Mohamad Ezral Baharudin
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Preferred name
Mohamad Ezral Baharudin
Official Name
Mohamad Ezral, Baharudin
Alternative Name
Baharudin, M. E.
Baharudin, Mohamad Ezral
Main Affiliation
Scopus Author ID
56016804900
Researcher ID
CCO-4698-2022

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  • Publication
    System identification of flexible structure using firefly algorithm
    ( 2021-05-03)
    Mohd Sazli Saad
    ;
    Noor Fadhilah Mat Ros
    ;
    Mohamad Ezral Baharudin
    ;
    Mohd Zakimi Zakaria
    ;
    Azuwir Mohd Nor
    This paper originally concentrates on application of firefly algorithm on modeling of flexible beam. An attempt of obtaining a linear parametric model is accomplished by acquiring the input-output data from the vibration of beam and followed by the selection the auto regressive with exogenous inputs (ARX) model structure as a benchmark for mathematical model of beam. The parameters of the model structure are identified using firefly algorithm. A few sets of parameter settings are tested to find the most optimal value. The best parameter setting estimation is selected based on performance of model. The model is compared with the model from conventional estimation approach and validated using validity test. It is found that firefly algorithm produces the best ARX model with the lowest MSE compared to the least square algorithm.
      3  32
  • Publication
    ARx modeling of flexible beam system using bat algorithm
    ( 2021-05-03)
    Mohd Sazli Saad
    ;
    Noor Fadhilah Mat Ros
    ;
    Mohd Zakimi Zakaria
    ;
    Mohamad Ezral Baharudin
    ;
    Azuwir Mohd Nor
    This paper describes the development of dynamic model of flexible beam system using system identification method based on nature inspired algorithm i.e. bat algorithm. At first, input-output data from the experimental rig of flexible beam were collected such that input signal is taken from piezo actuator and output signal from the laser displacement sensor. Then, linear parametric model structure is accomplished using auto regressive with exogenous inputs (ARX). The optimal parameters of the ARX model are identified using bat algorithm. The best parameter setting estimation is selected based on the best fit criterion i.e mean square error (MSE). The identified model is compared with the model from conventional estimation approach. Simulation results show that bat algorithm can outperform the least square algorithm in parametric modelling of the flexible beam.
      2  33