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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering
Rescue Robotics presents the most significant findings of the DDT Project on robots and systems for urban search and rescue. This project was launched by the Japanese government in 2002 with the aim of applying a wide variety of robotics technologies to find a solution to the problem of disaster response, especially urban search and rescue in large-scale earthquakes. From 2002 to 2007 more than 100 researchers took part in the DDT Project, coming from a wide spectrum of research and development to make up four research groups: Aerial Robot Systems MU (Mission Unit), Information Infrastructure System MU, In-Rubble Robot System MU, and On-Rubble Robot System MU. This book discusses their development and testing of various robotic systems and technologies such as serpentine robots, traced vehicles, intelligent human interface and data processing, as well as analysing and verifying the results of these experiments. Rescue Robotics will be of interest to researchers and students, but will also prove useful for emergency response personnel. It offers an insight into the state of the art of rescue robotics and its readers will benefit from a knowledge of the advanced technologies involved in this field.
Optimization is an integral part to science and engineering. Most real-world applications involve complex optimization processes, which are di?cult to solve without advanced computational tools. With the increasing challenges of ful?lling optimization goals of current applications there is a strong drive to advancethe developmentofe?cientoptimizers. The challengesintroduced by emerging problems include: * objective functions which are prohibitively expensive to evaluate, so ty- callysoonlyasmallnumber ofobjectivefunctionevaluationscanbemade during the entire search, * objective functions which are highly multimodal or discontinuous, and * non-stationary problems which may change in time (dynamic). Classical optimizers may perform poorly or even may fail to produce any improvement over the starting vector in the face of such challenges. This has motivated researchers to explore the use computational intelligence (CI) to augment classical methods in tackling such challenging problems. Such methods include population-based search methods such as: a) evolutionary algorithms and particle swarm optimization and b) non-linear mapping and knowledgeembedding approachessuchasarti?cialneuralnetworksandfuzzy logic, to name a few. Such approaches have been shown to perform well in challenging settings. Speci?cally, CI are powerful tools which o?er several potential bene?ts such as: a) robustness (impose little or no requirements on the objective function) b) versatility (handle highly non-linear mappings) c) self-adaptionto improveperformance and d) operationin parallel(making it easy to decompose complex tasks). However, the successful application of CI methods to real-world problems is not straightforward and requires both expert knowledge and trial-and-error experiments.
This book presents cutting-edge results on stability analysis and control scheme designs for networked teleoperation systems. It highlights new research on commonly encountered nonlinear teleoperation systems, including the stability analysis of teleoperation systems with asymmetric time-varying delays, stability analysis of teleoperation systems with interval time delays, and so on. Moreover, the book presents several high-performance control scheme designs for teleoperation systems when the velocity is available and unavailable, and for systems with nonlinear input. The results presented here mark a substantial contribution to nonlinear teleoperation system theory, robotic control theory and networked control system theory. As such, the book will be of interest to university researchers, R&D engineers and graduate students in control theory and control engineering who wish to learn about the core principles, methods, algorithms, and applications of networked teleoperation systems, robotic systems and nonlinear control systems.
Cost Oriented Automation 2004 addresses a new integration environment that enables the evolution of collaborative e-design paradigm. This design paradigm aims at seamless and dynamic integration of distributed design objects and engineering tools over the internet.
This book presents recent advances in the field of intelligent systems. Composed of fourteen selected chapters, it covers a wide range of research that varies from applications in industrial data science to those in applied science. Today the word INNOVATION is more and more connected with the words INTELLIGENT and SECURITY, as such the book discusses the theory and applications of hot topics such as big data, education applications of robots with different levels of autonomy, knowledge-based modeling and control of complex dynamical systems, sign-based synthesis of behavior, security issues with intelligent systems, innovative intelligent control design, neuromorphic computation, data-driven classification, intelligent modeling and measurement innovations, multisensor data association, personal education assistants, a modern production architecture, study of peer review and scientometrics, intelligent research on bug report data, and clustering non-Gaussian data. The broad and varied research discussed represents the mainstream of contemporary intelligent innovations that are slowly but surely changing the world.
