Comparative Study between ARX and ARMAX System Identification

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Farzin Piltan 1,* Shahnaz TayebiHaghighi 1 Nasri B. Sulaiman 2

1. Intelligent Systems and Robotics Lab, Iranian Institute of Advanced Science and Technology (IRAN SSP), Shiraz/Iran

2. Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Malaysia

* Corresponding author.


Received: 1 May 2016 / Revised: 11 Aug. 2016 / Accepted: 6 Oct. 2016 / Published: 8 Feb. 2017

Index Terms

System identification, highly nonlinear dynamic equations, Arx system identification algorithm, Armax system identification algorithm


System Identification is used to build mathematical models of a dynamic system based on measured data. To design the best controllers for linear or nonlinear systems, mathematical modeling is the main challenge. To solve this challenge conventional and intelligent identification are recommended. System identification is divided into different algorithms. In this research, two important types algorithm are compared to identifying the highly nonlinear systems, namely: Auto-Regressive with eXternal model input (ARX) and Auto Regressive moving Average with eXternal model input (Armax) Theory. These two methods are applied to the highly nonlinear industrial motor.

Cite This Paper

Farzin Piltan, Shahnaz TayebiHaghighi, Nasri B. Sulaiman,"Comparative Study between ARX and ARMAX System Identification", International Journal of Intelligent Systems and Applications(IJISA), Vol.9, No.2, pp.25-34, 2017. DOI:10.5815/ijisa.2017.02.04


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