Nonlinear Estimation in Continuous Time Systems
Nonlinear Estimation in Continuous Time Systems

Author: Paul Arthur Frost

Publisher:

Published: 1968

Total Pages: 184

ISBN-13:

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The nonlinear estimation of continuous time nonstationary signals contained in additive Gaussian white noise is considered in this study. The theory presented is more general than former studies and most previously known results are easily obtained as special cases, including the Kalman-Bucy theory and the Stratonovich-Kushner equations. A new approach to continuous time estimation is developed which is in the same spirit as the Bode-Shannon approach to Wiener filter theory. It is shown, for the first time, that nonstationary continuous time processes containing additive Gaussian white noise can be transformed causally into an 'innovation process, ' or equivalently, a Gaussian white noise. This innovation process contains all of the information of the original process and consequently nonlinear estimators can be designed to operate on the innovations rather than on the original observations. This approach leads to a number of new descriptions of nonlinear estimators; the two most useful are a stochastic integral representation and an infinite orthogonal series representation. One of the important properties of the series description is that the series can be terminated after any specified number of terms, yielding a suboptimal nonlinear estimator and the remainder of the series can be summed and expressed in closed form. The innovation process approach is developed for nonstationary linear estimation as well as nonlinear estimation and a close correspondence between these two theories is demonstrated. Some new contributions to linear estimation theory are presented, including a proof of the causal invertibility of Kalman filters and a simple derivation of linear smoothing algorithms. (Author).

Identification of Continuous-Time Systems
Identification of Continuous-Time Systems

Author: N.K. Sinha

Publisher: Springer Science & Business Media

Published: 1991-07-31

Total Pages: 670

ISBN-13: 9780792313366

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In view of the importance of system identification, the International Federation of Automatic Control (IFAC) and the International Federation of Operational Research Societies (IFORS) hold symposia on this topic every three years. Interest in continuous time approaches to system identification has been growing in recent years. This is evident from the fact that the of invited sessions on continuous time systems has increased from one in the 8th number Symposium that was held in Beijing in 1988 to three in the 9th Symposium in Budapest in 1991. It was during the 8th Symposium in August 1988 that the idea of bringing together important results on the topic of Identification of continuous time systems was conceived. Several distinguished colleagues, who were with us in Beijing at that time, encouraged us by promising on the spot to contribute to a comprehensive volume of collective work. Subsequently, we contacted colleagues all over the world, known for their work in this area, with a formal request to contribute to the proposed volume. The response was prompt and overwhelmingly encouraging. We sincerely thank all the authors for their valuable contributions covering various aspects of identification of continuous time systems.

Nonlinear Estimation
Nonlinear Estimation

Author: Shovan Bhaumik

Publisher: CRC Press

Published: 2019-07-24

Total Pages: 255

ISBN-13: 1351012339

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Nonlinear Estimation: Methods and Applications with Deterministic Sample Points focusses on a comprehensive treatment of deterministic sample point filters (also called Gaussian filters) and their variants for nonlinear estimation problems, for which no closed-form solution is available in general. Gaussian filters are becoming popular with the designers due to their ease of implementation and real time execution even on inexpensive or legacy hardware. The main purpose of the book is to educate the reader about a variety of available nonlinear estimation methods so that the reader can choose the right method for a real life problem, adapt or modify it where necessary and implement it. The book can also serve as a core graduate text for a course on state estimation. The book starts from the basic conceptual solution of a nonlinear estimation problem and provides an in depth coverage of (i) various Gaussian filters such as the unscented Kalman filter, cubature and quadrature based filters, Gauss-Hermite filter and their variants and (ii) Gaussian sum filter, in both discrete and continuous-discrete domain. Further, a brief description of filters for randomly delayed measurement and two case-studies are also included. Features: The book covers all the important Gaussian filters, including filters with randomly delayed measurements. Numerical simulation examples with detailed matlab code are provided for most algorithms so that beginners can verify their understanding. Two real world case studies are included: (i) underwater passive target tracking, (ii) ballistic target tracking. The style of writing is suitable for engineers and scientists. The material of the book is presented with the emphasis on key ideas, underlying assumptions, algorithms, and properties. The book combines rigorous mathematical treatment with matlab code, algorithm listings, flow charts and detailed case studies to deepen understanding.