This authoritative reference work will provide readers with a complete overview of artificial intelligence (AI), including its historic development and current status, existing and projected AI applications, and present and potential future impact on the United States and the world. Some people believe that artificial intelligence (AI) will revolutionize modern life in ways that improve human existence. Others say that the promise of AI is overblown. Still others contend that AI applications could pose a grave threat to the economic security of millions of people by taking their jobs and otherwise rendering them "obsolete"-or, even worse, that AI could actually spell the end of the human race. This volume will help users understand the reasons AI development has both spirited defenders and alarmed critics; explain theories and innovations like Moore's Law, mindcloning, and Technological Singularity that drive AI research and debate; and give readers the information they need to make their own informed judgment about the promise and peril of this technology. All of this coverage is presented using language and terminology accessible to a lay audience. Introduction explaining the historical evolution of AI Chronology of important AI-related events Authoritative entries on leading pioneers, entrepreneurs, and thinkers; AI concepts and theories; AI's potential impact on different facets of society; and major movies and other cultural touchstones exploring AI technology
Internal combustion engines (ICE) still have potential for substantial improvements, particularly with regard to fuel efficiency and environmental compatibility. In order to fully exploit the remaining margins, increasingly sophisticated control systems have to be applied. This book offers an introduction to cost-effective model-based control-system design for ICE. The primary emphasis is put on the ICE and its auxiliary devices. Mathematical models for these processes are developed and solutions for selected feedforward and feedback control-problems are presented. The discussions concerning pollutant emissions and fuel economy of ICE in automotive applications constantly intensified since the first edition of this book was published. Concerns about the air quality, the limited resources of fossil fuels and the detrimental effects of greenhouse gases exceedingly spurred the interest of both the industry and academia in further improvements. The most important changes and additions included in this second edition are: restructured and slightly extended section on superchargers, short subsection on rotational oscillations and their treatment on engine test-benches, complete section on modeling, detection, and control of engine knock, improved physical and chemical model for the three-way catalytic converter, new methodology for the design of an air-to-fuel ratio controller, short introduction to thermodynamic engine-cycle calculation and corresponding control-oriented aspects.
The book offers a comprehensive overview of controllability problems and minimum energy control for broad classes of dynamical systems, including linear, semilinear and nonlinear systems, which are important for modeling systems in automatic control, electrical engineering, mechanics and informatics. It develops the theory of controllability for both finite and infinite dimensional dynamical systems described by differential state equation, and studies in detail functional analysis and matrix algebra, which provide essential and effective tools for the new solutions of a number of important controllability problems. The theoretical results are illustrated by examples throughout the book. Primarily intended for academic researchers working in mathematical control theory, the self-contained text is easily accessible and particularly interesting for control engineering and applied mathematics graduates.
While domain decomposition methods have a long history dating back well over one hundred years, it is only during the last decade that they have become a major tool in numerical analysis of partial differential equations. This monograph emphasizes domain decomposition methods in the context of so-called virtual optimal control problems and treats optimal control problems for partial differential equations and their decompositions using an all-at-once approach.
Robotized Transcranial Magnetic Stimulation describes the methods needed to develop a robotic system that is clinically applicable for the application of transcranial magnetic stimulation (TMS). Chapter 1 introduces the basic principles of TMS and discusses current developments towards robotized TMS. Part I (Chapters 2 and 3) systematically analyzes and clinically evaluates robotized TMS. More specifically, it presents the impact of head motion on the induced electric field. In Part II (Chapters 3 to 8), a new method for a robust robot/camera calibration, a sophisticated force-torque control with hand-assisted positioning, a novel FTA-sensor for system safety, and techniques for direct head tracking, are described and evaluated. Part III discusses these developments in the context of safety and clinical applicability of robotized TMS and presents future prospects of robotized TMS. Robotized Transcranial Magnetic Stimulation is intended for researchers as a guide for developing effective robotized TMS solutions. Professionals and practitioners may also find the book valuable.
This book presents techniques that enable mobile manipulation robots to autonomously adapt to new situations. Covers kinematic modeling and learning; self-calibration; tactile sensing and object recognition; imitation learning and programming by demonstration.
