robustness, etc. It is worth pointing out that, those control specifications may not be easily satisfied by other control methods as they require more prior knowledge of the process in the stage of the controller design. ILC requires much less information of the system variations to yield the desired dynamic be haviors. Due to its simplicity and effectiveness, ILC has received considerable attention and applications in many areas for the past one and half decades. Most contributions have been focused on developing new ILC algorithms with property analysis. Since 1992, the research in ILC has progressed by leaps and bounds. On one hand, substantial work has been conducted and reported in the core area of developing and analyzing new ILC algorithms. On the other hand, researchers have realized that integration of ILC with other control techniques may give rise to better controllers that exhibit desired performance which is impossible by any individual approach."

This book presents the latest achievements of Russian scientists in the field of theory and practice of decision-making in SEMS, taking into account the information received from the sensors of its central nervous system (CNS). Recently, in the field of theory and practice of intelligent robotics systems management, the solution to the problem of SEMS type urgent task of making decisions about their expedient behavior is based on the integration of the processes of obtaining, processing and storing information, computing, control and monitoring. This enables the efficiency, reliability and safety of operation of SEMS in real time. Decision-making methods are described, both in the autonomous behavior of SEMS and in their group interaction, based on the principles of bionics, adaptability, intelligence and parallelism in information processing and computation. This book is intended for students, scientists and engineers specializing in the field of smart electromechanical systems and robotics.

In this concise yet comprehensive Open Access textbook, future inventors are introduced to the key concepts of Cyber-Physical Systems (CPS). Using modeling as a way to develop deeper understanding of the computational and physical components of these systems, one can express new designs in a way that facilitates their simulation, visualization, and analysis. Concepts are introduced in a cross-disciplinary way. Leveraging hybrid (continuous/discrete) systems as a unifying framework and Acumen as a modeling environment, the book bridges the conceptual gap in modeling skills needed for physical systems on the one hand and computational systems on the other. In doing so, the book gives the reader the modeling and design skills they need to build smart, IT-enabled products. Starting with a look at various examples and characteristics of Cyber-Physical Systems, the book progresses to explain how the area brings together several previously distinct ones such as Embedded Systems, Control Theory, and Mechatronics. Featuring a simulation-based project that focuses on a robotics problem (how to design a robot that can play ping-pong) as a useful example of a CPS domain, Cyber-Physical Systems: A Model-Based Approach demonstrates the intimate coupling between cyber and physical components, and how designing robots reveals several non-trivial control problems, significant embedded and real-time computation requirements, and a need to consider issues of communication and preconceptions.

Nonlinear Control Systems and Power System Dynamics presents a comprehensive description of nonlinear control of electric power systems using nonlinear control theory, which is developed by the differential geometric approach and nonlinear robust control method. This book explains in detail the concepts, theorems and algorithms in nonlinear control theory, illustrated by step-by-step examples. In addition, all the mathematical formulation involved in deriving the nonlinear control laws of power systems are sufficiently presented. Considerations and cautions involved in applying nonlinear control theory to practical engineering control designs are discussed and special attention is given to the implementation of nonlinear control laws using microprocessors. Nonlinear Control Systems and Power System Dynamics serves as a text for advanced level courses and is an excellent reference for engineers and researchers who are interested in the application of modern nonlinear control theory to practical engineering control designs.

There has been a great deal of excitement over the last few years concerning the emergence of new mathematical techniques for the analysis and control of nonlinear systems: witness the emergence of a set of simplified tools for the analysis of bifurcations, chaos and other simplified tools for the analysis of bifurcations, chaos and other complicated dynamical behaviour and the development of a comprehensive theory of nonlinear control. Coupled with this set of analytic advances has been the vast increase in computational power available both for the simulation of nonlinear systems as well as for the implementation in real time of sophisticated, real-time nonlinear control laws. Thus, technological advances have bolstered the impact of analytic advances and produced a tremendous variety of new problems and applications which are nonlinear in an essential way. This book lays out in a concise mathematical framework the tools and methods of analysis which underlie this diversity of applications. The material presented in this book is culled from different 1st year graduate courses that the author has taught at MIT and at Berkeley.

Many professionals and students in engineering, science, business, and other application fields need to develop Windows-based and web-enabled information systems to store and use data for decision support, without help from professional programmers. However, few books are available to train professionals and students who are not professional programmers to develop these information systems. Developing Windows-Based and Web-Enabled Information Systems fills this gap, providing a self-contained, easy-to-understand, and well-illustrated text that explores current concepts, methods, and software tools for developing Windows-based and web-enabled information systems. Written in an easily accessible style, the book details current concepts, methods, and software tools for Windows-based and web-enabled information systems that store and use data. It is self-contained with easy-to-understand small examples to walk through concepts and implementation details along with large-scale case studies. The book describes data modeling methods including entity-relationship modeling, relational modeling and normalization, and object-oriented data modeling, to develop data models of a database. The author covers how to use software tools in the Microsoft application development environment, including Microsoft Access, MySQL, SQL, Visual Studio, Visual Basic, VBA, HTML, and XML, to implement databases and develop Windows-based and web-enabled applications with the database, graphical user interface, and program components. The book takes you through the entire process of developing a computer and network application for an information system, highlighting concepts and operation details. In each chapter, small data examples are used to manually walk through concepts and operational details. These features and more give you the conceptual understanding and practical skill required, even if you don't have a computer science background, to develop Windows-based or web-enabled applications for your specialized information system.

The main objectives of the book are to introduce the design method of boundary control strategies for the axially moving structures to reduce their vibration. This book provides the reader with a thorough grounding in the boundary controller design. Our goal is to provide advanced boundary controller design methods and their stability analysis methods and offer simulation examples and MATLAB programs for each boundary control algorithm. For each chapter, several engineering application examples are given and the contents of each chapter in this book are independent, so that readers can just read their own needs. In this book, all the control algorithms and their programs are described separately and classified by the chapter name, which can be run successfully in MATLAB. The book can benefit researchers, engineers, and graduate students in the fields of PDE modeling and boundary vibration control of flexible structures.

This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large scale neural models, brain computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXII International Conference on Neuroinformatics, held on October 12-16, 2020, Moscow, Russia.

This book presents iterative learning control (ILC) to address practical issues of flexible structures. It is divided into four parts: Part I provides a general introduction to ILC and flexible structures, while Part II proposes various types of ILC for simple flexible structures to address issues such as vibration, input saturation, input dead-zone, input backlash, external disturbances, and trajectory tracking. It also includes simple partial differential equations to deal with the common problems of flexible structures. Part III discusses the design of ILC for flexible micro aerial vehicles and two-link manipulators, and lastly, Part IV offers a summary of the topics covered. Unlike most of the literature on ILC, which focuses on ordinary differential equation systems, this book explores distributed parameter systems, which are comparatively less stabilized through ILC.Including a comprehensive introduction to ILC of flexible structures, it also examines novel approaches used in ILC to address input constraints and disturbance rejection. This book is intended for researchers, graduate students and engineers in various fields, such as flexible structures, external disturbances, nonlinear inputs and tracking control.

The classic text, now completely up to date

This Second Edition of State Variables for Engineers is completely updated to reflect both the many changes in the field of systems and control and the fact that today's first-year graduate students are well prepared in the background skills and techniques needed to handle this material. The book begins with an introduction to the basic concepts behind time domain techniques, comparisons between state variable feedback and classical output feedback, and a discussion of the concepts of observability and controllability.

The authors stress the importance of studying matrices and linear spaces by offering state variable representations for continuous linear systems in matrix form along with the solution to the resulting linear matrix differential equation. This treatment demonstrates how these basic linear algebra tools are related to the state variable analysis of linear systems.

