Experimental and Theoretical Techniques for Nonlinear Identification and Adaptive Cancellation

Experimental and Theoretical Techniques for Nonlinear Identification and Adaptive Cancellation
Author:
Publisher:
Total Pages: 0
Release: 2000
Genre:
ISBN:

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Under this project we developed and demonstrated new techniques for identification and adaptive control. For linear identification, we developed quadratically constrained least squares (QCLS) identification, which extends classical least squares identification and is more resistant to the effects of system noise. For nonlinear identification, we developed a sequential method for combined Hammerstein-nonlinear feedback models. This method uses a piecewise linear approximation to the system nonlinearity and is based on computationally efficient numerical procedures. For adaptive control, we developed controllers for adaptive disturbance rejection and adaptive stabilization. These methods were implemented on laboratory experiments involving active noise control and rotating imbalance stabilization.

System Identification

System Identification
Author: Tien C. Hsia
Publisher: Free Press
Total Pages: 200
Release: 1977
Genre: Science
ISBN:

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Mastering System Identification in 100 Exercises

Mastering System Identification in 100 Exercises
Author: Johan Schoukens
Publisher: John Wiley & Sons
Total Pages: 285
Release: 2012-04-02
Genre: Technology & Engineering
ISBN: 1118218507

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This book enables readers to understand system identification and linear system modeling through 100 practical exercises without requiring complex theoretical knowledge. The contents encompass state-of-the-art system identification methods, with both time and frequency domain system identification methods covered, including the pros and cons of each. Each chapter features MATLAB exercises, discussions of the exercises, accompanying MATLAB downloads, and larger projects that serve as potential assignments in this learn-by-doing resource.

System Identification (SYSID '03)

System Identification (SYSID '03)
Author: Paul Van Den Hof
Publisher: Elsevier
Total Pages: 2080
Release: 2004-06-29
Genre: Science
ISBN: 9780080437095

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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.

Nonlinear System Identification

Nonlinear System Identification
Author: Oliver Nelles
Publisher: Springer Science & Business Media
Total Pages: 785
Release: 2013-03-09
Genre: Technology & Engineering
ISBN: 3662043238

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Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.

Nonlinear Modeling

Nonlinear Modeling
Author: Johan A. K. Suykens
Publisher: Springer Science & Business Media
Total Pages: 284
Release: 1998-06-30
Genre: Language Arts & Disciplines
ISBN: 9780792381952

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This collection of eight contributions presents advanced black-box techniques for nonlinear modeling. The methods discussed include neural nets and related model structures for nonlinear system identification, enhanced multi-stream Kalman filter training for recurrent networks, the support vector method of function estimation, parametric density estimation for the classification of acoustic feature vectors in speech recognition, wavelet based modeling of nonlinear systems, nonlinear identification based on fuzzy models, statistical learning in control and matrix theory, and nonlinear time- series analysis. The volume concludes with the results of a time- series prediction competition held at a July 1998 workshop in Belgium. Annotation copyrighted by Book News, Inc., Portland, OR.