Multi-agent systems have numerous civilian, homeland security, and military applications; however, for all these applications, communication bandwidth, sensing range, power constraints, and stealth requirements preclude centralized command and control. The alternative is distributed coordination, which is more promising in terms of scalability, robustness, and flexibility. Distributed Coordination of Multi-agent Networks introduces problems, models, and issues such as collective periodic motion coordination, collective tracking with a dynamic leader, and containment control with multiple leaders, and explores ideas for their solution. Solving these problems extends the existing application domains of multi-agent networks; for example, collective periodic motion coordination is appropriate for applications involving repetitive movements, collective tracking guarantees tracking of a dynamic leader by multiple followers in the presence of reduced interaction and partial measurements, and containment control enables maneuvering of multiple followers by multiple leaders. The authors models for distributed coordination arise from physical constraints and the complex environments in which multi-agent systems operate; they include Lagrangian models more realistic for mechanical-systems modeling than point models and fractional-order systems which better represent the consequences of environmental complexity. Other issues addressed in the text include the time delays inherent in networked systems, optimality concerns associated with the deisgn of energy-efficent algorithms, and the use of sampled-data settings in systems with intermittent neightbor-neighbor contact. Researchers, graduate students, and engineers interested in the field of multi-agent systems will find this monograph useful in introducing them to presently emerging research directions and problems in distributed coordination of multi-agent networks. The Communications and Control Engineering series reports major technological advances which have potential for great impact in the fields of communication and control. It reflects research in industrial and academic institutions around the world so that the readership can exploit new possibilities as they become available.
This thesis presents a novel neuro-fuzzy modeling approach for grasp neuroprostheses. At first, it offers a detailed study of discomfort due to the application of Functional Electrical Stimulation to the upper limb. Then, it discusses briefly previous methods to model hand movements induced by FES with the purpose of introducing the new modeling approach based on intelligent systems. This approach is thoroughly described in the book, together with the proposed application to induce hand and finger movements by means of a surface FES system based on multi-field electrodes. The validation tests, carried out on both healthy and neurologically impaired subjects, demonstrate the efficacy of the proposed modeling method. All in all, the book proposes an innovative system based on fuzzy neural networks that is expected to improve the design and validation of advanced control systems for non-invasive grasp neuroprostheses.
This monograph has arisen from the multidisciplinary research extending over biology, robotics and hybrid systems theory. It is inspired by modeling reactive behavior of the immune system cell population, where each cell is considered an independent agent. The authors formulate the optimal control of maximizing the probability of robotic presence in a given region and discuss the application of the Minimum Principle for partial differential equations to this problem.
Proportionala "integrala "derivative (PID) controllers are the most adopted controllers in industrial settings because of the advantageous cost/benefit ratio they are able to provide. Despite their long history and the know-how gained from years of experience, the availability of microprocessors and software tools and the increasing demand for higher product quality at reduced cost have stimulated researchers to devise new methodologies to improve their performance and make them easier to use. Practical PID Control covers important issues that arise when a PID controller is to be applied in practical cases. Its focus is on those functionalities that can provide significant improvements in performance in combination with a sound tuning of parameters. In particular, the choice of filter to make the controller proper, the use of a feedforward action and the selection of an anti-windup strategy are addressed. Further, the choice of the identification algorithm and of the model reduction technique are analysed in the context of model-based PID control. Widely adopted PID-based control architectures (ratio and cascade control) and performance assessment are also covered. For these topics, recent contributions are explained and compared with more standard approaches. A large number of simulation and experimental results are provided in order better to illustrate the different methodologies and to discuss their pros and cons. Practical PID Control is a helpful and instructive reference for researchers, graduate students and practitioners in process control.
From the reviews: "The book is an excellent combination of theory and real-world applications. Each application not only demonstrates the power of the theoretical results but also is important on its own behalf." IEEE Control Systems Magazine
TheThird International Workshop on Multi-Robot Systems was held in March 2005 at the Naval Research Laboratory in Washington, D. C. , USA. Bringing together leading researchers and government sponsors for three days of technicalinterchange on multi-robot systems, theworkshop follows two previous highly successful gatherings in 2002 and 2003. Likethe previous two workshops, the meeting began with presentations byvarious government p- gram managers describing application areas and programs with an interest in multi-robot systems. U. S. Government representatives were on handfrom theOf?ce of Naval Research and several other governmental of?ces. Top - searchers inthe ?eld then presented their current activities in many areas of multi-robot systems. Presentations spannedawide rangeof topics, incl- ing task allocation, coordination in dynamicenvironments, information/sensor sharing andfusion, distributed mapping and coverage, motion planning and control, human-robot interaction, and applications of multi-robot systems. All presentations were given in a single-track workshop format. This proce- ings documents the work presented at the workshop. The research presen- tions were followed by panel discussions, in which all participants interacted to highlight the challenges of this ?eld and to develop possible solutions. In addition to the invited research talks, researchers and students were given an opportunity to present their work at poster sessions. We would like to thank the Naval Research Laboratory for sponsoring this workshop and providing the - cilitiesforthesemeetingstotakeplace. WeareextremelygratefultoMagdalena Bugajska, Paul Wiegand, and Mitchell A. Potter, for their vital help (and long hours) in editing these proceedings and to Michelle Caccivio for providing the administrative support to the workshop.
