Linear logic, first introduced by Jean-Yves Girard in 1987 as a resource-conscious logic, is a refinement of classical logic that has now matured into a rich area of active research that includes linear logic semantics, proof theory, complexity, and applications to the theory of concurrent and distr
Computational Aspects of Linear Control
β Scribed by Claude Brezinski (auth.), Claude Brezinski (eds.)
- Publisher
- Springer US
- Year
- 2002
- Tongue
- English
- Leaves
- 296
- Series
- Numerical Methods and Algorithms 1
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Many devices (we say dynamical systems or simply systems) behave like black boxes: they receive an input, this input is transformed following some laws (usually a differential equation) and an output is observed. The problem is to regulate the input in order to control the output, that is for obtaining a desired output. Such a mechanism, where the input is modified according to the output measured, is called feedback. The study and design of such automatic processes is called control theory. As we will see, the term system embraces any device and control theory has a wide variety of applications in the real world. Control theory is an interdisciΒ plinary domain at the junction of differential and difference equations, system theory and statistics. Moreover, the solution of a control problem involves many topics of numerical analysis and leads to many interesting computational problems: linear algebra (QR, SVD, projections, Schur complement, structured matrices, localization of eigenvalues, computation of the rank, Jordan normal form, Sylvester and other equations, systems of linear equations, regularizaΒ tion, etc), root localization for polynomials, inversion of the Laplace transform, computation of the matrix exponential, approximation theory (orthogonal polyΒ nomials, Pad6 approximation, continued fractions and linear fractional transforΒ mations), optimization, least squares, dynamic programming, etc. So, control theory is also a. good excuse for presenting various (sometimes unrelated) issues of numerical analysis and the procedures for their solution. This book is not a book on control.
β¦ Table of Contents
Front Matter....Pages i-ix
Introduction....Pages 1-2
Control of Linear Systems....Pages 3-72
Formal Orthogonal Polynomials....Pages 73-85
PadΓ© Approximations....Pages 87-134
Transform Inversion....Pages 135-143
Linear Algebra Issues....Pages 145-159
Lanczos Tridiagonalization Process....Pages 161-169
Systems of Linear Algebraic Equations....Pages 171-223
Regularization of Ill-Conditioned Systems....Pages 225-247
Sylvester and Riccati Equations....Pages 249-253
Topics on Nonlinear Differential Equations....Pages 255-275
Appendix: The Mathematics of Model Reduction....Pages 277-287
Back Matter....Pages 289-295
β¦ Subjects
Computational Mathematics and Numerical Analysis; Calculus of Variations and Optimal Control; Optimization; Approximations and Expansions
π SIMILAR VOLUMES
In recent years the dramatic reduction in the cost of computing equipment has encouraged industry to automate its manufacturing processes as a credible means of reducing the unit costs of products. However, the application of computers to the control of processes generates new risks. These risks ari
We give a self-contained exposition of Mayr & Meyer's example of a polynomial ideal exhibiting double exponential degrees for the ideal membership problem, and generalise this example to exhibit minimal syzygies of double exponential degree. This demonstrates the existence of subschemes of projectiv
<p>Three subjects of major interest are contained in this textbook: Linear elasticity, mechanics of structures in linear isotropic elasticity, and nonlinear mechanics including computational algorithms. Engineering and mathematics are in a reasonable balance: After the simplest possible, intuitive a