Identification of Continuous-Time Systems
Identification of Continuous-Time Systems

Author: N.K. Sinha

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 641

ISBN-13: 9401135584

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In view of the importance of system identification, the International Federation of Automatic Control (IFAC) and the International Federation of Operational Research Societies (IFORS) hold symposia on this topic every three years. Interest in continuous time approaches to system identification has been growing in recent years. This is evident from the fact that the of invited sessions on continuous time systems has increased from one in the 8th number Symposium that was held in Beijing in 1988 to three in the 9th Symposium in Budapest in 1991. It was during the 8th Symposium in August 1988 that the idea of bringing together important results on the topic of Identification of continuous time systems was conceived. Several distinguished colleagues, who were with us in Beijing at that time, encouraged us by promising on the spot to contribute to a comprehensive volume of collective work. Subsequently, we contacted colleagues all over the world, known for their work in this area, with a formal request to contribute to the proposed volume. The response was prompt and overwhelmingly encouraging. We sincerely thank all the authors for their valuable contributions covering various aspects of identification of continuous time systems.

Nonlinear System Identification
Nonlinear System Identification

Author: Stephen A. Billings

Publisher: John Wiley & Sons

Published: 2013-07-29

Total Pages: 611

ISBN-13: 1118535553

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Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) model The orthogonal least squares algorithm that allows models to be built term by term where the error reduction ratio reveals the percentage contribution of each model term Statistical and qualitative model validation methods that can be applied to any model class Generalised frequency response functions which provide significant insight into nonlinear behaviours A completely new class of filters that can move, split, spread, and focus energy The response spectrum map and the study of sub harmonic and severely nonlinear systems Algorithms that can track rapid time variation in both linear and nonlinear systems The important class of spatio-temporal systems that evolve over both space and time Many case study examples from modelling space weather, through identification of a model of the visual processing system of fruit flies, to tracking causality in EEG data are all included to demonstrate how easily the methods can be applied in practice and to show the insight that the algorithms reveal even for complex systems NARMAX algorithms provide a fundamentally different approach to nonlinear system identification and signal processing for nonlinear systems. NARMAX methods provide models that are transparent, which can easily be analysed, and which can be used to solve real problems. This book is intended for graduates, postgraduates and researchers in the sciences and engineering, and also for users from other fields who have collected data and who wish to identify models to help to understand the dynamics of their systems.

Identification of Continuous-Time Systems
Identification of Continuous-Time Systems

Author: Allamaraju Subrahmanyam

Publisher: CRC Press

Published: 2019-12-06

Total Pages: 143

ISBN-13: 1000732622

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Models of dynamical systems are required for various purposes in the field of systems and control. The models are handled either in discrete time (DT) or in continuous time (CT). Physical systems give rise to models only in CT because they are based on physical laws which are invariably in CT. In system identification, indirect methods provide DT models which are then converted into CT. Methods of directly identifying CT models are preferred to the indirect methods for various reasons. The direct methods involve a primary stage of signal processing, followed by a secondary stage of parameter estimation. In the primary stage, the measured signals are processed by a general linear dynamic operation—computational or realized through prefilters, to preserve the system parameters in their native CT form—and the literature is rich on this aspect. In this book: Identification of Continuous-Time Systems-Linear and Robust Parameter Estimation, Allamaraju Subrahmanyam and Ganti Prasada Rao consider CT system models that are linear in their unknown parameters and propose robust methods of estimation. This book complements the existing literature on the identification of CT systems by enhancing the secondary stage through linear and robust estimation. In this book, the authors provide an overview of CT system identification, consider Markov-parameter models and time-moment models as simple linear-in-parameters models for CT system identification, bring them into mainstream model parameterization via basis functions, present a methodology to robustify the recursive least squares algorithm for parameter estimation of linear regression models, suggest a simple off-line error quantification scheme to show that it is possible to quantify error even in the absence of informative priors, and indicate some directions for further research. This modest volume is intended to be a useful addition to the literature on identifying CT systems.