This new edition retains thorough coverage of the eigenvalue-eigenvector problem from the first edition, as well as several chapters on state variables for continuous and discrete-time systems—now supplemented with additional material on observability and controllability. It also offers three entirely new chapters covering:

• Canonical forms for representing linear systems
• Observers and controllers
• Identification and estimation

Supplemented with appendices on basic matrix algebra and Z transforms, State Variables for Engineers, Second Edition is the ideal text for courses in systems analysis and techniques. It is also an excellent reference for professionals who want to keep pace with recent changes in the field.

Despite major advances in healthcare over the past century, the successful treatment of cancer has remained a significant challenge, and cancers are the second leading cause of death worldwide behind cardiovascular disease. Early detection and survival are important issues to control cancer. The development of quantitative methods and computer technology has facilitated the formation of new models in medical and biological sciences. The application of mathematical modelling in solving many real-world problems in medicine and biology has yielded fruitful results. In spite of advancements in instrumentations technology and biomedical equipment, it is not always possible to perform experiments in medicine and biology for various reasons. Thus, mathematical modelling and simulation are viewed as viable alternatives in such situations, and are discussed in this book. The conventional diagnostic techniques of cancer are not always effective as they rely on the physical and morphological appearance of the tumour. Early stage prediction and diagnosis is very difficult with conventional techniques. It is well known that cancers are involved in genome level changes. As of now, the prognosis of various types of cancer depends upon findings related to the data generated through different experiments. Several machine learning techniques exist in analysing the data of expressed genes; however, the recent results related with deep learning algorithms are more accurate and accommodative, as they are effective in selecting and classifying informative genes. This book explores the probabilistic computational deep learning model for cancer classification and prediction.

This book presents the interdisciplinary and international "Virtual and Remote Tower" research and development work. It has been carried out since nearly twenty years with the goal of replacing the conventional aerodrome control tower by a new "Remote Tower Operation" (RTO) work environment for enhancing work efficiency and safety and reducing cost. The revolutionary human-system interface replaces the out-of-windows view by an augmented vision video panorama that allows for remote aerodrome traffic control without a physical tower building. It enables the establishment of a (multiple) remote control center (MRTO, RTC) that may serve several airports from a central location. The first (2016) edition of this book covered all aspects from preconditions over basic research and prototype development to initial validation experiments with field testing. Co-edited and -authored by DLR RTO-team members Dr. Anne Papenfuss and Joern Jakobi, this second extended edition with nearly doubled number of chapters includes further important aspects of the international follow-up work towards the RTO-deployment. Focus of the extension with new contributions from ENRI/Japan and IAA/Dublin with Cranfield University, is on MRTO, workload, implementation, and standardization. Specifically, the two revised and nine new Chapters put the focus on inclusion of augmented vision and virtual reality technologies, human-in-the-loop simulation for quantifying workload and deriving minimum (technical) requirements according to standards of the European Organization for Civil Aviation Equipment (EUROCAE), and MRTO implementation and certification. Basics of optical / video design, workload measures, and advanced psychophysical data analysis are presented in four appendices.

This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field. Provides multiple examples to facilitate the understanding data streams in non-stationary environments; Presents several application cases to show how the methods solve different real world problems; Discusses the links between methods to help stimulate new research and application directions.

This book discusses methods and algorithms for the near-optimal adaptive control of nonlinear systems, including the corresponding theoretical analysis and simulative examples, and presents two innovative methods for the redundancy resolution of redundant manipulators with consideration of parameter uncertainty and periodic disturbances. It also reports on a series of systematic investigations on a near-optimal adaptive control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the tracking control problem of nonlinear systems under different scenarios. The book culminates with a presentation of two new redundancy resolution methods; one addresses adaptive kinematic control of redundant manipulators, and the other centers on the effect of periodic input disturbance on redundancy resolution. Each self-contained chapter is clearly written, making the book accessible to graduate students as well as academic and industrial researchers in the fields of adaptive and optimal control, robotics, and dynamic neural networks.

