Computer-Aided Control Systems Design, Chin, Cheng Siong

Автор: Brunton, Steven L. (university Of Washington) Kutz
Название: Data-driven science and engineering
ISBN: 1009098489 ISBN-13(EAN): 9781009098489
Издательство: Cambridge Academ
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Цена: 52790.00 T
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Описание: Data-driven discovery is revolutionizing how we model, predict, and control complex systems. This text integrates emerging machine learning and data science methods for engineering and science communities. Now with Python and MATLAB (R), new chapters on reinforcement learning and physics-informed machine learning, and supplementary videos and code.

Автор: Alina Gavrilut , Endre Pap
Название: Regular Non-Additive Multimeasures. Fundaments and Applications
ISBN: 3031110994 ISBN-13(EAN): 9783031110993
Издательство: Springer
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Цена: 93160.00 T
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Описание: This book is intended to be an exhaustive study on regularity and other properties of continuity for different types of non-additive multimeasures and with respect to different types of topologies. The book is addressed to graduate and postgraduate students, teachers and all researchers in mathematics, but not only. Since the notions and results offered by this book are closely related to various notions of the theory of probability, this book will be useful to a wider category of readers, using multivalued analysis techniques in areas such as control theory and optimization, economic mathematics, game theory, decision theory, etc. Measure and integration theory developed during the early years of the 20th century is one of the most important contributions to modern mathematical analysis, with important applications in many fields. In the last years, many classical problems from measure theory have been treated in the non-additive case and also extended in the set-valued case. The property of regularity is involved in many results of mathematical analysis, due to its applications in probability theory, stochastic processes, optimal control problems, dynamical systems, Markov chains, potential theory etc.

Автор: Borrelli
Название: Predictive Control for Linear and Hybrid Systems
ISBN: 1107652871 ISBN-13(EAN): 9781107652873
Издательство: Cambridge Academ
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Цена: 63350.00 T
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Описание: With a simple, unified approach, and with consideration of real-time applications, this book covers the theory of stability, feasibility, and robustness of model predictive control (MPC). It is for graduate and postgraduate students, as well as advanced control practitioners interested in the theory and/or implementation of predictive control.

Автор: Dinesh C.S. Bisht, Mangey Ram
Название: Computational Intelligence: Theoretical Advances and Advanced Applications
ISBN: 3110655241 ISBN-13(EAN): 9783110655247
Издательство: Walter de Gruyter
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Цена: 173490.00 T
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Описание: Computational intelligence (CI) lies at the interface between engineering and computer science; control engineering, where problems are solved using computer-assisted methods. Thus, it can be regarded as an indispensable basis for all artificial intelligence (AI) activities. This book collects surveys of most recent theoretical approaches focusing on fuzzy systems, neurocomputing, and nature inspired algorithms. It also presents surveys of up-to-date research and application with special focus on fuzzy systems as well as on applications in life sciences and neuronal computing.

Автор: Corke, Peter
Название: Robotics, Vision and Control, 2 ed.
ISBN: 3319544128 ISBN-13(EAN): 9783319544120
Издательство: Springer
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Описание: Robotic vision, the combination of robotics and computer vision, involves the application of computer algorithms to data acquired from sensors. It weaves together theory, algorithms and examples in a narrative that covers robotics and computer vision separately and together.

Автор: Shao Shuyi, Chen Mou, Shi Peng
Название: Robust Discrete-Time Flight Control of Uav with External Disturbances
ISBN: 3030579565 ISBN-13(EAN): 9783030579562
Издательство: Springer
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Цена: 158380.00 T
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Описание: This book studies selected discrete-time flight control schemes for fixed-wing unmanned aerial vehicle (UAV) systems in the presence of system uncertainties, external disturbances and input saturation.

Автор: Ma, Jun Li
Название: Advanced optimization for motion control systems
ISBN: 0367343398 ISBN-13(EAN): 9780367343392
Издательство: Taylor&Francis
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Цена: 93910.00 T
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Описание: The book is organized into two parts: Part I focuses on the model-based approaches, and Part II presents the data-based approaches. Industrial problems explored in the book are formulated systematically with necessary analysis of the control system synthesis.

