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Qualitative Analysis And Control Of Complex Neural Networks With Delays

Author: Zhanshan Wang
Publisher: Springer
ISBN: 3662474840
Size: 45.62 MB
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This book focuses on the stability of the dynamical neural system, synchronization of the coupling neural system and their applications in automation control and electrical engineering. The redefined concept of stability, synchronization and consensus are adopted to provide a better explanation of the complex neural network. Researchers in the fields of dynamical systems, computer science, electrical engineering and mathematics will benefit from the discussions on complex systems. The book will also help readers to better understand the theory behind the control technique and its design.

Learning Based Adaptive Control

Author: Mouhacine Benosman
Publisher: Butterworth-Heinemann
ISBN: 0128031514
Size: 46.73 MB
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Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained. Includes a good number of Mechatronics Examples of the techniques. Compares and blends Model-free and Model-based learning algorithms. Covers fundamental concepts, state-of-the-art research, necessary tools for modeling, and control.

Cyber Physical Systems Decision Making Mechanisms And Applications

Author: Kostas Siozios
Publisher: River Publishers
ISBN: 8793609094
Size: 76.46 MB
Format: PDF
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As systems continue to evolve they rely less on human decision-making and more on computational intelligence. This trend in conjunction with the available technologies for providing advanced sensing, measurement, process control, and communication lead towards the new field of the CyberPhysical System (CPS). CyberPhysical systems are expected to play a major role in the design and development of future engineering platforms with new capabilities that far exceed today's levels of autonomy, functionality and usability. Although these systems exhibit remarkable characteristics, their design and implementation is a challenging issue, as numerous (heterogeneous) components and services have to be appropriately modeled and simulated together. The problem of designing efficient CPS becomes far more challenging in case the target system has to meet also real-time constraints. CyberPhysical Systems: Decision Making Mechanisms and Applications describes essential theory, recent research and large-scale user cases that addresses urgent challenges in CPS architectures. In particular, it includes chapters on: Decision making for large scale CPSModeling of CPS with emphasis at the control mechanismsHardware/software implementation of the control mechanismsFault-tolerant and reliability issues for the control mechanismsCyberPhysical user-cases that incorporate challenging decision making

Complex Systems

Author: Georgi M. Dimirovski
Publisher: Springer
ISBN: 3319288601
Size: 53.85 MB
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This book gives a wide-ranging description of the many facets of complex dynamic networks and systems within an infrastructure provided by integrated control and supervision: envisioning, design, experimental exploration, and implementation. The theoretical contributions and the case studies presented can reach control goals beyond those of stabilization and output regulation or even of adaptive control. Reporting on work of the Control of Complex Systems (COSY) research program, Complex Systems follows from and expands upon an earlier collection: Control of Complex Systems by introducing novel theoretical techniques for hard-to-control networks and systems. The major common feature of all the superficially diverse contributions encompassed by this book is that of spotting and exploiting possible areas of mutual reinforcement between control, computing and communications. These help readers to achieve not only robust stable plant system operation but also properties such as collective adaptivity, integrity and survivability at the same time retaining desired performance quality. Applications in the individual chapters are drawn from: • the general implementation of model-based diagnosis and systems engineering in medical technology, in communication, and in power and airport networks; • the creation of biologically inspired control brains and safety-critical human–machine systems, • process-industrial uses; • biped robots; • large space structures and unmanned aerial vehicles; and • precision servomechanisms and other advanced technologies. Complex Systems provides researchers from engineering, applied mathematics and computer science backgrounds with innovative theoretical and practical insights into the state-of-the-art of complex networks and systems research. It employs physical implementations and extensive computer simulations. Graduate students specializing in complex-systems research will also learn much from this collection./pp

Computationally Efficient Model Predictive Control Algorithms

Author: Maciej Lawrynczuk
Publisher: Springer Science & Business Media
ISBN: 3319042297
Size: 68.39 MB
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This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: · A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. · Implementation details of the MPC algorithms for feed forward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. · The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). · The MPC algorithms with neural approximation with no on-line linearization. · The MPC algorithms with guaranteed stability and robustness. · Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require demanding on-line nonlinear optimization. The presented simulation results demonstrate high accuracy and computational efficiency of the algorithms. For a few representative nonlinear benchmark processes, such as chemical reactors and a distillation column, for which the classical MPC algorithms based on linear models do not work properly, the trajectories obtained in the suboptimal MPC algorithms are very similar to those given by the ``ideal'' MPC algorithm with on-line nonlinear optimization repeated at each sampling instant. At the same time, the suboptimal MPC algorithms are significantly less computationally demanding.

