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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
The book provides fault detection and diagnosis approaches from the perspective of filtering analysis. In order to design fault detection filters, it uses set-membership principles to deal with the unknown but bounded noise term. Some regular geometric spaces are introduced, such as the ellipsoid, polyhedron, interval, to describe the feasible parameter sets of the given system. Both principles and engineering practice have been addressed, with more weight placed on engineering practice. Some typical application cases are studied for fault detection and diagnosis in detail, which are power converter, permanent magnet synchronous motor, pitch system of wind turbine. Given its scope, the book offers a valuable guide for students, teachers, engineers and researchers in the field of fault detection and diagnosis.
This book covers the author's research achievements and the latest advances in high-speed pneumatic control theory and applied technologies. It presents the basic theory and highlights pioneering technologies resulting from research and development efforts in aerospace, aviation and other major equipment, including: pneumatic servo control theory, pneumatic nonlinear mechanisms, aerothermodynamics, pneumatic servo mechanisms, and high-speed pneumatic control theory.
This book aims to extend existing works on consensus of multi-agent systems systematically. The agents to be considered range from double integrators to generic linear systems. The primary goal is to explicitly characterize how agent parameters, which reflect both self-dynamics and inner coupling of each agent, and switching network topologies jointly influence the collective behaviors. A series of necessary and/or sufficient conditions for exponential consensus are derived. The contents of this book are as follows. Chapter 1 provides the background and briefly reviews the advances of consensus of multi-agent systems. Chapter 2 addresses the consensus problem of double integrators over directed switching network topologies. It is proven that exponential consensus can be secured under very mild conditions incorporating the damping gain and network topology. Chapter 3 considers generic linear systems with undirected switching network topologies. Necessary and sufficient conditions on agent parameters and connectivity of the communication graph for exponential consensus are provided. Chapter 4 furthers the study of consensus for multiple generic linear systems by considering directed switching network topologies. How agent parameters and joint connectivity work together for reaching consensus is characterized from an algebraic and geometric view. Chapter 5 extends the design and analysis methodology to containment control problem, where there exist multiple leaders. A novel analysis framework from the perspective of state transition matrix is developed. This framework relates containment to consensus and overcomes the difficulty of construction of a containment error. This book serves as a reference to the main research issues and results on consensus of multi-agent systems. Some prerequisites for reading this book include linear system theory, matrix theory, mathematics, and so on.
Perturbation Methods in Science and Engineering provides the fundamental and advanced topics in perturbation methods in science and engineering, from an application viewpoint. This book bridges the gap between theory and applications, in new as well as classical problems. The engineers and graduate students who read this book will be able to apply their knowledge to a wide range of applications in different engineering disciplines. The book begins with a clear description on limits of mathematics in providing exact solutions and goes on to show how pioneers attempted to search for approximate solutions of unsolvable problems. Through examination of special applications and highlighting many different aspects of science, this text provides an excellent insight into perturbation methods without restricting itself to a particular method. This book is ideal for graduate students in engineering, mathematics, and physical sciences, as well as researchers in dynamic systems.
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 presents best selected research papers presented at the International Conference on Recent Trends in Communication and Intelligent Systems (ICRTCIS 2020), organized by Arya College of Engineering and IT, Jaipur, on 20-21 November 2020. It discusses the latest technologies in communication and intelligent systems, covering various areas of communication engineering, such as signal processing, VLSI design, embedded systems, wireless communications, and electronics and communications in general. Featuring work by leading researchers and technocrats, the book serves as a valuable reference resource for young researchers and academics as well as practitioners in industry.
The book focuses the latest endeavours relating researches and developments conducted in fields of Control, Robotics and Automation. Through more than twenty revised and extended articles, the present book aims to provide the most up-to-date state-of-art of the aforementioned fields allowing researcher, PhD students and engineers not only updating their knowledge but also benefiting from the source of inspiration that represents the set of selected articles of the book. The deliberate intention of editors to cover as well theoretical facets of those fields as their practical accomplishments and implementations offers the benefit of gathering in a same volume a factual and well-balanced prospect of nowadays research in those topics. A special attention toward "Intelligent Robots and Control" may characterize another benefit of this book.
