Advanced search
Publication Cover
International Journal of Control Volume 51, 1990 - Issue 6
Submit an article Journal homepage
1,519
Views
821
CrossRef citations to date
0
Altmetric
Original Articles

Non-linear system identification using neural networks

S. CHEN Department of Electrical Engineering, University of Edinburgh, Mayfield Road, Edinburgh, EH9 3JL, Scotland, U.K
,
S. A. BILLINGS Department of Control Engineering, University of Sheffield, Mappin Street, Sheffield, SI 3JD, England, U.K
&
P. M. GRANT Department of Electrical Engineering, University of Edinburgh, Mayfield Road, Edinburgh, EH9 3JL, Scotland, U.K
Pages 1191-1214 | Received 28 Aug 1989, Published online: 27 Mar 2007
 
Sample our Engineering & Technology journals, sign in here to start your access, latest two full volumes FREE to you for 14 days

Abstract

Multi-layered neural networks offer an exciting alternative for modelling complex non-linear systems. This paper investigates the identification of discrete-time nonlinear systems using neural networks with a single hidden layer. New parameter estimation algorithms are derived for the neural network model based on a prediction error formulation and the application to both simulated and real data is included to demonstrate the effectiveness of the neural network approach.

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:

Order Reprints Request Corporate Permissions

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:

Request Academic Permissions

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

Predictions of vertical train-bridge response using artificial neural network-based surrogate model:
Source: SAGE Publications
A dynamic neural network model for predicting risk of Zika in real-time
Source: Springer Science and Business Media LLC
Arsenic removal from water using N,N-diethylethanolammonium chloride based DES-functionalized CNTs: (NARX) neural network approach
Source: IWA Publishing
LONG-TERM STATIC DEFORMATION DATA OF FEI-TSUI ARCH DAM
Source: Wiley
Artificial Neural Network Approach for Modelling of Mercury Ions Removal from Water Using Functionalized CNTs with Deep Eutectic Solvent.
Source: MDPI AG
A modified homotopy optimization for parameter identification in dynamic systems with backlash discontinuity
Source: Springer Science and Business Media LLC
On the approximate realization of continuous mappings by neural networks
Source: Elsevier BV
The skipjack tuna fishery in the west-central Pacific Ocean: applying neural networks to detect habitat preferences
Source: Springer Science and Business Media LLC
Fault detection in distillation column using NARX neural network
Source: Springer Science and Business Media LLC
Improved least squares identification
Source: Informa UK Limited
Dynamic neural networks for gas turbine engine degradation prediction, health monitoring and prognosis
Source: Springer Science and Business Media LLC
Threshold Models in Non-linear Time Series Analysis
Source: Springer New York
A prediction-error and stepwise-regression estimation algorithm for non-linear systems
Source: Informa UK Limited
Development of riverbank erosion rate predictor for natural channels using NARX-QR Factorization model: a case study of Sg. Bernam, Selangor, Malaysia
Source: Springer Science and Business Media LLC
A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of the Daily Direct Solar Radiation
Source: Multidisciplinary Digital Publishing Institute
Input-output parametric models for non-linear systems Part I: deterministic non-linear systems
Source: Informa UK Limited
Parameter estimation of dynamical systems via a chaotic ant swarm.
Source: American Physical Society (APS)
New recursive parameter estimation algorithms with varying but bounded gain matrix
Source: Informa UK Limited
Novel approaches for parameter estimation of local linear models for dynamical system identification
Source: Springer Science and Business Media LLC
Approximation by superpositions of a sigmoidal function
Source: Springer Science and Business Media LLC
Constructing NARMAX models using ARMAX models
Source: Informa UK Limited
Identification of non-linear rational systems using a prediction-error estimation algorithm
Source: Informa UK Limited
Dynamic Bus Travel Time Prediction Using an ANN-based Model
Source: Association for Computing Machinery (ACM)
Black box modeling of a turboshaft gas turbine engine fuel control unit based on neural NARX
Source: SAGE Publications
A NEURAL NETWORK APPROACH TO ON-LINE IDENTIFICATION OF NONLINEAR SYSTEMS
Source: Informa UK Limited
Soft Sensors in the Primary Aluminum Production Process Based on Neural Networks Using Clustering Methods.
Source: Multidisciplinary Digital Publishing Institute
Recursive prediction error parameter estimator for non-linear models
Source: Informa UK Limited
A Novel Hybrid Data-Driven Modeling Method for Missiles
Source: MDPI AG
Neural Partial Differentiation for Aircraft Parameter Estimation Under Turbulent Atmospheric Conditions
Source: Springer Science and Business Media LLC
Mercury removal from water using deep eutectic solvents-functionalized multi walled carbon nanotubes: Nonlinear autoregressive network with an exogenous input neural network approach
Source: Wiley
Determining power consumption using neural model in multibody systems with clearance and flexible joints
Source: Springer Science and Business Media LLC
Paper: Maximum-power validation of models without higher-order fitting
Source: Elsevier BV
OFFSET-FREE MODEL PREDICTIVE CONTROL
Source: Wiley
Thailand tourism forecasting based on a hybrid of discrete wavelet decomposition and NARX neural network
Source: Emerald

Linking provided by 

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.