Optimization and Its Applications in Control and Data Sciences

Optimization and Its Applications in Control and Data Sciences

Author: Boris Goldengorin

Publisher: Springer

Published: 2016-09-29

Total Pages: 516

ISBN-13: 3319420569

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This book focuses on recent research in modern optimization and its implications in control and data analysis. This book is a collection of papers from the conference “Optimization and Its Applications in Control and Data Science” dedicated to Professor Boris T. Polyak, which was held in Moscow, Russia on May 13-15, 2015. This book reflects developments in theory and applications rooted by Professor Polyak’s fundamental contributions to constrained and unconstrained optimization, differentiable and nonsmooth functions, control theory and approximation. Each paper focuses on techniques for solving complex optimization problems in different application areas and recent developments in optimization theory and methods. Open problems in optimization, game theory and control theory are included in this collection which will interest engineers and researchers working with efficient algorithms and software for solving optimization problems in market and data analysis. Theoreticians in operations research, applied mathematics, algorithm design, artificial intelligence, machine learning, and software engineering will find this book useful and graduate students will find the state-of-the-art research valuable.


Optimization and Control with Applications

Optimization and Control with Applications

Author: Liqun Qi

Publisher: Springer Science & Business Media

Published: 2006-03-30

Total Pages: 587

ISBN-13: 0387242554

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A collection of 28 refereed papers grouped according to four broad topics: duality and optimality conditions, optimization algorithms, optimal control, and variational inequality and equilibrium problems. Suitable for researchers, practitioners and postgrads.


Data-Driven Science and Engineering

Data-Driven Science and Engineering

Author: Steven L. Brunton

Publisher: Cambridge University Press

Published: 2022-05-05

Total Pages: 615

ISBN-13: 1009098489

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A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.


Optimization for Data Analysis

Optimization for Data Analysis

Author: Stephen J. Wright

Publisher: Cambridge University Press

Published: 2022-04-21

Total Pages: 239

ISBN-13: 1316518981

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A concise text that presents and analyzes the fundamental techniques and methods in optimization that are useful in data science.


Approximation and Optimization

Approximation and Optimization

Author: Ioannis C. Demetriou

Publisher: Springer

Published: 2019-05-10

Total Pages: 244

ISBN-13: 3030127672

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This book focuses on the development of approximation-related algorithms and their relevant applications. Individual contributions are written by leading experts and reflect emerging directions and connections in data approximation and optimization. Chapters discuss state of the art topics with highly relevant applications throughout science, engineering, technology and social sciences. Academics, researchers, data science practitioners, business analysts, social sciences investigators and graduate students will find the number of illustrations, applications, and examples provided useful. This volume is based on the conference Approximation and Optimization: Algorithms, Complexity, and Applications, which was held in the National and Kapodistrian University of Athens, Greece, June 29–30, 2017. The mix of survey and research content includes topics in approximations to discrete noisy data; binary sequences; design of networks and energy systems; fuzzy control; large scale optimization; noisy data; data-dependent approximation; networked control systems; machine learning ; optimal design; no free lunch theorem; non-linearly constrained optimization; spectroscopy.


Advanced and Optimization Based Sliding Mode Control: Theory and Applications

Advanced and Optimization Based Sliding Mode Control: Theory and Applications

Author: Antonella Ferrara

Publisher: SIAM

Published: 2019-07-01

Total Pages: 302

ISBN-13: 1611975840

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A compendium of the authors’ recently published results, this book discusses sliding mode control of uncertain nonlinear systems, with a particular emphasis on advanced and optimization based algorithms. The authors survey classical sliding mode control theory and introduce four new methods of advanced sliding mode control. They analyze classical theory and advanced algorithms, with numerical results complementing the theoretical treatment. Case studies examine applications of the algorithms to complex robotics and power grid problems. Advanced and Optimization Based Sliding Mode Control: Theory and Applications is the first book to systematize the theory of optimization based higher order sliding mode control and illustrate advanced algorithms and their applications to real problems. It presents systematic treatment of event-triggered and model based event-triggered sliding mode control schemes, including schemes in combination with model predictive control, and presents adaptive algorithms as well as algorithms capable of dealing with state and input constraints. Additionally, the book includes simulations and experimental results obtained by applying the presented control strategies to real complex systems. This book is suitable for students and researchers interested in control theory. It will also be attractive to practitioners interested in implementing the illustrated strategies. It is accessible to anyone with a basic knowledge of control engineering, process physics, and applied mathematics.


Introduction to Applied Optimization

Introduction to Applied Optimization

Author: Urmila Diwekar

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 342

ISBN-13: 1475737459

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This text presents a multi-disciplined view of optimization, providing students and researchers with a thorough examination of algorithms, methods, and tools from diverse areas of optimization without introducing excessive theoretical detail. This second edition includes additional topics, including global optimization and a real-world case study using important concepts from each chapter. Introduction to Applied Optimization is intended for advanced undergraduate and graduate students and will benefit scientists from diverse areas, including engineers.


Optimization Models

Optimization Models

Author: Giuseppe C. Calafiore

Publisher: Cambridge University Press

Published: 2014-10-31

Total Pages: 651

ISBN-13: 1107050871

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This accessible textbook demonstrates how to recognize, simplify, model and solve optimization problems - and apply these principles to new projects.


Optimization and Control of Bilinear Systems

Optimization and Control of Bilinear Systems

Author: Panos M. Pardalos

Publisher: Springer Science & Business Media

Published: 2010-03-14

Total Pages: 388

ISBN-13: 0387736697

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Covers developments in bilinear systems theory Focuses on the control of open physical processes functioning in a non-equilibrium mode Emphasis is on three primary disciplines: modern differential geometry, control of dynamical systems, and optimization theory Includes applications to the fields of quantum and molecular computing, control of physical processes, biophysics, superconducting magnetism, and physical information science


Numerical Methods and Optimization

Numerical Methods and Optimization

Author: Jean-Pierre Corriou

Publisher: Springer Nature

Published: 2022-01-04

Total Pages: 730

ISBN-13: 3030893669

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This text, covering a very large span of numerical methods and optimization, is primarily aimed at advanced undergraduate and graduate students. A background in calculus and linear algebra are the only mathematical requirements. The abundance of advanced methods and practical applications will be attractive to scientists and researchers working in different branches of engineering. The reader is progressively introduced to general numerical methods and optimization algorithms in each chapter. Examples accompany the various methods and guide the students to a better understanding of the applications. The user is often provided with the opportunity to verify their results with complex programming code. Each chapter ends with graduated exercises which furnish the student with new cases to study as well as ideas for exam/homework problems for the instructor. A set of programs made in MatlabTM is available on the author’s personal website and presents both numerical and optimization methods.