This book offers a comprehensive overview of recently developed space multi-tethers, such as maneuverable space tethered nets and space tethered formation. For each application, it provides detailed derivatives to describe and analyze the mathematical model of the system, and then discusses the design and proof of different control schemes for various problems. The dynamics modeling presented is based on Newton and Lagrangian mechanics, and the book also introduces Hamilton mechanics and Poincare surface of section for dynamics analysis, and employs both centralized and distributed controllers to derive the formation question of the multi-tethered system. In addition to the equations and text, it includes 3D design drawings, schematic diagrams, control scheme blocks and tables to make it easy to understand. This book is intended for researchers and graduate students in the fields of astronautics, control science, and engineering.

Recent trends in the fashion market (including an impressive increase in the number of new collections, product assortments and variants, and the emerging mass-customization model) dictate the need for a new approach. "Transforming Clothing Production into a Demand-Driven, Knowledge-Based, High-Tech Industry" discusses the ramifications of such an approach, which must lead to a drastic shortening of the whole cycle from conception to production and retail, as well as a shift from a labor-intensive to a technology- and knowledge-intensive clothing manufacturing industry. "Transforming Clothing Production into a Demand-Driven, Knowledge-Based, High-Tech Industry" is a collection of short papers from prominent researchers involved with the LEAPFROG (Leadership for European Apparel Production From Research along Original Guidelines) initiative. LEAPFROG proposes a revolutionary industrial paradigm based on research results in scientific-technological fields.

This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing. It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems. The text is primarily written for graduate students and academic researchers in areas of electrical engineering, electronics engineering, computer engineering, and computational biology. This book: * Covers algorithms in the fields of artificial intelligence, and machine learning useful in biological data analysis. * Discusses comprehensively artificial intelligence and automatic image interpretation in modern biological systems. * Presents the application of evolutionary computations for fractal visualization of sequence data. * Explores the use of genetic algorithms for pair-wise and multiple sequence alignments. * Examines the roles of efficient computational techniques in biology.

This book presents the development of SLAM-based mobile robot control systems as an integrated approach that combines the localization, mapping and motion control fields, and reviews several techniques that represent the basics of the mathematical description of wheeled robots, their navigation and path planning approaches, localization and map creating techniques. It examines SLAM paradigms and Bayesian recursive state and map estimation techniques, which include Kalman and particle filtering, and enable the development of a SLAM-based integrated system for the inspection task performed. The system's development is divided into two phases: a single-robot approach and multirobot inspection system. The book describes an original approach to 2D SLAM in multi-floor buildings that covers each 2D level map, as well as continuous 3D pose tracking, and views the multirobot inspection system as a group of homogeneous mobile robots. The last part of the book is dedicated to multirobot map creation and the development of path planning solutions, which allow the robots' homogeneous behavior and configuration to be used to develop a multirobot system without theoretical limitations on the number of robots used.

This book provides a systematic approach to the design of predictor based controllers for (time-varying) linear systems with either (time-varying) input or state delays. Differently from those traditional predictor based controllers, which are infinite-dimensional static feedback laws and may cause difficulties in their practical implementation, this book develops a truncated predictor feedback (TPF) which involves only finite dimensional static state feedback. Features and topics: A novel approach referred to as truncated predictor feedback for the stabilization of (time-varying) time-delay systems in both the continuous-time setting and the discrete-time setting is built systematically Semi-global and global stabilization problems of linear time-delay systems subject to either magnitude saturation or energy constraints are solved in a systematic manner Both stabilization of a single system and consensus of a group of systems (multi-agent systems) are treated in a unified manner by applying the truncated predictor feedback and predictor feedback The properties of the solutions to a class of parametric (differential and difference) Lyapunov matrix equations are presented in detail Detailed numerical examples and applications to the spacecraft rendezvous and formation flying problems are provided to demonstrate the usefulness of the presented theoretical results This book can be a useful resource for the researchers, engineers, and graduate students in the fields of control, applied mathematics, mechanical engineering, electrical engineering, and aerospace engineering.