Identification of Continuous Systems
Identification of Continuous Systems

Author: Heinz Unbehauen

Publisher:

Published: 1987

Total Pages: 402

ISBN-13:

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Bringing together important advances in the field of continuous system identification, this book deals with both parametric and nonparametric methods. It pays special attention to the problem of retaining continuous model parameters in the estimation equations, to which all the existing techniques used in estimating discrete models may be applied. It is aimed at both the academic researcher and the control engineer in industry. The techniques covered range from certain simple numerical or graphical methods applicable to some of the frequently encountered model forms, to attractive recursive algorithms for continuous model identification suitable for real time implementation. These include the recent methods based on orthogonal functions such as those of Walsh and Poisson moment functionals. Some techniques based on stable model adaptation principles are also presented and illustrated.

Optimal and Robust Estimation
Optimal and Robust Estimation

Author: Frank L. Lewis

Publisher: CRC Press

Published: 2017-12-19

Total Pages: 638

ISBN-13: 1351837540

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More than a decade ago, world-renowned control systems authority Frank L. Lewis introduced what would become a standard textbook on estimation, under the title Optimal Estimation, used in top universities throughout the world. The time has come for a new edition of this classic text, and Lewis enlisted the aid of two accomplished experts to bring the book completely up to date with the estimation methods driving today's high-performance systems. A Classic Revisited Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second Edition reflects new developments in estimation theory and design techniques. As the title suggests, the major feature of this edition is the inclusion of robust methods. Three new chapters cover the robust Kalman filter, H-infinity filtering, and H-infinity filtering of discrete-time systems. Modern Tools for Tomorrow's Engineers This text overflows with examples that highlight practical applications of the theory and concepts. Design algorithms appear conveniently in tables, allowing students quick reference, easy implementation into software, and intuitive comparisons for selecting the best algorithm for a given application. In addition, downloadable MATLAB® code allows students to gain hands-on experience with industry-standard software tools for a wide variety of applications. This cutting-edge and highly interactive text makes teaching, and learning, estimation methods easier and more modern than ever.

Optimal and Robust Estimation
Optimal and Robust Estimation

Author: Frank L. Lewis

Publisher: CRC Press

Published: 2017-12-19

Total Pages: 546

ISBN-13: 1420008293

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More than a decade ago, world-renowned control systems authority Frank L. Lewis introduced what would become a standard textbook on estimation, under the title Optimal Estimation, used in top universities throughout the world. The time has come for a new edition of this classic text, and Lewis enlisted the aid of two accomplished experts to bring the book completely up to date with the estimation methods driving today's high-performance systems. A Classic Revisited Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second Edition reflects new developments in estimation theory and design techniques. As the title suggests, the major feature of this edition is the inclusion of robust methods. Three new chapters cover the robust Kalman filter, H-infinity filtering, and H-infinity filtering of discrete-time systems. Modern Tools for Tomorrow's Engineers This text overflows with examples that highlight practical applications of the theory and concepts. Design algorithms appear conveniently in tables, allowing students quick reference, easy implementation into software, and intuitive comparisons for selecting the best algorithm for a given application. In addition, downloadable MATLAB® code allows students to gain hands-on experience with industry-standard software tools for a wide variety of applications. This cutting-edge and highly interactive text makes teaching, and learning, estimation methods easier and more modern than ever.

Design of Nonlinear Control Systems with the Highest Derivative in Feedback
Design of Nonlinear Control Systems with the Highest Derivative in Feedback

Author: Valery D. Yurkevich

Publisher: World Scientific

Published: 2004

Total Pages: 374

ISBN-13: 9812388990

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This unique book presents an analytical uniform design methodology of continuous-time or discrete-time nonlinear control system design which guarantees desired transient performances in the presence of plant parameter variations and unknown external disturbances. All results are illustrated with numerical simulations, their practical importance is highlighted, and they may be used for real-time control system design in robotics, mechatronics, chemical reactors, electrical and electro-mechanical systems as well as aircraft control systems. The book is easy reading and is suitable for teaching.