This book provides a unique approach to derive model-based torque controllers for all types of Lorentz force machines, i.e. DC, synchronous and induction machines. The rotating transformer model forms the basis for the generalized modeling approach of rotating field machines, which leads to the development of universal field-oriented control algorithms. Contrary to this, direct torque control algorithms, using observer-based methods, are developed for switched reluctance machines. Tutorials are included at the end of each chapter, and the reader is encouraged to execute these tutorials in order to gain familiarity with the dynamic behavior of drive systems. This updated edition uses PLECS (R) simulation and vector processing tools that were specifically adopted for the purpose of these hands-on tutorials. Hence, Advanced Electrical Drives encourages "learning by doing" and the experienced drive specialist may find the simulation tools useful to design high-performance torque controllers. Although it is a powerful reference in its own right, when used in conjunction with the companion texts Fundamentals of Electrical Drives and Applied Control of Electrical Drives, this book provides a uniquely comprehensive reference set that takes readers all the way from understanding the basics of how electrical drives work, to deep familiarity with advanced features and models, to a mastery of applying the concepts to actual hardware in practice. Teaches readers to perform insightful analysis of AC electrical machines and drives; Introduces new modeling methods and modern control techniques for switched reluctance drives; Updated to use PLECS (R) simulation tools for modeling electrical drives, including new and more experimental results; Numerous tutorials at end of each chapter to learn by doing, step-by-step; Includes extra material featuring "build and play" lab modules, for lectures and self-study.
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.
Approximation Methods in Engineering and Science covers fundamental and advanced topics in three areas: Dimensional Analysis, Continued Fractions, and Stability Analysis of the Mathieu Differential Equation. Throughout the book, a strong emphasis is given to concepts and methods used in everyday calculations. Dimensional analysis is a crucial need for every engineer and scientist to be able to do experiments on scaled models and use the results in real world applications. Knowing that most nonlinear equations have no analytic solution, the power series solution is assumed to be the first approach to derive an approximate solution. However, this book will show the advantages of continued fractions and provides a systematic method to develop better approximate solutions in continued fractions. It also shows the importance of determining stability chart of the Mathieu equation and reviews and compares several approximate methods for that. The book provides the energy-rate method to study the stability of parametric differential equations that generates much better approximate solutions.
Incorporating recent developments in control and systems research, "Linear Control Theory" provides the fundamental theoretical background needed to fully exploit control system design software. This logically-structured text opens with a detailed treatment of the relevant aspects of the state space analysis of linear systems. End-of-chapter problems facilitate the learning process by encouraging the student to put his or her skills into practice. Features include:
These proceedings address the latest developments in the broad area of intelligent construction integrated in the mission of the International Society for Intelligent Construction (ISIC) which aims to promote intelligent construction technologies applications from the survey, design, construction, operation, and maintenance/rehabilitation by adapting to changes of environments and minimizing risks. Its goals are to improve the quality of construction, cost-saving, and safety, exploring fundamental issues related to the application and use of Artificial Intelligence (AI) and Machine Learning techniques and technology. ISIC 2022 is the 3rd ISIC international conference, held in Guimaraes, Portugal on September 6-9, 2022, and follows the previous successful instalments of the conference series in China (2019) and USA (2017). It took a holistic approach to integrate civil engineering, construction machinery, electronic sensor technology, survey/testing technologies, information technology/computing, and other related fields in the broad area of intelligent construction. The respective contributions cover the following topics: Artificial Intelligence for Design and the Built Environment, Building Information Modelling (BIM) and Construction Automation and Robotics, Intelligent Construction, Sustainable Construction, and Sustainable and Smart Infrastructures. Given its broad range of coverage, the book will benefit students, educators, researchers and professionals practitioners alike, encouraging these readers to help the intelligent construction community into the digital era and with a vision on societal issues.
A Tour of Data Science: Learn R and Python in Parallel covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single short book. It does not cover everything, but rather, teaches the key concepts and topics in Data Science. It also covers two of the most popular programming languages used in Data Science, R and Python, in one source. Key features: Allows you to learn R and Python in parallel Cover statistics, programming, optimization and predictive modelling, and the popular data manipulation tools - data.table and pandas Provides a concise and accessible presentation Includes machine learning algorithms implemented from scratch, linear regression, lasso, ridge, logistic regression, gradient boosting trees, etc. Appealing to data scientists, statisticians, quantitative analysts, and others who want to learn programming with R and Python from a data science perspective.
