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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
This book presents a foundation for a broad class of mobile robot mapping and navigation methodologies for indoor, outdoor, and exploratory missions. It addresses the challenging problem of autonomous navigation in dynamic environments, presenting new ideas and approaches in this emerging technical domain. Coverage discusses in detail various related challenging technical aspects and addresses upcoming technologies in this field.
This book provides robust analysis and synthesis tools for Markovian jump systems in the finite-time domain with specified performances. It explores how these tools can make the systems more applicable to fields such as economic systems, ecological systems and solar thermal central receivers, by limiting system trajectories in the desired bound in a given time interval. Robust Control for Discrete-Time Markovian Jump Systems in the Finite-Time Domain focuses on multiple aspects of finite-time stability and control, including: finite-time H-infinity control; finite-time sliding mode control; finite-time multi-frequency control; finite-time model predictive control; and high-order moment finite-time control for multi-mode systems and also provides many methods and algorithms to solve problems related to Markovian jump systems with simulation examples that illustrate the design procedure and confirm the results of the methods proposed. The thorough discussion of these topics makes the book a useful guide for researchers, industrial engineers and graduate students alike, enabling them systematically to establish the modeling, analysis and synthesis for Markovian jump systems in the finite-time domain.
Actuator saturation is probably the most frequent nonlinearity encountered in control applications. Input saturation leads to controller windup, removable by structural modification during compensator realization and plant windup which calls for additional dynamics. Peter Hippe presents solutions to the windup prevention problem for stable and unstable single-input-single-output and multiple-input-multiple-output (MIMO) systems. The solutions use only standard tools for the investigation of linear systems a" state equations, transfer functions, etc. The stability tests are based on well-known criteria for loops consisting of a linear part with isolated sector-type nonlinearity. Less rigorous "engineering solutions" which guarantee improved performance but without strict proof of stability are also demonstrated. MIMO systems in which the behaviour of controlled variables is decoupled require specific input vectors and so also suffer problems of directionality when their input signals saturate. This can have extremely deleterious consequences for closed-loop behaviour. Windup in Control offers an exact solution to this directionality problem for stable and unstable systems. The methods laid out in this survey also integrate solutions for applications with rate-constrained actuators and for bumpless transfer from manual to automatic during system start-up or in override control. Developments in control methods are always supplemented by easily repeated numerical examples. Academics doing control-related research in electronics, mechanics, or mechatronics and engineers working in the process industries will find this book an extremely useful overview of systematic windupprevention for all kinds of systems. It also has valuable insights to offer the graduate student of control.
- The book discusses the recent techniques in NGS data analysis which is the most needed material by biologists (students and researchers) in the wake of numerous genomic projects and the trend toward genomic research. - The book includes both theory and practice for the NGS data analysis. So, readers will understand the concept and learn how to do the analysis using the most recent programs. - The steps of application workflows are written in a manner that can be followed for related projects. - Each chapter includes worked examples with real data available on the NCBI databases. Programming codes and outputs are accompanied with explanation. - The book content is suitable as teaching material for biology and bioinformatics students. Meets the requirements of a complete semester course on Sequencing Data Analysis Covers the latest applications for Next Generation Sequencing Covers data reprocessing, genome assembly, variant discovery, gene profiling, epigenetics, and metagenomics
This book reports on the latest advances in the study of Networked Control Systems (NCSs). It highlights novel research concepts on NCSs; the analysis and synthesis of NCSs with special attention to their networked character; self- and event-triggered communication schemes for conserving limited network resources; and communication and control co-design for improving the efficiency of NCSs. The book will be of interest to university researchers, control and network engineers, and graduate students in the control engineering, communication and network sciences interested in learning the core principles, methods, algorithms and applications of NCSs.
This book includes significant recent research on robotic algorithms. It has been written by leading experts in the field. The 15th Workshop on the Algorithmic Foundations of Robotics (WAFR) was held on June 22-24, 2022, at the University of Maryland, College Park, Maryland. Each chapter represents an exciting state-of-the-art development in robotic algorithms that was presented at this 15th incarnation of WAFR. Different chapters combine ideas from a wide variety of fields, spanning and combining planning (for tasks, paths, motion, navigation, coverage, and patrol), computational geometry and topology, control theory, machine learning, formal methods, game theory, information theory, and theoretical computer science. Many of these papers explore new and interesting problems and problem variants that include human-robot interaction, planning and reasoning under uncertainty, dynamic environments, distributed decision making, multi-agent coordination, and heterogeneity.
