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Titlebook: Computational Intelligence and Optimization Methods for Control Engineering; Maude Josée Blondin,Panos M. Pardalos,Javier Sanch Book 2019

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书目名称Computational Intelligence and Optimization Methods for Control Engineering
编辑Maude Josée Blondin,Panos M. Pardalos,Javier Sanch
视频videohttp://file.papertrans.cn/233/232437/232437.mp4
概述Features case studies (Chapters 3-14) for engineering applications.Utilizes state-of-the-art in control optimization techniques.Provides the reader with future directions and insights into developing
丛书名称Springer Optimization and Its Applications
图书封面Titlebook: Computational Intelligence and Optimization Methods for Control Engineering;  Maude Josée Blondin,Panos M. Pardalos,Javier Sanch Book 2019
描述.This volume presents some recent and principal developments related to computational intelligence and optimization methods in control. Theoretical aspects and practical applications of control engineering are covered by 14 self-contained contributions. Additional gems include the discussion of future directions and research perspectives designed to add to the reader’s understanding of both the challenges faced in control engineering and the insights into the developing of new techniques. With the knowledge obtained, readers are encouraged to determine the appropriate control method for specific applications..
出版日期Book 2019
关键词control optimization techniques; engineering applications; Intelligence computational; Control engineer
版次1
doihttps://doi.org/10.1007/978-3-030-25446-9
isbn_softcover978-3-030-25448-3
isbn_ebook978-3-030-25446-9Series ISSN 1931-6828 Series E-ISSN 1931-6836
issn_series 1931-6828
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Optimal Controller Parameter Tuning from Multi/Many-objective Optimization Algorithms,conventional controllers like PID are designed, so that the desired performance is reached only by adjusting the controller parameters; this adjustment mechanism is called tuning. Even many approaches are proposed for tuning; still, it remains one of the problems of control theory due to the imperfe
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Fuzzy and Neuro-fuzzy Control for Smart Structures,uncertainties. Especially in smart structures, which is the case here, a significant degree of uncertainty is involved due to several imperfections and/or errors of both the controller and the structure itself. For example, in structures with multiple layers, several failures may appear, such as del
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Computational Intelligence in the Desalination Industry,ld of water desalination—on the employment of computational intelligence (CI) systems in this technological field. The main goal of the proposals put forward has been to tackle the high degree of complexity involved in the different processes that can be found in the desalination industry. The wide
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Control of Complex Biological Systems Utilizing the Neural Network Predictor,inties. Because a lot of data are collected in modern systems, a data-driven approach can be employed to design intelligent control algorithms. Specifically, machine learning can be used to take advantage of the available datasets and predict the behavior of the system for improved design and perfor
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A Real-Time Big Data Control-Theoretical Framework for Cyber-Physical-Human Systems,quitous information sensing and processing, intelligent machine-to-machine communication for a seamless coordination, as well as intelligent interactions between humans and machines. This chapter presents a control-theoretical framework to model heterogeneous physical dynamic systems, information an
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Coherency Estimation in Power Systems: A Koopman Operator Approach,rch and understanding of the impact of the non-synchronous generation through back-to-back Full Rated Converters’ (FRCs) on power system’s coherency is a matter of importance. Coherency behavior under the presence of large inclusion of non-synchronous generation requires more research, in order to u
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