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About The NARMAX Model For A DC Motor Using ML PDF
This document presents a study using a NARMAX (nonlinear autoregressive moving average with exogenous inputs) model and multilayer perceptron (MLP) neural network to model a DC motor system. A NARMAX model describes a system's nonlinear input-output relationship as a difference equation. An MLP neural network was used to optimize the NARMAX model parameters. The modeling process involved collecting input-output motor data, determining the maximum model lags using Lipschitz analysis, fitting the NARMAX model structure using the MLP network, and validating the model predictions. The results showed the MLP network could accurately fit the NARMAX model to identify the nonlinear DC motor system.
Detailed Information
| Author: | ['Tancho Indra'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 5 |
| Language: | English |
| Format: | |
| Price: | FREE |
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