Ordinary and fractional approximations by non-additive integrals, especially by integral approximators of Choquet, Silkret and Sugeno types, are a new trend in approximation theory. These integrals are only subadditive and only the first two are positive linear, and they produce very fast and flexible approximations based on limited data. The author presents both the univariate and multivariate cases. The involved set functions are much weaker forms of the Lebesgue measure and they were conceived to fulfill the needs of economic theory and other applied sciences. The approaches presented here are original, and all chapters are self-contained and can be read independently. Moreover, the book's findings are sure to find application in many areas of pure and applied mathematics, especially in approximation theory, numerical analysis and mathematical economics (both ordinary and fractional). Accordingly, it offers a unique resource for researchers, graduate students, and for coursework in the above-mentioned fields, and belongs in all science and engineering libraries.
This book systematically presents the concept, history, implementation, theory system and basic methods of pulsar and space flight, illustrating the characteristics of pulsars. It also describes the classification of spacecraft navigation systems and the autonomous navigation technologies, as well as X-ray pulsar-based navigation systems (XPNAV) and discusses future navigation satellite systems in detail.
This book introduces the principle theories and applications of control and filtering problems to address emerging hot topics in feedback systems. With the development of IT technology at the core of the 4th industrial revolution, dynamic systems are becoming more sophisticated, networked, and advanced to achieve even better performance. However, this evolutionary advance in dynamic systems also leads to unavoidable constraints. In particular, such elements in control systems involve uncertainties, communication/transmission delays, external noise, sensor faults and failures, data packet dropouts, sampling and quantization errors, and switching phenomena, which have serious effects on the system's stability and performance. This book discusses how to deal with such constraints to guarantee the system's design objectives, focusing on real-world dynamical systems such as Markovian jump systems, networked control systems, neural networks, and complex networks, which have recently excited considerable attention. It also provides a number of practical examples to show the applicability of the presented methods and techniques. This book is of interest to graduate students, researchers and professors, as well as R&D engineers involved in control theory and applications looking to analyze dynamical systems with constraints and to synthesize various types of corresponding controllers and filters for optimal performance of feedback systems.
This book analyzes coalitional control schemes by incorporating concepts of cooperative game theory into a distributed control framework. It considers a networked architecture where the nodes are the agents and the edges are their communication links and either the agents or the links are established as the players of cooperative games related to the cost function of the coalitional schemes. The book discusses various cooperative game theory tools that are used to measure/analyze the players' features, impose constraints on them, provide alternative methods of game computation, detect critical players inside the control scheme, and perform system partitioning of large-scale systems, such as the Barcelona drinking water network, which is described in a case study.
This book presents a comprehensive guide to the design of playing robots and the related play experiences. Play is a natural activity for building and improving abilities, and it reveals important particularly for persons with disabilities. Many social, physical and cultural factors may hinder children with disabilities from fully enjoying play as their peers. Autonomous robots with specific characteristics can enhance the ludic experience, having implications for the character of the play and presenting opportunities related to autonomy and physical movement, the very nature of robots. Their introduction into play thus provides everybody, and in particular persons with disabilities, new possibilities for developing abilities, improving general status, participating in social contexts, as well as supporting professionals in monitoring progress. This book presents a framework for the design of playful activities with robots, developed over 20 years' experience at AIRLab - POLIMI. Part 1 introduces the play concepts and characteristics, and research results about play of children with different kinds of impairments. Part 2 focuses on implementing robots able to play. The design of playful activities is discussed, as well as the necessary characteristics for them to be useful in both general play and activities involving disability-related limitations. In Part 3, the defined framework is used to analyze possibilities involving robots available on the toy market, robots developed at research labs, and robots to be developed in the next future. The aim of the book is to give developers, caregivers, and users a set of methodological tools for selecting, exploring, and designing inclusive play activities where robots play a central role.
