Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems Book

Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems


  • Author : Radu-Emil Precup
  • Publisher : Butterworth-Heinemann
  • Release Date : 2019-05-15
  • Genre: Technology & Engineering
  • Pages : 148
  • ISBN 10 : 9780128163580

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Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems Excerpt :

Nature-inspired Optimization Algorithms for Fuzzy Controlled Servo Systems suits the general need of a book that explains the major issues to fuzzy control in servo systems without any solid mathematical prerequisite. In addition, pertinent information on nature-inspired optimization algorithms is offered. The book is intended to rapidly make intelligible notions of fuzzy set theory and fuzzy control to readers with limited experience. The attractive analysis and design methodologies dedicated to fuzzy controllers are accompanied by applications to servo systems and case studies in fuzzy controlled servo systems are organized in a special chapter of this book, and allow simple implementations of low-cost automation solutions. The theoretical approaches presented throughout the book are validated by the illustration of digital simulation results and real-time experimental results as well. This book aims at a large category of audience including graduate students, engineers (designers, practitioners and researchers), and everyone who faces challenging control problems. Gives a merge between classical and modern approaches to fuzzy control Presents in a unified structure from the point of view of a control engineer the essential aspects regarding fuzzy control in servo systems Makes intelligible notions of fuzzy set theory and fuzzy control to readers with limited experience

Data Driven Model Free Controllers Book

Data Driven Model Free Controllers


  • Author : Radu-Emil Precup
  • Publisher : CRC Press
  • Release Date : 2021-12-27
  • Genre: Technology & Engineering
  • Pages : 408
  • ISBN 10 : 9781000519631

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Data Driven Model Free Controllers Excerpt :

This book categorizes the wide area of data-driven model-free controllers, reveals the exact benefits of such controllers, gives the in-depth theory and mathematical proofs behind them, and finally discusses their applications. Each chapter includes a section for presenting the theory and mathematical definitions of one of the above mentioned algorithms. The second section of each chapter is dedicated to the examples and applications of the corresponding control algorithms in practical engineering problems. This book proposes to avoid complex mathematical equations, being generic as it includes several types of data-driven model-free controllers, such as Iterative Feedback Tuning controllers, Model-Free Controllers (intelligent PID controllers), Model-Free Adaptive Controllers, model-free sliding mode controllers, hybrid model‐free and model‐free adaptive‐Virtual Reference Feedback Tuning controllers, hybrid model-free and model-free adaptive fuzzy controllers and cooperative model-free controllers. The book includes the topic of optimal model-free controllers, as well. The optimal tuning of model-free controllers is treated in the chapters that deal with Iterative Feedback Tuning and Virtual Reference Feedback Tuning. Moreover, the extension of some model-free control algorithms to the consensus and formation-tracking problem of multi-agent dynamic systems is provided. This book can be considered as a textbook for undergraduate and postgraduate students, as well as a professional reference for industrial and academic researchers, attracting the readers from both industry and academia.

Nature Inspired Computation and Swarm Intelligence Book

Nature Inspired Computation and Swarm Intelligence


  • Author : Xin-She Yang
  • Publisher : Academic Press
  • Release Date : 2020-04-24
  • Genre: Computers
  • Pages : 442
  • ISBN 10 : 9780128197141

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Nature Inspired Computation and Swarm Intelligence Excerpt :

Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence. Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others Provides a theoretical foundation and analyses of algorithms, including: statistical theory and Markov chain theory on the convergence and stability of algorithms, dynamical system theory, benchmarking of optimization, no-free-lunch theorems, and a generalized mathematical framework Includes a diversity of case studies of real-world applications: feature selection, clustering and classification, tuning of restricted Boltzmann machines, travelling salesman problem, classifi

Nature Inspired Computation in Navigation and Routing Problems Book

Nature Inspired Computation in Navigation and Routing Problems


  • Author : Xin-She Yang
  • Publisher : Springer Nature
  • Release Date : 2020-02-19
  • Genre: Technology & Engineering
  • Pages : 222
  • ISBN 10 : 9789811518423

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Nature Inspired Computation in Navigation and Routing Problems Excerpt :

This book discusses all the major nature-inspired algorithms with a focus on their application in the context of solving navigation and routing problems. It also reviews the approximation methods and recent nature-inspired approaches for practical navigation, and compares these methods with traditional algorithms to validate the approach for the case studies discussed. Further, it examines the design of alternative solutions using nature-inspired techniques, and explores the challenges of navigation and routing problems and nature-inspired metaheuristic approaches.