This book demonstrates how to describe and analyze a system's behavior and extract the desired prediction and control algorithms from this analysis. A typical prediction is based on observing similar situations in the past, knowing the outcomes of these past situations, and expecting that the future outcome of the current situation will be similar to these past observed outcomes. In mathematical terms, similarity corresponds to symmetry, and similarity of outcomes to invariance. This book shows how symmetries can be used in all classes of algorithmic problems of sciences and engineering: from analysis to prediction to control. Applications cover chemistry, geosciences, intelligent control, neural networks, quantum physics, and thermal physics. Specifically, it is shown how the approach based on symmetry and similarity can be used in the analysis of real-life systems, in the algorithms of prediction, and in the algorithms of control.
This is a book for engineers that covers the hardware and software
aspects of high-reliability safety systems, safety instrumentation
and shutdown systems as well as risk assessment techniques and the
wider spectrum of industrial safety. Rather than another book on
the discipline of safety engineering, this is a thoroughly
practical guide to the procedures and technology of safety in
control and plant engineering. This highly practical book focuses
on efficiently implementing and assessing hazard studies, designing
and applying international safety practices and techniques, and
ensuring high reliability in the safety and emergency shutdown of
systems in your plant.
Integral processes with dead time are frequently encountered in the process industry; typical examples include supply chains, level control and batch distillation columns. Special attention must be paid to their control because they lack asymptotic stability (they are not self-regulating) and because of their delays. As a result, many techniques have been devised to cope with these hurdles both in the context of single-degree-of-freedom (proportional-integral-differential (PID)) and two-degree-of-freedom control schemes. Control of Integral Processes with Dead Time provides a unified and coherent review of the various approaches devised for the control of integral processes, addressing the problem from different standpoints. In particular, the book treats the following topics: how to tune a PID controller and assess its performance; how to design a two-degree-of-freedom control scheme in order to deal with both the set-point following and load disturbance rejection tasks; how to modify the basic Smith predictor control scheme in order to cope with the presence of an integrator in the process; and how to address the presence of large process dead times. The methods are presented sequentially, highlighting the evolution of their rationale and implementation and thus clearly characterising them from both academic and industrial perspectives. Control of Integral Processes with Dead Time will serve academic researchers in systems with dead time both as a reference and stimulus for new ideas for further work and will help industry-based control and process engineers to solve their control problems using the most suitable technique and achieving the best cost: benefit ratio."
The book addresses the control issues such as stability analysis, control synthesis and filter design of Markov jump systems with the above three types of TPs, and thus is mainly divided into three parts. Part I studies the Markov jump systems with partially unknown TPs. Different methodologies with different conservatism for the basic stability and stabilization problems are developed and compared. Then the problems of state estimation, the control of systems with time-varying delays, the case involved with both partially unknown TPs and uncertain TPs in a composite way are also tackled. Part II deals with the Markov jump systems with piecewise homogeneous TPs. Methodologies that can effectively handle control problems in the scenario are developed, including the one coping with the asynchronous switching phenomenon between the currently activated system mode and the controller/filter to be designed. Part III focuses on the Markov jump systems with memory TPs. The concept of -mean square stability is proposed such that the stability problem can be solved via a finite number of conditions. The systems involved with nonlinear dynamics (described via the Takagi-Sugeno fuzzy model) are also investigated. Numerical and practical examples are given to verify the effectiveness of the obtained theoretical results. Finally, some perspectives and future works are presented to conclude the book.
This book presents the most recent research advances in the theory, design, control, and application of robotic systems, which are intended for a variety of purposes such as manipulation, manufacturing, automation, surgery, locomotion, and biomechanics. |
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