Control perspectives on numerical algorithms and matrix problems by Amit Bhaya

Cover of: Control perspectives on numerical algorithms and matrix problems | Amit Bhaya

Published by Society for Industrial and Applied Mathematics in Philadelphia .

Written in English

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Subjects:

  • Control theory.,
  • Numerical analysis.,
  • Algorithms.,
  • Mathematical optimization.,
  • Matrices.

Edition Notes

Includes bibliographical references and index.

Book details

StatementAmit Bhaya, Eugenius Kaszkurewicz.
SeriesAdvances in design and control
ContributionsKaszkurewicz, Eugenius.
Classifications
LC ClassificationsQA402.3 .B49 2006
The Physical Object
Paginationp. cm.
ID Numbers
Open LibraryOL3431731M
ISBN 100898716020
LC Control Number2005057551

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Control Perspectives on Numerical Algorithms and Matrix Problems organizes the analysis and design of iterative numerical methods from a control perspective. The authors discuss a variety of applications, including iterative methods for linear and nonlinear systems of equations, neural networks for linear and quadratic programming problems, support vector machines, integration and shooting methods for ordinary differential equations, matrix preconditioning, matrix stability.

Control Perspectives on Numerical Algorithms and Matrix Problems > /ch3 Control Perspectives on Numerical Algorithms and Matrix Problems. Control Perspectives on Numerical Algorithms and Matrix Problems > /ch2 Control Perspectives on Numerical Algorithms and Matrix Problems. Control perspectives on numerical algorithms and matrix problems / Amit Bhaya, Eugenius Kaszkurewicz.

— (Advances in design and control) Includes bibliographical references and index. ISBN (pbk.) 1. Control theory. Numerical analysis. Algorithms. Mathematical optimization. Matrices. Kaszkurewicz, Eugenius. Title. III. Series. Control Perspectives on Numerical Algorithms and Matrix Problems.

Control perspectives on numerical algorithms and matrix problems. Bhaya, Amit and Eugenius Kaszkurewicz. SIAM pages $ Paperback Advances in design and control. Control Perspectives on Numerical Algorithms and Matrix Problems This book organizes the analysis and design of iterative numerical methods from a Control perspective.

The following books are reviewed in this issue: Wind Turbine Control Systems (Bianchi, F.D. et al.; ); Control Perspectives on Numerical Algorithms and Matrix.

The book is a control perspective on problems mainly in numerical analysis, optimization, and matrix theory in which systems and control ideas are shown to play an important role. Summary: "Control Perspectives on Numerical Algorithms and Matrix Problems is intended for researchers in applied mathematics and control as well as senior undergraduate and graduate students in both of these fields.

Control perspectives on numerical algorithms and matrix problems. [Amit Bhaya; Eugenius Kaszkurewicz; Society for Industrial and Applied Mathematics.] -- Control Perspectives on Numerical Algorithms and Matrix Problems organizes the analysis and design of iterative numerical methods from a control perspective.

numerical algorithms in MATLAB to approximate the solution to an optimal control problem. Once the methods are developed, the concept of convergence for each method will be discussed as well as any flaws or problems with each specific method.

Abstract. We present an overview of the use of semi-infinite optimization algorithms in linear, multivariable control system design. We deal with problem formulation, basics of algorithms, numerical aspects and software : E.

Polak. Optimal control and numerical software: an overview 7 The Pontryagin Maximum Prin ciple (Theorem ) r emains valid for problems with bounds on the control. Numerical Methods for Linear Control Systems Design and Analysis is an interdisciplinary textbook aimed at systematic descriptions and implementations of numerically-viable algorithms based on well-established, efficient and stable modern numerical linear techniques for mathematical problems arising in the design and analysis of linear control.

algorithm is applied to a well-conditioned problem, the solution should be accurate. The condition numbers of only a few control problems have been identi ed.

Some of them will be mentioned in this paper. Another important aspect of a numerical algorithm is its e ciency. A matrix algorithm. Accuracy and stability of numerical algorithms I Nicholas J.

Highamnd ed. Includes bibliographical references. ISBN I. Numerical analysis-Data processing. Computer algorithms. Title. QAH53 5 I ''5 l-dc21 •. Book Description. Numerical Analysis with Algorithms and Programming is the first comprehensive textbook to provide detailed coverage of numerical methods, their algorithms, and corresponding computer programs.

It presents many techniques for the efficient numerical solution of problems in science and engineering. stabilization problem is a special case of the eigenvalue assignment problem. Matrix-equation problems such as the Lyapunov, Sylvester, and Riccati, arising in stability and robust-stability analyses, H-infinity control, estimation, etc., are clearly matrix-equation problems in linear Size: 1MB.

Numerical Methods for Linear Control Systems Design and Analysis is an interdisciplinary textbook aimed at systematic descriptions and implementations of numerically-viable algorithms based on well-established, efficient and stable modern numerical linear techniques for mathematical problems arising in the design and analysis of linear control systems both for the first- and second-order models.

The Numerical Methods for Linear Equations and Matrices • • • We saw in the previous chapter that linear equations play an important role in transformation theory and that these equations could be simply expressed in terms of matrices. However, this is only a small segment of the importance of linear equations and matrix theory to the File Size: KB.

He coauthored the books Matrix Diagonal Stability in Systems and Computation (Cambridge, MA: Birkhäuser, ) and Control Perspectives on Numerical Algorithms and Matrix Problems (Philadelphia, PA: SIAM, ) and works in the areas of systems and control theory, parallel computation, neural networks, matrix stability theory, and mathematical Cited by: 4.