This book is based on the authors' research on the stabilization and fault-tolerant control of batch processes, which are flourishing topics in the field of control system engineering. It introduces iterative learning control for linear/nonlinear single/multi-phase batch processes; iterative learning optimal guaranteed cost control; delay-dependent iterative learning control; and iterative learning fault-tolerant control for linear/nonlinear single/multi-phase batch processes. Providing important insights and useful methods and practical algorithms that can potentially be applied in batch process control and optimization, it is a valuable resource for researchers, scientists, and engineers in the field of process system engineering and control engineering.
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.
This book offers fundamental information on the analysis and synthesis of continuous and sampled data control systems. It includes all the required preliminary materials (from mathematics, signals and systems) that are needed in order to understand control theory, so readers do not have to turn to other textbooks. Sampled data systems have recently gained increasing importance, as they provide the basis for the analysis and design of computer-controlled systems. Though the book mainly focuses on linear systems, input/output approaches and state space descriptions are also provided. Control structures such as feedback, feed forward, internal model control, state feedback control, and the Youla parameterization approach are discussed, while a closing section outlines advanced areas of control theory. Though the book also contains selected examples, a related exercise book provides Matlab/Simulink exercises for all topics discussed in the textbook, helping readers to understand the theory and apply it in order to solve control problems. Thanks to this combination, readers will gain a basic grasp of systems and control, and be able to analyze and design continuous and discrete control systems.
This book shows in a comprehensive presentation how Bond Graph methodology can support model-based control, model-based fault diagnosis, fault accommodation, and failure prognosis by reviewing the state-of-the-art, presenting a hybrid integrated approach to Bond Graph model-based fault diagnosis and failure prognosis, and by providing a review of software that can be used for these tasks. The structured text illustrates on numerous small examples how the computational structure superimposed on an acausal bond graph can be exploited to check for control properties such as structural observability and control lability, perform parameter estimation and fault detection and isolation, provide discrete values of an unknown degradation trend at sample points, and develop an inverse model for fault accommodation. The comprehensive presentation also covers failure prognosis based on continuous state estimation by means of filters or time series forecasting. This book has been written for students specializing in the overlap of engineering and computer science as well as for researchers, and for engineers in industry working with modelling, simulation, control, fault diagnosis, and failure prognosis in various application fields and who might be interested to see how bond graph modelling can support their work. Presents a hybrid model-based, data-driven approach to failure prognosis Highlights synergies and relations between fault diagnosis and failure prognostic Discusses the importance of fault diagnosis and failure prognostic in various fields
This book describes the theoretical framework of parallel manipulators and presents examples of their application. The theoretical part begins with the theory of parallel manipulator synthesis. Working on this basis, various topology designs of one-loop and multiloop parallel manipulators are then obtained. The next section describes the zero parameters method for the analysis of mechanism (manipulator) structure with closed kinematic circuits, and includes examples of its application, highlighting its advantages compared to traditional methods. The book then presents the redundant parameters method for determining the position of special parallel manipulator links, and discusses its application in solving the direct problem of link position for multiloop manipulators. It also addresses one-loop and multiloop manipulators, and includes a solution for the direct and inverse link position problems of kinematics. In closing, the book presents a range of potential applications for parallel manipulator. These examples are intended to promote the development and implementation of new engineering solutions, e.g. in seismic protection systems, renewable energy and other areas. The book includes a wealth of material that can be used for teaching undergraduate, graduate and PhD students majoring in robotics, automation and related fields, and can also be used by researchers to solve problems in connection with introducing robotics technologies.
For years, systems theory has been applied successfully in all fields of technology, but its impact on the world of finance has to date been limited. This book aims to rectify this situation. Readers will no longer be able to assert that money cannot be reliably earned on the financial markets: one might just as well say that man has never set foot on the moon. The potential reader may be frightened by the number of formulas, but can be reassured that almost all of them can be skipped. What makes the miracle of guaranteed trading success possible are the worksheets and the codes for Internet platforms which provide (at a click) functions that once had to be built with great difficulty. These worksheets and codes will be sent free of charge to anyone who requests them from the author ([email protected]) as long as the request is accompanied by proof of purchase of the book, such as a photograph of the receipt taken on a mobile phone. |
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