Random Processes in Nonlinear Control Systems by A A Pervozvanskii


Book Description

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




Nonlinear System Techniques and Applications


Book Description

New practical techniques for nonlinear system research and evaluation Nonlinear Systems Techniques and Applications provides the most practical techniques currently available for analyzing and identifying nonlinear systems from random data measured at the input and output points of the nonlinear systems. These new techniques require only one-dimensional spectral functions that are much simpler to compute and apply than previous nonlinear procedures. The new results show when and how to replace a wide class of single-input/single-output nonlinear models with simpler equivalent multiple-input/single-output linear models. While other techniques are usually restricted to Gaussian data, the new techniques developed here apply to data with arbitrary probability, correlation, and spectral properties. Numerous examples used in the book are based on the analysis of real physical data passing through real nonlinear systems in the fields of oceanography, automotive engineering, and biomedical research. For practicing engineers and scientists involved in aerospace, automotive, biomedical, electrical, mechanical, oceanographic, and other activities concerned with nonlinear system analysis, Nonlinear Systems Techniques and Applications is the essential reference work in the field.










Nonlinear Control Systems 2004


Book Description







Stability of Nonlinear Control Systems


Book Description

Stability of Nonlinear Control Systems




Random Processes for Engineers


Book Description

This engaging introduction to random processes provides students with the critical tools needed to design and evaluate engineering systems that must operate reliably in uncertain environments. A brief review of probability theory and real analysis of deterministic functions sets the stage for understanding random processes, whilst the underlying measure theoretic notions are explained in an intuitive, straightforward style. Students will learn to manage the complexity of randomness through the use of simple classes of random processes, statistical means and correlations, asymptotic analysis, sampling, and effective algorithms. Key topics covered include: • Calculus of random processes in linear systems • Kalman and Wiener filtering • Hidden Markov models for statistical inference • The estimation maximization (EM) algorithm • An introduction to martingales and concentration inequalities. Understanding of the key concepts is reinforced through over 100 worked examples and 300 thoroughly tested homework problems (half of which are solved in detail at the end of the book).




Adaptive Systems in Control and Signal Processing 1989


Book Description

The Symposium covered three major areas: adaptive control, identification and signal processing. In all three, new developments were discussed covering both theoretical and applications research. Within the subject area of adaptive control the discussion centred around the challenges of robust control design to unmodelled dynamics, robust parameter estimation and enhanced performance from the estimator, while the papers on identification took the theme of it being a bridge between adaptive control and signal processing. The final area looked at two aspects of signal processing: recursive estimation and adaptive filters.




Stochastic Systems: Theory And Applications


Book Description

This book presents the general theory and basic methods of linear and nonlinear stochastic systems (StS) i.e. dynamical systems described by stochastic finite- and infinite-dimensional differential, integral, integrodifferential, difference etc equations. The general StS theory is based on the equations for characteristic functions and functionals. The book outlines StS structural theory, including direct numerical methods, methods of normalization, equivalent linearization and parametrization of one- and multi-dimensional distributions, based on moments, quasimoments, semi-invariants and orthogonal expansions. Special attention is paid to methods based on canonical expansions and integral canonical representations. About 500 exercises and problems are provided. The authors also consider applications in mathematics and mechanics, physics and biology, control and information processing, operations research and finance.