Almost all process systems are nonlinear in nature. Nonlinear control is traditionally an area of interest in process systems engineering which is of great practical importance. These facts notwithstanding, many process engineers have difficulty with the paradigms and results of modern nonlinear con
Random Processes in Nonlinear Control Systems
✍ Scribed by A.A. Pervozvanskii (Eds.)
- Publisher
- Academic Press
- Year
- 1965
- Tongue
- English
- Leaves
- 354
- Series
- Mathematics in Science and Engineering 15
- Category
- Library
No coin nor oath required. For personal study only.
✦ Synopsis
In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; andmethods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory.As a result, the book represents a blend of new methods in general computational analysis,and specific, but also generic, techniques for study of systems theory ant its particularbranches, such as optimal filtering and information compression. - Best operator approximation,- Non-Lagrange interpolation,- Generic Karhunen-Loeve transform- Generalised low-rank matrix approximation- Optimal data compression- Optimal nonlinear filtering
✦ Table of Contents
Content:
Edited by
Page iii
Copyright page
Page iv
Editor's Foreword
Page v
Richard Bellman
Preface
Pages vii-xi
A.A. Pervozvanskii
Introduction
Pages 1-15
Chapter 1 Nonlinear Transformations Without Feedback
Pages 16-87
Chapter 2 Nonlinear Transformations With Feedback Stationary States
Pages 88-145
Chapter 3 Nonlinear Transformations With Feedback Nonstationary States
Pages 146-210
Chapter 4 Extremal Systems
Pages 211-291
Appendix I Functions my(mx, σx), h1(mx, σx), a2(mx, σx), and a3(mx, σx) for Several Typical Nonlinearities
Pages 292-303
Appendix II Representation of a Lagless Nonlinear Transformation in the Form of an Integral Transformation in a Complex Region. The Theorem of R. Price
Pages 304-308
Appendix III Computation of the Integrals In
Page 309
Appendix IV The Coefficients of Statistical Linearization h1(a, σ) and h2(a, σ) for Typical Nonlinearities
Pages 310-317
Appendix V Elementary Statements on the Theory of Markov Processes
Pages 318-328
Related Literature
Pages 329-331
Bibliography
Pages 332-337
Author Index
Pages 339-340
Subject Index
Page 341
📜 SIMILAR VOLUMES
<p><P>Almost all process systems are nonlinear in nature. Nonlinear control is traditionally an area of interest in process systems engineering which is of great practical importance. These facts notwithstanding, many process engineers have difficulty with the paradigms and results of modern nonline