Contains case studies from engineering and operations research Includes commented literature for each chapter
This book is written in a clear and thorough way to cover both the traditional and modern uses of Artificial Intelligence and soft computing. It gives an in-depth look at mathematical models, algorithms, and real-world problems that are hard to solve in MATLAB. The book is intended to provide a broad and in-depth understanding of fuzzy logic controllers, genetic algorithms, neural networks, and hybrid techniques such as ANFIS and the GA-ANN model. Key Features: A detailed description of basic intelligent techniques(Fuzzy logic, Genetic algorithm & neural network using MATLAB) A detailed description of the hybrid intelligent technique: Adaptive fuzzy inference technique(ANFIS) Formulation of the nonlinear model like Analysis of ANOVA & Response Surface Methodology Variety of solved problem on ANOVA & RSM Case studies of above mentioned intelligent techniques on the different process control system This book can be used as a handbook and a guide for students of all engineering disciplines, operational research areas, computer applications, and for various professionals who work in the optimization area.
During the last decades, applications of dynamical analysis in advanced, often nonlinear, engineering systems have been evolved in a revolutionary way. In this context one can think of applications in aerospace engineering like satellites, in naval engineering like ship motion, in mechanical engineering like rotating machinery, vehicle systems, robots and biomechanics, and in civil engineering like earthquake dynamics and offshore technology. One could continue with this list for a long time. The application of advanced dynamics in the above fields has been possible due to the use of sophisticated computational techniques employing powerful concepts of nonlinear dynamics. These concepts have been and are being developed in mathematics, mechanics and physics. It should be remarked that careful experimental studies are vitally needed to establish the real existence and observability of the predicted dynamical phenomena. The interaction between nonlinear dynamics and nonlinear control in advanced engineering systems is becoming of increasing importance because of several reasons. Firstly, control strategies in nonlinear systems are used to obtain desired dynamic behaviour and improved reliability during operation, Applications include power plant rotating machinery, vehicle systems, robotics, etc. Terms like motion control, optimal control and adaptive control are used in this field of interest. Since mechanical and electronic components are often necessary to realize the desired action in practice, the engineers use the term mechatronics to indicate this field. If the desired dynamic behaviour is achieved by changing design variables (mostly called system parameters), one can think of fields like control of chaos.
This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security.
Advanced technologies such as robotics, 5G mobile communications, IoT, cloud computing and wireless sensor networks have had a huge impact and influence on manufacturing, with an increased collaboration between humans and smart systems. As the manufacturing process becomes more automated using real-time data, communication systems, Artificial Intelligence (AI) techniques and robotics feed data back into the manufacturing process. This enables the design of products that are more customized and personal, and leads to a more competitive, efficient and value-added production process by reacting more quickly to technical or human errors to avoid product and system damage while increasing workplace safety, and reducing waste, pollution, and associated costs. This edited book covers challenges, concepts, systems, architectures, technologies, and design characteristics of human-machine cooperation and interaction systems in smart manufacturing environments using state of the art technologies including AI, 5G, IoTs, Blockchains, CPS, sensing, automation and robotics. The book is aimed at researchers and engineers working on the applications of robotics and automation, HMI, HCI, CPS, sensing, information and communications technology, data science, ML/DL/AI, AR/VR, cybersecurity and electronics. It is also a useful reference for advanced students and lecturers in these fields, and will appeal to manufacturers and automation system developers.
This second edition of Precision Motion Control focuses on enabling technologies for precision engineering. It has been extensively edited and rewritten throughout with the following particular areas being expanded or added: * piezoelectric actuators * fine movement control * gantry-stage control * interpolation of quadrature encoder signals * geometrical error modeling for single-, dual- and general-XY-axis stages.
Much work on analysis and synthesis problems relating to the multiple model approach has already been undertaken. This has been motivated by the desire to establish the problems of control law synthesis and full state estimation in numerical terms.In recent years, a general approach based on multiple LTI models (linear or affine) around various function points has been proposed. This so-called multiple model approach is a convex polytopic representation, which can be obtained either directly from a nonlinear mathematical model, through mathematical transformation or through linearization around various function points.This book concentrates on the analysis of the stability and synthesis of control laws and observations for multiple models. The authors' approach is essentially based on Lyapunov's second method and LMI formulation. Uncertain multiple models with unknown inputs are studied and quadratic and non-quadratic Lyapunov functions are also considered.
Navigation in Space by X-ray Pulsars will consist of two parts. One is on modeling of X-ray pulsar signals. The second part explains how X-ray pulsar signals can be used to solve the relative navigation problem. This book formulates the problem, proposes a recursive solution, and analyzes different aspects of the navigation system. This book will be a comprehensive source for researchers. It provides new research results on signal processing techniques needed for X-ray pulsar based navigation in deep space.
