Nasri B. Sulaiman

Work place: Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Malaysia



Research Interests: Robotics, Process Control System, Control Theory


Dr. Nasri Sulaiman advisor and supervisor of several high impact projects involving more than 150 researchers from countries around the world including Iran, Malaysia, Finland, Italy, Germany, South Korea, Australia, and the United States. Dr. Nasri Sulaiman has authored or co-authored more than 80 papers in academic journals, conference papers and book chapters. His papers have been cited at least 3000 times by independent and dependent researchers from around the world including Iran, Algeria, Pakistan, India, China, Malaysia, Egypt, Columbia, Canada, United Kingdom, Turkey, Taiwan, Japan, South Korea, Italy, France, Thailand, Brazil and more. Dr. Nasri Sulaiman has employed his remarkable expertise in these areas to make outstanding contributions as detailed below:


  • Design of a reconfigurable Fast Fourier Transform (FFT) Processor using multi-objective Genetic Algorithms (2008-UPM)
  • Power consumption investigation in reconfigurable Fast Fourier Transform (FFT) processor (2010-UPM)
  • Crest factor reduction And digital predistortion Implementation in Orthogonal frequency Division multiplexing (ofdm) systems(2011-UPM)
  • High Performance Hardware Implementation of a Multi-Objective Genetic Algorithm, (RUGS), Grant amount RM42,000.00, September(2012-UPM)
  • Nonlinear control for industrial robot manipulator(2010-IRAN SSP)
  • Intelligent Tuning The Rate Of Fuel Ratio In Internal Combustion Engine(2011-IRANSSP)
  • Design High Precision and Fast Dynamic Controller For Multi-Degrees Of Freedom Actuator(2013-IRANSSP)
  • Research on Full Digital Control for Nonlinear Systems(2011-IRANSSP)
  • Micro-Electronic Based Intelligent Nonlinear Controller(2015-IRANSSP)
  • Active Robot Controller for Dental Automation(2015-IRANSSP)
  • Design a Micro-Electronic Based Nonlinear Controller for First Order Delay System(2015-IRANSSP)

Author Articles
Comparative Study between ARX and ARMAX System Identification

By Farzin Piltan Shahnaz TayebiHaghighi Nasri B. Sulaiman

DOI:, Pub. Date: 8 Feb. 2017

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.

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