Author: Jean-Noël AubrunPublisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 90
Book Description
Nonlinear systems for matching input-output of mathematical model to physical system.
Nonlinear Systems Identification in Presence of Nonuniqueness
Author: Jean-Noël AubrunPublisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 90
Book Description
Nonlinear systems for matching input-output of mathematical model to physical system.
NASA Technical Note
Author: Nonlinear System Identification
Author: Stephen A. BillingsPublisher: John Wiley & Sons
ISBN: 1118535553
Category : Technology & Engineering
Languages : en
Pages : 611
Book Description
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.
Scientific and Technical Aerospace Reports
Author: Parameter Estimation Techniques and Applications in Aircraft Flight Testing
Author: Monthly Catalogue, United States Public Documents
Author: Publisher:
ISBN:
Category : Government publications
Languages : en
Pages : 1508
Book Description
System Identification 2003
Author: Paul Van Den HofPublisher: Elsevier
ISBN: 0080913156
Category : Technology & Engineering
Languages : en
Pages : 2092
Book Description
The scope of the symposium covers all major aspects of system identification, experimental modelling, signal processing and adaptive control, ranging from theoretical, methodological and scientific developments to a large variety of (engineering) application areas. It is the intention of the organizers to promote SYSID 2003 as a meeting place where scientists and engineers from several research communities can meet to discuss issues related to these areas. Relevant topics for the symposium program include: Identification of linear and multivariable systems, identification of nonlinear systems, including neural networks, identification of hybrid and distributed systems, Identification for control, experimental modelling in process control, vibration and modal analysis, model validation, monitoring and fault detection, signal processing and communication, parameter estimation and inverse modelling, statistical analysis and uncertainty bounding, adaptive control and data-based controller tuning, learning, data mining and Bayesian approaches, sequential Monte Carlo methods, including particle filtering, applications in process control systems, motion control systems, robotics, aerospace systems, bioengineering and medical systems, physical measurement systems, automotive systems, econometrics, transportation and communication systems*Provides the latest research on System Identification*Contains contributions written by experts in the field*Part of the IFAC Proceedings Series which provides a comprehensive overview of the major topics in control engineering.
Non-linear Electromagnetic Systems
Author: Volkmar KosePublisher: IOS Press
ISBN: 9789051993813
Category : Science
Languages : en
Pages : 926
Book Description
The contents is dominated by the latest problems of applied electrical engineering, micro electromechanics, biosensor technology and biomagnetism. The book covers the numerical calculation methods for the design and optimization of sensors, actuators and electric machines, as well as the treatment of inverse problems, in materials testing and in the field of medicine in particular. Other central topics are the material properties and their simulation and much consideration is given to micro-electromechanics.
Ames Research Center Publications, July 1971 Through December 1973
Author: Subspace Identification for Linear Systems
Author: Peter van OverscheePublisher: Springer Science & Business Media
ISBN: 1461304652
Category : Technology & Engineering
Languages : en
Pages : 263
Book Description
Subspace Identification for Linear Systems focuses on the theory, implementation and applications of subspace identification algorithms for linear time-invariant finite- dimensional dynamical systems. These algorithms allow for a fast, straightforward and accurate determination of linear multivariable models from measured input-output data. The theory of subspace identification algorithms is presented in detail. Several chapters are devoted to deterministic, stochastic and combined deterministic-stochastic subspace identification algorithms. For each case, the geometric properties are stated in a main 'subspace' Theorem. Relations to existing algorithms and literature are explored, as are the interconnections between different subspace algorithms. The subspace identification theory is linked to the theory of frequency weighted model reduction, which leads to new interpretations and insights. The implementation of subspace identification algorithms is discussed in terms of the robust and computationally efficient RQ and singular value decompositions, which are well-established algorithms from numerical linear algebra. The algorithms are implemented in combination with a whole set of classical identification algorithms, processing and validation tools in Xmath's ISID, a commercially available graphical user interface toolbox. The basic subspace algorithms in the book are also implemented in a set of Matlab files accompanying the book. An application of ISID to an industrial glass tube manufacturing process is presented in detail, illustrating the power and user-friendliness of the subspace identification algorithms and of their implementation in ISID. The identified model allows for an optimal control of the process, leading to a significant enhancement of the production quality. The applicability of subspace identification algorithms in industry is further illustrated with the application of the Matlab files to ten practical problems. Since all necessary data and Matlab files are included, the reader can easily step through these applications, and thus get more insight in the algorithms. Subspace Identification for Linear Systems is an important reference for all researchers in system theory, control theory, signal processing, automization, mechatronics, chemical, electrical, mechanical and aeronautical engineering.