This book introduces a family of large-signal stability-based control methods for different power inverters (grid-connected inverter, standalone inverter, single-phase inverter, and three-phase inverter) in practical applications. Power inverters have stability issues, which include the inverter's own instability as well as the inverter's instability in relation to the other power electronic devices in the system (i.e., weak grid and the EMI filter). Most of the stability analyses and solutions are based on small-signal stability technology. Unfortunately, in actuality, the majority of practical instability concerns in power inverter systems are large-signal stability problems, which, when compared to small-signal stability problems, can cause substantial damage to electrical equipment. As a result, researchers must conduct a comprehensive investigation of the large-signal stability challenge and solutions for power inverters. This book can be used as a reference for researchers, power inverters manufacturers, and end-users. As a result, the book will not become obsolete in the near future, regardless of technology advancements.
Over the last few decades, both the aeronautics and space disciplines have greatly influenced advances in controls, sensors, data fusion and navigation. Many of those achievements that made the word "aerospace" synonymous with "high-tech" were enabled by innovations in guidance, navigation and control. Europe has seen a strong trans-national consolidation process in aerospace over the last few decades. Most of the visible products, like commercial aircraft, fighters, helicopters, satellites, launchers or missiles, are not made by a single country - they are the fruits of cooperation. No European country by itself hosts a specialized guidance, navigation and controls community large enough to cover the whole spectrum of disciplines. However, on a European scale, mutual exchange of ideas, concepts and solutions is enriching for all. The 1st CEAS Specialist Conference on Guidance, Navigation and Control is an attempt to bring this community together. This book is a selection of papers presented at the conference. All submitted papers have gone through a formal review process in compliance with good journal practices. The best papers have been recommended by the reviewers to be published in this book."
This book introduces several appearance-based place recognition pipelines based on different mapping techniques for addressing loop-closure detection in mobile platforms with limited computational resources. The motivation behind this book has been the prospect that in many contemporary applications efficient methods are needed that can provide high performance under run-time and memory constraints. Thus, three different mapping techniques for addressing the task of place recognition for simultaneous localization and mapping (SLAM) are presented. The book at hand follows a tutorial-based structure describing each of the main parts needed for a loop-closure detection pipeline to facilitate the newcomers. It mainly goes through a historical review of the problem, focusing on how it was addressed during the years reaching the current age. This way, the reader is initially familiarized with each part while the place recognition paradigms follow.
Reset Control Systems addresses the analysis for reset control treating both its basic form, and some useful variations of the reset action and reset condition. The issues regarding reset control - concepts and motivation; analysis tools; and the application of design methodologies to real-world examples - are given thorough coverage. The text opens with a historical perspective which moves from the seminal work of the Clegg integrator and Horowitz FORE to more recent approaches based on impulsive/hybrid control systems and explains the motivation for reset compensation. Preliminary material is also included. The focus then turns to stability analysis for systems using techniques which account for various time- and frequency-domain criteria. The final section of the book is centered on control systems design and application. The PI+CI compensator is detailed as are a proposed frequency domain approach using quantitative feedback theory and ideas for design improvement. Design examples are given.
Autonomous manipulation is a challenge in robotic technologies. It refers to the capability of a mobile robot system with one or more manipulators that performs intervention tasks requiring physical contacts in unstructured environments and without continuous human supervision. Achieving autonomous manipulation capability is a quantum leap in robotic technologies as it is currently beyond the state of the art in robotics. This book addresses issues with the complexity of the problems encountered in autonomous manipulation including representation and modeling of robotic structures, kinematic and dynamic robotic control, kinematic and algorithmic singularity avoidance, dynamic task priority, workspace optimization and environment perception. Further development in autonomous manipulation should be able to provide robust improvements of the solutions for all of the above issues. The book provides an extensive tract on sensory-based autonomous manipulation for intervention tasks in unstructured environments. After presenting the theoretical foundations for kinematic and dynamic modelling as well as task-priority based kinematic control of multi-body systems, the work is focused on one of the most advanced underwater vehicle-manipulator system, SAUVIM (Semi-Autonomous Underwater Vehicle for Intervention Missions). Solutions to the problem of target identification and localization are proposed, a number of significant case studies are discussed and practical examples and experimental/simulation results are presented. The book may inspire the robot research community to further investigate critical issues in autonomous manipulation and to develop robot systems that can profoundly impact our society for the better."
