Surina Mat Suboh
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Surina Mat Suboh
Official Name
Surina, Mat Suboh
Alternative Name
Suboh, S. M.
Mat Suboh, S.
Surina, M. S.
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Scopus Author ID
57189243590

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  • Publication
    Fault Detection Analysis for Three Phase Induction Motor Drive System using Neural Network
    ( 2021-06-11)
    Mohar N.A.
    ;
    Ernie Che Mid
    ;
    Surina Mat Suboh
    ;
    Nor Hanisah Baharudin
    ;
    Ahamad N.B.
    ;
    Rahman N.A.
    ;
    Ruslan E.
    ;
    Hadi D.A.
    One of the most important components of the industrial process is known to be the three-phase induction motor. This device, however, is prone to electrical and mechanical faults, which may cause a substantial component or financial losses. The fault analysis received growing attention due to a need to increase reliability and to decrease potential output loss due to machine breakdown. Thus, the purpose of this paper is to present a simple and reliable fault analysis based on the Neural Network (NN) is proposed. The NN method is a simpler approach without a diagnostic professional to review data and diagnose issues. Various fault disputes of induction motor are developed and analysed using the NN method. The main types of faults considered are over-voltage, under-voltage, and unbalanced voltage faults. The trained network is tested with simulated fault current and voltage data.
  • Publication
    Output Power Maximization of DFIG Wind Turbine using Linear MPC Technique
    ( 2021-06-11)
    Surina Mat Suboh
    ;
    Hassan M.S.
    ;
    Nor Hanisah Baharudin
    ;
    Kumuthawathe Ananda-Rao
    ;
    Ahamad N.B.
    ;
    Ernie Che Mid
    ;
    Othman M.
    ;
    Sardi J.
    Wind energy conversion systems have been attracting wide attention as a renewable energy source. To extract maximum energy from the wind turbine, an efficient controller plays an important role. The target of this paper is to develop a Linear Model Predictive Control (MPC) to maximize power production according to wind speed. Firstly, the DFIG wind turbine model was linearized at a specific operating point by using the Jacobian method. The MPC then was developed based on the linearized model where wind speed equal to 8 m/s is chosen as its operating area. The controller was tested to deal with different wind speed. A presence of a certain range of wind speed errors was included to evaluate the controller efficiency. Numerical simulation was done by using MATLAB software. The proposed controller has shown great performances when within its operating area but downgraded when moving away from its operating area. Imprecise wind speed measurement has shown a significant impact on the controller efficiency.
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