SIAM Journal on Control and Optimization

SIAM Journal on Control and Optimization PDF Author: Society for Industrial and Applied Mathematics
Publisher:
ISBN:
Category : Control theory
Languages : en
Pages : 1200

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Book Description

SIAM Journal on Control and Optimization

SIAM Journal on Control and Optimization PDF Author: Society for Industrial and Applied Mathematics
Publisher:
ISBN:
Category : Control theory
Languages : en
Pages : 1200

Get Book Here

Book Description


Global Optimization

Global Optimization PDF Author: Marco Locatelli
Publisher: SIAM
ISBN: 1611972671
Category : Mathematics
Languages : en
Pages : 439

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Book Description
This volume contains a thorough overview of the rapidly growing field of global optimization, with chapters on key topics such as complexity, heuristic methods, derivation of lower bounds for minimization problems, and branch-and-bound methods and convergence. The final chapter offers both benchmark test problems and applications of global optimization, such as finding the conformation of a molecule or planning an optimal trajectory for interplanetary space travel. An appendix provides fundamental information on convex and concave functions. Intended for Ph.D. students, researchers, and practitioners looking for advanced solution methods to difficult optimization problems. It can be used as a supplementary text in an advanced graduate-level seminar.

Advanced and Optimization Based Sliding Mode Control: Theory and Applications

Advanced and Optimization Based Sliding Mode Control: Theory and Applications PDF Author: Antonella Ferrara
Publisher: SIAM
ISBN: 1611975840
Category : Mathematics
Languages : en
Pages : 302

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Book Description
A compendium of the authorsÂ’ 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.

Formulation and Numerical Solution of Quantum Control Problems

Formulation and Numerical Solution of Quantum Control Problems PDF Author: Alfio Borzi
Publisher: SIAM
ISBN: 1611974844
Category : Technology & Engineering
Languages : en
Pages : 396

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Book Description
This book provides an introduction to representative nonrelativistic quantum control problems and their theoretical analysis and solution via modern computational techniques. The quantum theory framework is based on the Schr?dinger picture, and the optimization theory, which focuses on functional spaces, is based on the Lagrange formalism. The computational techniques represent recent developments that have resulted from combining modern numerical techniques for quantum evolutionary equations with sophisticated optimization schemes. Both finite and infinite-dimensional models are discussed, including the three-level Lambda system arising in quantum optics, multispin systems in NMR, a charged particle in a well potential, Bose?Einstein condensates, multiparticle spin systems, and multiparticle models in the time-dependent density functional framework. This self-contained book covers the formulation, analysis, and numerical solution of quantum control problems and bridges scientific computing, optimal control and exact controllability, optimization with differential models, and the sciences and engineering that require quantum control methods.

Control and Optimization with Differential-Algebraic Constraints

Control and Optimization with Differential-Algebraic Constraints PDF Author: Lorenz T. Biegler
Publisher: SIAM
ISBN: 1611972248
Category : Mathematics
Languages : en
Pages : 351

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Book Description
A cutting-edge guide to modelling complex systems with differential-algebraic equations, suitable for applied mathematicians, engineers and computational scientists.

Perspectives in Flow Control and Optimization

Perspectives in Flow Control and Optimization PDF Author: Max D. Gunzburger
Publisher: SIAM
ISBN: 089871527X
Category : Science
Languages : en
Pages : 273

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Book Description
Introduces several approaches for solving flow control and optimization problems through the use of modern methods.

Practical Methods for Optimal Control and Estimation Using Nonlinear Programming

Practical Methods for Optimal Control and Estimation Using Nonlinear Programming PDF Author: John T. Betts
Publisher: SIAM
ISBN: 0898716888
Category : Mathematics
Languages : en
Pages : 442

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Book Description
A focused presentation of how sparse optimization methods can be used to solve optimal control and estimation problems.

Arc Routing

Arc Routing PDF Author: Angel Corberan
Publisher: SIAM
ISBN: 1611973678
Category : Mathematics
Languages : en
Pages : 404

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Book Description
This book provides a thorough and up-to-date discussion of arc routing by world-renowned researchers. Organized by problem type, the book offers a rigorous treatment of complexity issues, models, algorithms, and applications. Arc Routing: Problems, Methods, and Applications opens with a historical perspective of the field and is followed by three sections that cover complexity and the Chinese Postman and the Rural Postman problems; the Capacitated Arc Routing Problem and routing problems with min-max and profit maximization objectives; and important applications, including meter reading, snow removal, and waste collection.

Stochastic Control and Mathematical Modeling

Stochastic Control and Mathematical Modeling PDF Author: Hiroaki Morimoto
Publisher: Cambridge University Press
ISBN: 9780521195034
Category : Mathematics
Languages : en
Pages : 340

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Book Description
This is a concise and elementary introduction to stochastic control and mathematical modeling. This book is designed for researchers in stochastic control theory studying its application in mathematical economics and those in economics who are interested in mathematical theory in control. It is also a good guide for graduate students studying applied mathematics, mathematical economics, and non-linear PDE theory. Contents include the basics of analysis and probability, the theory of stochastic differential equations, variational problems, problems in optimal consumption and in optimal stopping, optimal pollution control, and solving the HJB equation with boundary conditions. Major mathematical requisitions are contained in the preliminary chapters or in the appendix so that readers can proceed without referring to other materials.

First-order and Stochastic Optimization Methods for Machine Learning

First-order and Stochastic Optimization Methods for Machine Learning PDF Author: Guanghui Lan
Publisher: Springer Nature
ISBN: 3030395685
Category : Mathematics
Languages : en
Pages : 591

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Book Description
This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning.