A new methodology for identifying non-linear NARMAX models, from noise corrupted data, is introduced based on semi-orthogonal wavelet multiresolution approximations. An adaptive model sequencing strategy is introduced to infer model complexity from the data while reducing computational costs. This is used in conjunction with an iterative orthogonal-forward-regression routine coupled with model validity tests to identify sparse but accurate wavelet series representations of non-linear processes. Experimental data from two real systems, a liquid level system and from a civil engineering structure are used to illustrate the effectiveness of the new identification procedure.
International Journal of Control
Volume 74, 2001 - Issue 18
![Sample our Mathematics & Statistics journals, sign in here to start your FREE access for 14 days]({"type":"image" , "src" : "/sda/5943/TOC-Subject-Sample-2021-Mathematics-Statistics.jpg"})
Reprints and Corporate Permissions
Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?
To request a reprint or corporate permissions for this article, please click on the relevant link below:
Academic Permissions
Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?
Obtain permissions instantly via Rightslink by clicking on the button below:
If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.
Related Research Data
Input-output parametric models for non-linear systems Part I: deterministic non-linear systems
Source:
Informa UK Limited
Model validation tests for multivariable nonlinear models including neural networks
Source:
Informa UK Limited
Compression of Wavelet Decompositions
Source:
JSTOR
Structure identification of nonlinear dynamic systems—a survey on input/output approaches
Source:
Elsevier BV
Nonlinear black-box modeling in system identification: a unified overview
Source:
Elsevier BV
Extended model set, global data and threshold model identification of severely non-linear systems
Source:
Informa UK Limited
Mathematical Control Theory
Source:
Springer New York
A SMOOTHING ALGORITHM FOR NONLINEAR TIME SERIES
Source:
World Scientific Pub Co Pte Lt
Continuous-Time System Identification for Linear and Nonlinear Systems Using Wavelet Decompositions
Source:
World Scientific Pub Co Pte Lt
Wavelet-based system identification for nonlinear control
Source:
Institute of Electrical and Electronics Engineers (IEEE)
A new look at the statistical model identification
Source:
Institute of Electrical and Electronics Engineers (IEEE)
A theory for multiresolution signal decomposition: the wavelet representation
Source:
Institute of Electrical and Electronics Engineers (IEEE)
Wavelet networks
Source:
Institute of Electrical and Electronics Engineers (IEEE)
Identification of nonlinear systems–a survey
Source:
Institution of Engineering and Technology (IET)
Adapting to Unknown Smoothness via Wavelet Shrinkage
Source:
Informa UK Limited
A prediction-error and stepwise-regression estimation algorithm for non-linear systems
Source:
Informa UK Limited
A Wavelet-Based Approach to Identifying Structural Modal Parameters from Seismic Response and Free Vibration Data
Source:
Wiley
Matching pursuits with time-frequency dictionaries
Source:
Institute of Electrical and Electronics Engineers (IEEE)
A new look at the statistical model identification
Source:
Institute of Electrical and Electronics Engineers (IEEE)
ASMO—Dan algorithm for adaptive spline modelling of observation data
Source:
Informa UK Limited
Nonlinear Model Validation Using Correlation Tests
Source:
Informa UK Limited
Representations of non-linear systems: the NARMAX model
Source:
Informa UK Limited
Recursive maximum likelihood identification of a non-linear output-affine model
Source:
Informa UK Limited
Bayesian Methods for Updating Dynamic Models
Source:
ASME International
Using wavelet network in nonparametric estimation
Source:
HAL CCSD
Projection Pursuit Regression
Source:
Informa UK Limited
On compactly supported spline wavelets and a duality principle
Source:
American Mathematical Society (AMS)
DISCRETE WAVELET MODELS FOR IDENTIFICATION AND QUALITATIVE ANALYSIS OF CHAOTIC SYSTEMS
Source:
World Scientific Pub Co Pte Lt
A Practical Guide to Splines
Source:
Springer New York
Correlation based model validity tests for non-linear models
Source:
Informa UK Limited
Practical identification of NARMAX models using radial basis functions
Source:
Informa UK Limited
Linking provided by