Handbook On Computational Intelligence  In 2 Volumes  Book

Handbook On Computational Intelligence In 2 Volumes


  • Author : Angelov Plamen Parvanov
  • Publisher : World Scientific
  • Release Date : 2016-03-18
  • Genre: Computers
  • Pages : 964
  • ISBN 10 : 9789814675024

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Handbook On Computational Intelligence In 2 Volumes Excerpt :

With the Internet, the proliferation of Big Data, and autonomous systems, mankind has entered into an era of 'digital obesity'. In this century, computational intelligence, such as thinking machines, have been brought forth to process complex human problems in a wide scope of areas — from social sciences, economics and biology, medicine and social networks, to cyber security.The Handbook of Computational Intelligence (in two volumes) prompts readers to look at these problems from a non-traditional angle. It takes a step by step approach, supported by case studies, to explore the issues that have arisen in the process. The Handbook covers many classic paradigms, as well as recent achievements and future promising developments to solve some of these very complex problems. Volume one explores the subjects of fuzzy logic and systems, artificial neural networks, and learning systems. Volume two delves into evolutionary computation, hybrid systems, as well as the applications of computational intelligence in decision making, the process industry, robotics, and autonomous systems.This work is a 'one-stop-shop' for beginners, as well as an inspirational source for more advanced researchers. It is a useful resource for lecturers and learners alike.

Applied Optimization and Swarm Intelligence Book

Applied Optimization and Swarm Intelligence


  • Author : Eneko Osaba
  • Publisher : Springer Nature
  • Release Date : 2021-05-17
  • Genre: Technology & Engineering
  • Pages : 229
  • ISBN 10 : 9789811606625

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Applied Optimization and Swarm Intelligence Excerpt :

This book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers, lecturers and practitioners interested in swarm intelligence, optimization problems and artificial intelligence.

Computational Science     ICCS 2020 Book

Computational Science ICCS 2020


  • Author : Valeria V. Krzhizhanovskaya
  • Publisher : Springer Nature
  • Release Date : 2020-06-18
  • Genre: Computers
  • Pages : 618
  • ISBN 10 : 9783030504267

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Computational Science ICCS 2020 Excerpt :

The seven-volume set LNCS 12137, 12138, 12139, 12140, 12141, 12142, and 12143 constitutes the proceedings of the 20th International Conference on Computational Science, ICCS 2020, held in Amsterdam, The Netherlands, in June 2020.* The total of 101 papers and 248 workshop papers presented in this book set were carefully reviewed and selected from 719 submissions (230 submissions to the main track and 489 submissions to the workshops). The papers were organized in topical sections named: Part I: ICCS Main Track Part II: ICCS Main Track Part III: Track of Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Track of Agent-Based Simulations, Adaptive Algorithms and Solvers; Track of Applications of Computational Methods in Artificial Intelligence and Machine Learning; Track of Biomedical and Bioinformatics Challenges for Computer Science Part IV: Track of Classifier Learning from Difficult Data; Track of Complex Social Systems through the Lens of Computational Science; Track of Computational Health; Track of Computational Methods for Emerging Problems in (Dis-)Information Analysis Part V: Track of Computational Optimization, Modelling and Simulation; Track of Computational Science in IoT and Smart Systems; Track of Computer Graphics, Image Processing and Artificial Intelligence Part VI: Track of Data Driven Computational Sciences; Track of Machine Learning and Data Assimilation for Dynamical Systems; Track of Meshfree Methods in Computational Sciences; Track of Multiscale Modelling and Simulation; Track of Quantum Computing Workshop Part VII: Track of Simulations of Flow and Transport: Modeling, Algorithms and Computation; Track of Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Track of Software Engineering for Computational Science; Track of Solving Problems with Uncertainties; Track of Teaching Computational Science; Track of UNcErtainty QUantIficatiOn for ComputationAl modeLs *The conference

Intelligent Data Engineering and Automated Learning     IDEAL 2021 Book

Intelligent Data Engineering and Automated Learning IDEAL 2021


  • Author : Hujun Yin
  • Publisher : Springer Nature
  • Release Date : 2021-11-23
  • Genre: Computers
  • Pages : 649
  • ISBN 10 : 9783030916084

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Intelligent Data Engineering and Automated Learning IDEAL 2021 Excerpt :

This book constitutes the refereed proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2021, which took place during November 25-27, 2021. The conference was originally planned to take place in Manchester, UK, but was held virtually due to the COVID-19 pandemic. The 61 full papers included in this book were carefully reviewed and selected from 85 submissions. They deal with emerging and challenging topics in intelligent data analytics and associated machine learning paradigms and systems. Special sessions were held on clustering for interpretable machine learning; machine learning towards smarter multimodal systems; and computational intelligence for computer vision and image processing.

