NARMAX Model Identification Using Multi-Objective Optimization Differential Evolution

Zakaria, Mohd Hafiz; Mansor, Zakwan; Nor, Azuwir Mohd; Saad, Mohd Sazli; Baharudin, Mohamad Ezral; Ahmad, Robiah

doi:10.30880/ijie.2018.10.07.018

Cited by 4 publications

(2 citation statements)

References 25 publications

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“…Z. [22] presented the expansion of the MOODE algorithm to get an adequate and adjusting nonlinear auto-regressive moving average with exogenous input (NARMAX) model. They (2018) [23] also presented the identification of a flexible beam system using Nonlinear Autoregressive Moving Average with Exogenous input (NARMAX) model.…”

Section: Introductionmentioning

confidence: 99%

An Improved All-Pass Filtered x Least Mean Square Algorithm

Mondal¹

2020

IJATCSE

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In this advanced world the usage of cutting-edge technologies in daily life increase day by day, whereby, acoustics noise also increases thereby affecting our life. So, an urgent requirement is to reduce this noise and improve the quality of life. Several Active noise control (ANC) systems using Artificial Neural Networks (ANN) are present but in limited performance. This paper is focused to develop an adaptive all-pass filtered x least square algorithm for a single-channel narrowband active noise control system using Nonlinear autoregressive with external (exogenous) input (NARX). The novelty of this research is that the All-pass filtered x LMS (APFxLMS) algorithm is introduced to the system without the need to identify the secondary path. Here the first-order all-pass filters with a single parameter are used to improve the convergence of the LMS algorithm. The results show that the proposed method performance is better in terms of regression and mean square error and on comparison with the recent method through numerical simulation shows that the proposed method is simpler to implement, and it achieves fast convergence speed.

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Section: Introductionmentioning

confidence: 99%

An Improved All-Pass Filtered x Least Mean Square Algorithm

Mondal¹

2020

IJATCSE

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“…It is a vital task as the first step in scientific studies for any system analysis [4]. The constructing process of models from experimental data is called system identification [5][6][7]. The model chosen should represent the accurate behavior of the real system.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Varied Model Order in GA-optimised Parameter Estimation of Toothbrush Rig System

Ainul

Mahzan

Ahmad

et al. 2019

IJIE

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Parameter estimation is a vital part in constructing the best model of a dynamic system. This paper analyzed the performance of toothbrush rig parameter estimation using different model orders. Parameter estimation process of the system is performed through system identification. The approximate mathematical model that resembles the real system is obtained when the output is measured after loading the input signal. The application of real-coded genetic algorithm (RCGA) is proposed as optimization method in estimating the parameters of dynamic system. The best model is obtained by optimizing the objective function of mean squared errors. The performance is analyzed to get the approximate model of the real system using three different model orders with 10 times analysis for each model. A few criteria have been considered which are the optimization result of objective function, time execution and validation process. The estimated parameters are acceptable and possible to be used for controller development later on. Estimated parameter with model order 3 is chosen as the best model or the dynamic system as it has the highest performance compared to others.

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Adapting Travelling Salesmen Problem for Real-Time UAS Path Planning Using Genetic Algorithm

Debnath

2021

Lecture Notes in Mechanical Engineering

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NARMAX Model Identification Using Multi-Objective Optimization Differential Evolution

Cited by 4 publications

References 25 publications

An Improved All-Pass Filtered x Least Mean Square Algorithm

An Improved All-Pass Filtered x Least Mean Square Algorithm

Evaluation of Varied Model Order in GA-optimised Parameter Estimation of Toothbrush Rig System

Adapting Travelling Salesmen Problem for Real-Time UAS Path Planning Using Genetic Algorithm

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