This monograph presents new model-based design methods for trajectory planning, feedback stabilization, state estimation, and tracking control of distributed-parameter systems governed by partial differential equations (PDEs). Flatness and backstepping techniques and their generalization to PDEs with higher-dimensional spatial domain lie at the core of this treatise. This includes the development of systematic late lumping design procedures and the deduction of semi-numerical approaches using suitable approximation methods. Theoretical developments are combined with both simulation examples and experimental results to bridge the gap between mathematical theory and control engineering practice in the rapidly evolving PDE control area. The text is divided into five parts featuring: - a literature survey of paradigms and control design methods for PDE systems - the first principle mathematical modeling of applications arising in heat and mass transfer, interconnected multi-agent systems, and piezo-actuated smart elastic structures - the generalization of flatness-based trajectory planning and feedforward control to parabolic and biharmonic PDE systems defined on general higher-dimensional domains - an extension of the backstepping approach to the feedback control and observer design for parabolic PDEs with parallelepiped domain and spatially and time varying parameters - the development of design techniques to realize exponentially stabilizing tracking control - the evaluation in simulations and experiments Control of Higher-Dimensional PDEs - Flatness and Backstepping Designs is an advanced research monograph for graduate students in applied mathematics, control theory, and related fields. The book may serve as a reference to recent developments for researchers and control engineers interested in the analysis and control of systems governed by PDEs.
This book describes the practical application of artificial intelligence (AI) methods using time series data in system control. This book consistently discusses the application of machine learning to the analysis and modelling of time series data of physical quantities to be controlled in the field of system control. Since dynamic systems are not stable steady states but changing transient states, the changing transient states depend on the state history before the change. In other words, it is essential to predict the change from the present to the future based on the time history of each variable in the target system, and to manipulate the system to achieve the desired change. In short, time series is the key to the application of AI machine learning to system control. This is the philosophy of this book: "time series data" + "AI machine learning" = "new practical control methods". This book can give my helps to undergradate or graduate students, institute researchers and senior engineers whose scientific background are engineering, mathematics, physics and other natural sciences.
The area of hybrid dynamical systems (HDS) represents a difficult and exciting challenge to control engineers and is referred to as "the control theory of tomorrow" because of its future potential for solving problems. This relatively new discipline bridges control engineering, mathematics, and computer science. There is now an emerging literature on this topic describing a number of mathematical models, heuristic algorithms, and stability criteria. However, presently there is no systematic theory of HDS. "Hybrid Dynamical Systems" focuses on a comprehensive development of HDS theory and integrates results established by the authors. The work is a self-contained informative text/reference, covering several theoretically interesting and practically significant problems concerning the use of switched controllers and examining the sensor scheduling problem. The emphasis is on classes of uncertain systems as models for HDS. Features and topics: * Focuses on the design of robust HDS in a logical and clear manner * Applies the hybrid control systems framework to two classical robust control problems: design of an optimal stable controller for a linear system and simultaneous stabilization of a collection of plants * Presents a detailed treatment of stability and H-infinity control problems for a class of HDS * Covers recent original results with complete mathematically rigorous proofs Researchers and postgraduate students in control engineering, applied mathematics, and theoretical computer science will find this book covers the latest results on this important area of research. Advanced engineering practitioners and applied researchers working in areas of controlengineering, signal processing, communications, and fault detection will find this book an up-to-date resource.
This book tackles the problem of overshoot and undershoot in blood glucose levels caused by delay in the effects of carbohydrate consumption and insulin administration. The ideas presented here will be very important in maintaining the welfare of insulin-dependent diabetics and avoiding the damaging effects of unpredicted swings in blood glucose - accurate prediction enables the implementation of counter-measures. The glucose prediction algorithms described are also a key and critical ingredient of automated insulin delivery systems, the so-called "artificial pancreas". The authors address the topic of blood-glucose prediction from medical, scientific and technological points of view. Simulation studies are utilized for complementary analysis but the primary focus of this book is on real applications, using clinical data from diabetic subjects. The text details the current state of the art by surveying prediction algorithms, and then moves beyond it with the most recent advances in data-based modeling of glucose metabolism. The topic of performance evaluation is discussed and the relationship of clinical and technological needs and goals examined with regard to their implications for medical devices employing prediction algorithms. Practical and theoretical questions associated with such devices and their solutions are highlighted. This book shows researchers interested in biomedical device technology and control researchers working with predictive algorithms how incorporation of predictive algorithms into the next generation of portable glucose measurement can make treatment of diabetes safer and more efficient.
Brain and Behavior Computing offers insights into the functions of the human brain. This book provides an emphasis on brain and behavior computing with different modalities available such as signal processing, image processing, data sciences, statistics further it includes fundamental, mathematical model, algorithms, case studies, and future research scopes. It further illustrates brain signal sources and how the brain signal can process, manipulate, and transform in different domains allowing researchers and professionals to extract information about the physiological condition of the brain. Emphasizes real challenges in brain signal processing for a variety of applications for analysis, classification, and clustering. Discusses data sciences and its applications in brain computing visualization. Covers all the most recent tools for analysing the brain and it's working. Describes brain modeling and all possible machine learning methods and their uses. Augments the use of data mining and machine learning to brain computer interface (BCI) devices. Includes case studies and actual simulation examples. This book is aimed at researchers, professionals, and graduate students in image processing and computer vision, biomedical engineering, signal processing, and brain and behavior computing. |
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