Numerical algorithms in control CONTROL Zlatko Drmaˇc Introduction Problems Machine numbers Examples Consequences Goals Scaling: examples Numerical rank revealing Eigenvalues and singular values The stiffness matrix of a mass spring system with 3 masses ⊠!.

The feedbackstabilization problem is a special case of the eigenvalue assignment problem. Matrix-equation problems such as the Lyapunov, Sylvester, and Riccati, arising in stability and robust-stability analyses, H-infinity control, estimation, etc., are clearly matrix-equation problems in linear by: Search the world's most comprehensive index of full-text books.

My library. Numerical algorithms of linear algebra The methods of the linear algebra count among the most important areas used at the solution of technical problems: the understanding of numerical methods of linear algebra is important for the understanding of full problems of numerical methods.

In the numerical algebra we encounter two basic variants of File Size: KB. Many problems in the sciences and engineering can be rephrased as optimization problems on matrix search spaces endowed with a so-called manifold structure. This book shows how to exploit the special structure of such problems to develop efficient numerical algorithms.

It places careful emphasis on both the numerical formulation of the. Another key requirement is the development of dedicated interior-point methods for convex (but potentially ill-conditioned or large-scale) linear matrix inequality (LMI) design problems (exploiting the structure, reducing the number of variables), and algorithms for control design via non-convex bilinear matrix inequality (BMI) by: Numerical methods vary in their behavior, and the many different types of differ-ential equation problems affect the performanceof numerical methods in a variety of ways.

An excellent book for “real world” examples of solving differential equations is that of Shampine, Gladwell, and Thompson [74].File Size: 1MB. The book is a comprehensive and theoretically sound treatment of parallel and distributed numerical methods.

It focuses on algorithms that are naturally suited for massive parallelization, and it explores the fundamental convergence, rate of convergence, communication, and synchronization issues associated with such algorithms.

Journal of Applied Mathematics / / Article. Article Sections. On this page. Bhaya and E. Kaszkurewicz, Control Perspectives on Numerical Algorithms and Matrix Problems, Advances in Design and Control, B SIAM, Philadelphia, Pa, USA, Cited by: 4.

Numerical Analysis with Algorithms and Programming is the first comprehensive textbook to provide detailed coverage of numerical methods, their algorithms, and corresponding computer programs.

It presents many techniques for the efficient numerical solution of problems in science and by: 6. Abstract. In this paper, we describe block matrix algorithms for the iterative solution of large scale linear-quadratic optimal control problems arising from the control of parabolic partial differential equations over a finite control horizon.

After spatial discretization, by finite element or finite difference methods, the original problem reduces to an optimal control problem for n coupled Cited by: 6.

Description: This book organizes the analysis and design of iterative numerical methods from a control perspective.

A variety of applications are discussed, including iterative methods for linear and nonlinear systems of equations, neural networks for linear and quadratic programming problems and integration and shooting methods for ordinary differential equations.

Although numerical algorithms for linear matrix equations in control theory were published sincethis is still a hot research topic. The challenge for solving larger Author: Vasile Sima. Numerical Methods: Algorithms and Applications 1st Edition It also presents a summary of the key components of a computer program for solving problems involving numerical techniques such as those given in the text.

The trapezoid rule for numerical integration is used to illustrate the relationship between a numerical algorithm and a Cited by: An encyclopedic discussion of the stability of algorithms, mostly algorithms in numerical linear algebra, is the focus of this book. Eigenvalue algorithms are excluded, as they have a framework of their own.

This is the second edition of the book; it will prove valuable to those who do not have its first edition, and also to those who do. Library of Congress Control Number: ISBN: Numerical Algorithms 1 Finding roots 2 Analyzing Heron’s algorithm 5 the importance of the field of numerical analysis that such books and others [] are so popular.

However, such books File Size: 2MB. Much of the book can be understood with only a basic grounding in numerical analysis and linear algebra. About the Author Nicholas J. Higham is a Professor of Applied Mathematics at the University of Manchester, England.

Numerical Methods: Design, Analysis, and Computer Implementation of Algorithms - Ebook written by Anne Greenbaum, Tim P. Chartier. Read this book using Google Play Books app on your PC, android, iOS devices. Download for offline reading, highlight, bookmark or take notes while you read Numerical Methods: Design, Analysis, and Computer Implementation of Algorithms.3/5(1).

The state-of-the-art algorithms given as examples are competitive with the best existing algorithms for a selection of eigenspace problems in numerical linear algebra. Optimization Algorithms on Matrix Manifolds offers techniques with broad applications in linear algebra, signal processing, data mining, computer vision, and statistical analysis.Top Ten Algorithms in Science (Dongarra and Sullivan, ) 1 Metropolis Algorithm (Monte Carlo method) 2 Simplex Method for Linear Programming 3 Krylov Subspace Iteration Methods 4 The Decompositional Approach to Matrix Computations 5 The Fortran Optimizing Compiler 6 QR Algorithm for Computing Eigenvalues 7 Quicksort Algorithm for Sorting 8 Fast Fourier TransformFile Size: KB.This paper applies a recently proposed control-inspired approach to the design of iterative steepest descent and conjugate gradient algorithms for perceptron training in batch mode, by regarding certain parameters of the training/algorithm as controls and then using a control Liapunov technique to choose appropriate values of these parameters.

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