Intelligent Production Machines And Systems 2nd I Proms Virtual International Conference 3 14 July 2006

Author: Duc T. Pham
Publisher: Elsevier
ISBN: 0080556345
Size: 46.66 MB
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I*PROMS 2005 is an online web-based conference. It provides a platform for presenting, discussing, and disseminating research results contributed by scientists and industrial practitioners active in the area of intelligent systems and soft computing techniques (such as fuzzy logic, neural networks, evolutionary algorithms, and knowledge-based systems) and their application in different areas of manufacturing. Comprised of 100 peer-reviewed articles, this important resource provides tools to help enterprises achieve goals critical to the future of manufacturing. I*PROMS is an European Union-funded network that involves 30 partner organizations and more than 130 researchers from universities, research organizations, and corporations. * State-of-the-art research results * Leading European researchers and industrial practitioners * Comprehensive collection of indexed and peer-reviewed articles in book format supported by a user-friendly full-text CD-ROM with search functionality

Information Engineering And Applications

Author: Rongbo Zhu
Publisher: Springer Science & Business Media
ISBN: 1447123867
Size: 38.67 MB
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In past twenty years or so, information technology has influenced and changed every aspect of our lives and our cultures. Without various IT-based applications, we would find it difficult to keep information stored securely, to process information and business efficiently, and to communicate information conveniently. In the future world, ITs and information engineering will play a very important role in convergence of computing, communication, business and all other computational sciences and application and it also will influence the future world's various areas, including science, engineering, industry, business, law, politics, culture and medicine. The International Conference on Information Engineering and Applications (IEA) 2011 is intended to foster the dissemination of state-of-the-art research in information and business areas, including their models, services, and novel applications associated with their utilization. International Conference on Information Engineering and Applications (IEA) 2011 is organized by Chongqing Normal University, Chongqing University, Shanghai Jiao Tong University, Nanyang Technological University, University of Michigan and the Chongqing University of Arts and Sciences, and is sponsored by National Natural Science Foundation of China (NSFC). The objective of IEA 2011 is to will provide a forum for engineers and scientists in academia, industry, and government to address the most innovative research and development . Information Engineering and Applications provides a summary of this conference including contributions for key speakers on subjects such as technical challenges, social and economic issues, and ideas, results and current work on all aspects of advanced information and business intelligence.

Self Learning Optimal Control Of Nonlinear Systems

Author: Qinglai Wei
Publisher: Springer
ISBN: 981104080X
Size: 47.11 MB
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This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum. With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering.

Handbook Of Neural Computing Applications

Author: Alianna J. Maren
Publisher: Academic Press
ISBN: 148326484X
Size: 40.87 MB
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Handbook of Neural Computing Applications is a collection of articles that deals with neural networks. Some papers review the biology of neural networks, their type and function (structure, dynamics, and learning) and compare a back-propagating perceptron with a Boltzmann machine, or a Hopfield network with a Brain-State-in-a-Box network. Other papers deal with specific neural network types, and also on selecting, configuring, and implementing neural networks. Other papers address specific applications including neurocontrol for the benefit of control engineers and for neural networks researchers. Other applications involve signal processing, spatio-temporal pattern recognition, medical diagnoses, fault diagnoses, robotics, business, data communications, data compression, and adaptive man-machine systems. One paper describes data compression and dimensionality reduction methods that have characteristics, such as high compression ratios to facilitate data storage, strong discrimination of novel data from baseline, rapid operation for software and hardware, as well as the ability to recognized loss of data during compression or reconstruction. The collection can prove helpful for programmers, computer engineers, computer technicians, and computer instructors dealing with many aspects of computers related to programming, hardware interface, networking, engineering or design.

Trends And Research In The Decision Sciences

Author: Decision Sciences Institute
Publisher: FT Press
ISBN: 0133925536
Size: 28.76 MB
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Decision science offers powerful insights and techniques that help people make better decisions to improve business and society. This new volume brings together the peer-reviewed papers that have been chosen as the "best of the best" by the field's leading organization, the Decision Sciences Institute. These papers, authored by respected decision science researchers and academics from around the world, will be presented at DSI's 45th Annual Meeting in Tampa, Florida in November 2014. The first book of papers ever assembled by DSI, this volume describes recent methods and approaches in the decision sciences, with a special focus on how accelerating technological innovation is driving change in the ways organizations and individuals make decisions. These papers offer actionable insights for decision-makers of all kinds, in business, public policy, non-profit organizations, and beyond. They also point to new research directions for academic researchers in decision science worldwide.