Автор: Yinyan Zhang; Shuai Li; Xuefeng Zhou
Название: Deep Reinforcement Learning with Guaranteed Performance
ISBN: 3030333833 ISBN-13(EAN): 9783030333836
Издательство: Springer
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Цена: 121110.00 T
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Описание: 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.

Автор: Zhang, W., Li
Название: Virtual Equivalent System Approach for Stability Analysis of Model-based Control Systems
ISBN: 9811555370 ISBN-13(EAN): 9789811555374
Издательство: Springer
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Цена: 93160.00 T
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Описание: The new concept will facilitate the development of a unified framework for analyzing the stability and convergence of self-tuning control (STC) systems, and potentially, of all adaptive control systems.

Автор: Marco Ceccarelli
Название: Fundamentals of Mechanics of Robotic Manipulation
ISBN: 9048165164 ISBN-13(EAN): 9789048165162
Издательство: Springer
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Цена: 111790.00 T
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Описание: This book has evolved from a course on Mechanics of Robots that the author has thought for over a dozen years at the University of Cassino at Cassino, Italy.

Автор: Pfanne
Название: In-Hand Object Localization and Control: Enabling Dexterous Manipulation with Robotic Hands
ISBN: 3031069668 ISBN-13(EAN): 9783031069666
Издательство: Springer
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Цена: 121110.00 T
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Описание: This book introduces a novel model-based dexterous manipulation framework, which, thanks to its precision and versatility, significantly advances the capabilities of robotic hands compared to the previous state of the art. This is achieved by combining a novel grasp state estimation algorithm, the first to integrate information from tactile sensing, proprioception and vision, with an impedance-based in-hand object controller, which enables leading manipulation capabilities, including finger gaiting. The developed concept is implemented on one of the most advanced robotic manipulators, the DLR humanoid robot David, and evaluated in a range of challenging real-world manipulation scenarios and tasks. This book greatly benefits researchers in the field of robotics that study robotic hands and dexterous manipulation topics, as well as developers and engineers working on industrial automation applications involving grippers and robotic manipulators.

Автор: Emmanouil Amolochitis
Название: Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining
ISBN: 8793609647 ISBN-13(EAN): 9788793609648
Издательство: Taylor&Francis
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Цена: 78590.00 T
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Описание: Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining presents novel algorithms for academic search, recommendation and association rule mining that have been developed and optimized for different commercial as well as academic purpose systems. Along with the design and implementation of algorithms, a major part of the work presented in the book involves the development of new systems both for commercial as well as for academic use. In the first part of the book the author introduces a novel hierarchical heuristic scheme for re-ranking academic publications retrieved from standard digital libraries. The scheme is based on the hierarchical combination of a custom implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. In order to evaluate the performance of the introduced algorithms, a meta-search engine has been designed and developed that submits user queries to standard digital repositories of academic publications and re-ranks the top-n results using the introduced hierarchical heuristic scheme. In the second part of the book the design of novel recommendation algorithms with application in different types of e-commerce systems are described. The newly introduced algorithms are a part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. The initial version of the system uses a novel hybrid recommender (user, item and content based) and provides daily recommendations to all active subscribers of the provider (currently more than 30,000). The recommenders that we are presenting are hybrid by nature, using an ensemble configuration of different content, user as well as item-based recommenders in order to provide more accurate recommendation results.The final part of the book presents the design of a quantitative association rule mining algorithm. Quantitative association rules refer to a special type of association rules of the form that antecedent implies consequent consisting of a set of numerical or quantitative attributes. The introduced mining algorithm processes a specific number of user histories in order to generate a set of association rules with a minimally required support and confidence value. The generated rules show strong relationships that exist between the consequent and the antecedent of each rule, representing different items that have been consumed at specific price levels. This research book will be of appeal to researchers, graduate students, professionals, engineers and computer programmers.