This book is aimed to provide comprehensive and systematic knowledge of kinematic synthesis as developed up to date. Modern mechanical systems require advance kinematics knowledge to support mechanism design with sound theories and methods. The book includes not only the classical foundations of kinematic synthesis, but also the latest advances developed by the authors. Moreover, many examples are included to illustrate both methods and their supporting theory. The focus is on systems of rigid bodies forming closed loops. The four-bar linkage, representing the foundations of mechanical systems, is given due attention, in its three domains: planar, spherical, and spatial. The book contains six chapters, the first two covering fundamentals for kinematic synthesis, including qualitative synthesis. Chapters 3-5 describe, in full detail, the function, motion, and path syntheses of single-dof linkages. In the last chapter, the synthesis of single-dof complex linkages, including six-bar and ten-bar linkages, is introduced. The book is suitable for graduate students of mechanical engineering, researchers of mechanism and robot design, and machine design engineers.

This book introduces readers to the fundamentals of estimation and dynamical system theory, and their applications in the field of multi-source information fused autonomous navigation for spacecraft. The content is divided into two parts: theory and application. The theory part (Part I) covers the mathematical background of navigation algorithm design, including parameter and state estimate methods, linear fusion, centralized and distributed fusion, observability analysis, Monte Carlo technology, and linear covariance analysis. In turn, the application part (Part II) focuses on autonomous navigation algorithm design for different phases of deep space missions, which involves multiple sensors, such as inertial measurement units, optical image sensors, and pulsar detectors. By concentrating on the relationships between estimation theory and autonomous navigation systems for spacecraft, the book bridges the gap between theory and practice. A wealth of helpful formulas and various types of estimators are also included to help readers grasp basic estimation concepts and offer them a ready-reference guide.       

The book consists of chapters based on selected papers of international conference Power, Control and Optimization 2012, held in Las Vegas, USA. Readers can find interesting chapters discussing various topics from the field of power control, its distribution and related fields. Book discusses topics like energy consumption impacted by climate, mathematical modeling of the influence of thermal power plant on the aquatic environment, investigation of cost reduction in residential electricity bill using electric vehicle at peak times or allocation and size evaluation of distributed generation using ANN model and others.

Chapter authors are to the best of our knowledge the originators or closely related to the originators of presented ideas and its applications. Hence, this book certainly is one of the few books discussing the benefit from intersection of those modern and fruitful scientific fields of research with very tight and deep impact on real life and industry.

This book is devoted to the studies of common and related subjects in intensive research fields of power technologies. For these reasons, we believe that this book will be useful for scientists and engineers working in the above-mentioned fields of research and applications.

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This book focuses on the fault diagnosis observer design for the switched system. Model-based fault diagnosis and fault tolerant control are one of the most popular research directions in recent decades. It contains eight chapters. Every chapter is independent in the method of observer design, but all chapters are around the same topic. Besides, in each chapter, the model description and theoretical results are firstly provided, then some practical application examples are illustrated to prove the obtained results. The advanced theoretical methodologies will benefit researchers or engineers in the area of safety engineering and the arrangement of the structure will help the readers to understand the content easily.

Unique selling point: * Brings together insights on various fields, and how IoT and AI combined can help bring about sustainable living Core audience: * Researchers and academics - worldwide applicability Place in the market: * Gives a more comprehensive overview of the potential applications of IoT and AI for sustainability than other books on the market

The book proposes new technologies and discusses innovative solutions to various problems in the field of communication, circuits, and systems, as reflected in high-quality papers presented at International Conference on Communication, Circuits, and Systems (IC3S 2020) held at KIIT, Bhubaneswar, India from 16 - 18 October 2020. It brings together new works from academicians, scientists, industry professionals, scholars, and students together to exchange research outcomes and open up new horizons in the areas of signal processing, communications, and devices.