Progress in Advanced Computing and Intelligent Engineering Book

Progress in Advanced Computing and Intelligent Engineering


  • Author : Chhabi Rani Panigrahi
  • Publisher : Springer Nature
  • Release Date : 2021-04-15
  • Genre: Technology & Engineering
  • Pages : 915
  • ISBN 10 : 9789813342996

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Progress in Advanced Computing and Intelligent Engineering Excerpt :

This book focuses on theory, practice and applications in the broad areas of advanced computing techniques and intelligent engineering. This book includes 74 scholarly articles which were accepted for presentation from 294 submissions in the 5th ICACIE during 25–27 June 2020 at Université des Mascareignes (UdM), Mauritius, in collaboration with Rama Devi Women’s University, Bhubaneswar, India, and S‘O’A Deemed to be University, Bhubaneswar, India. This book brings together academicians, industry persons, research scholars and students to share and disseminate their knowledge and scientific research work related to advanced computing and intelligent engineering. It helps to provide a platform to the young researchers to find the practical challenges encountered in these areas of research and the solutions adopted. The book helps to disseminate the knowledge about some innovative and active research directions in the field of advanced computing techniques and intelligent engineering, along with some current issues and applications of related topics.

Intelligent Data Engineering and Automated Learning     IDEAL 2020 Book

Intelligent Data Engineering and Automated Learning IDEAL 2020


  • Author : Cesar Analide
  • Publisher : Springer Nature
  • Release Date : 2020-10-29
  • Genre: Computers
  • Pages : 400
  • ISBN 10 : 9783030623623

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Intelligent Data Engineering and Automated Learning IDEAL 2020 Excerpt :

This two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, held in Guimaraes, Portugal, in November 2020.* The 93 papers presented were carefully reviewed and selected from 134 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2020 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspiredmodels, agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. * The conference was held virtually due to the COVID-19 pandemic.

Nature Inspired Algorithms and Applied Optimization Book

Nature Inspired Algorithms and Applied Optimization


  • Author : Xin-She Yang
  • Publisher : Springer
  • Release Date : 2017-10-08
  • Genre: Technology & Engineering
  • Pages : 330
  • ISBN 10 : 9783319676692

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Nature Inspired Algorithms and Applied Optimization Excerpt :

This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.

Model Free Adaptive Control Book

Model Free Adaptive Control


  • Author : Zhongsheng Hou
  • Publisher : CRC Press
  • Release Date : 2013-09-24
  • Genre: Technology & Engineering
  • Pages : 400
  • ISBN 10 : 9781466594180

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Model Free Adaptive Control Excerpt :

Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the design and analysis of MFAC merely depend on the measured input and output data of the controlled plant, which makes it more applicable for many practical plants. This book covers new concepts, including pseudo partial derivative, pseudo gradient, pseudo Jacobian matrix, and generalized Lipschitz conditions, etc.; dynamic linearization approaches for nonlinear systems, such as compact-form dynamic linearization, partial-form dynamic linearization, and full-form dynamic linearization; a series of control system design methods, including MFAC prototype, model-free adaptive predictive control, model-free adaptive iterative learning control, and the corresponding stability analysis and typical applications in practice. In addition, some other important issues related to MFAC are also discussed. They are the MFAC for complex connected systems, the modularized controller designs between MFAC and other control methods, the robustness of MFAC, and the symmetric similarity for adaptive control system design. The book is written for researchers who are interested in control theory and control engineering, senior undergraduates and graduated students in engineering and applied sciences, as well as professional engineers in process control.

Fuzzy Optimization Book

Fuzzy Optimization


  • Author : Miguel Delgado
  • Publisher : Springer Verlag
  • Release Date : 1994
  • Genre: Fuzzy algorithms
  • Pages : 478
  • ISBN 10 : UOM:39015032615265

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Fuzzy Optimization Excerpt :

Handbook of AI based Metaheuristics Book

Handbook of AI based Metaheuristics


  • Author : Anand J. Kulkarni
  • Publisher : CRC Press
  • Release Date : 2021-09-02
  • Genre: Computers
  • Pages : 418
  • ISBN 10 : 9781000434255

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Handbook of AI based Metaheuristics Excerpt :

At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms. The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms. This will be a valuable reference for researchers in industry and academia, as well as for all Master’s and PhD students working in the metaheuristics and applications domains.