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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Hazlina Selamat
Universiti Teknologi Malaysia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Review on Psychological Crowd Model Based on LeBon’s Theory Vahid Behtaji Siahkal Mahalleh; Hazlina Selamat; Fargham Sandhu
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 2: June 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i2.6114

Abstract

Irrational crowds tend to adapt herd mentality, having group behaviour and high suggestion through interaction. It is important to see how an irrational crowd can be controlled to prevent undesirable crowd attitude. This paper reviews existing models and the controllers to provide a comprehensive study for crowd control. It focuses on a comprehensive analysis of the control of psychological crowd, modelled using LeBon’s theory; which defines the crowd behaviour in terms of crowd attitude. The crowd attitude is defined in terms of suggestibility and prestige and the crowd interaction is defined in terms of the interaction of prestige and suggestibility, which is naturally unstable. A controller is required to achieve stability. In this paper several control approaches are described and the best control approach is highlighted. The results conclude, the best control approach is using multiple control agents, since the control effort is reduced and the stabilizing time is improved.
Comprehensive Pineapple Segmentation Techniques with Intelligent Convolutional Neural Network Muhammad Azmi Ahmed Nawawi; Fatimah Sham Ismail; Hazlina Selamat
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i3.pp1098-1105

Abstract

This paper proposes an intelligent segmentation technique for pineapple fruit using Convolutional Neural Network (CNN). Cascade Object Detector (COD) method is used to detect the position of the pineapple from the captured image by returning the bounding box around the detecting pineapple. Image background such as ground, sky and other unwanted objects have been removed using Hue value, Adaptive Red and Blue Chromatic Map (ARB) and Normalized Difference Index (NDI) methods. However, the ARB and NDI methods are still producing misclassified error and the edge is not really smooth. In this case Template Matching Method (TMM) has been implemented for image enhancement process. Finally, an intelligent CNN is developed as a decision maker to select the best segmentation image ouput from ARB and NDI. The results obtained show that the proposed intelligent method has successfully verified the fruit from the background with high accuracy as compared to the conventional method.
Adaptive internal model control-proportional integral for robust control of three-phase active front-end rectifiers Azizah Abdul Razak; Norjulia Mohamad Nordin; Razman Ayop; Hazlina Selamat; Abobaker Kikki Abobaker; Nik Rumzi Nik Idris; Tole Sutikno
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp1794-1807

Abstract

Three-phase active front-end (AFE) rectifiers are widely deployed in motor drives, electric vehicle chargers, and grid-connected renewable energy systems, where precise DC-link voltage regulation is essential for stable converter operation. In practice, DC-link capacitance degrades over time, and load profiles vary dynamically, both degrading the DC-link voltage regulation performance. Conventional proportional-integral (PI) outer voltage controllers are designed based on nominal operating conditions, with limited stability margins resulting in sluggish or oscillatory DC-link voltage responses under significant load and parameter variations. This paper proposes an adaptive internal model control-proportional integral (AIMC-PI) outer voltage loop controller for a three-phase AFE rectifier. It extends the conventional IMC-PI structure by incorporating an active damping term, an internal feedforward gain, a reference filter, and a Lyapunov-based adaptation law that updates the embedded plant model and IMC filter time constant online ensuring closed-loop stability and bounded tracking error. Simulation results show that AIMC-PI achieves a faster dynamic response than PI and performance comparable to IMC-PI and linear active disturbance rejection control (LADRC) under nominal conditions. As DC-link capacitance degrades to 0.5C, AIMC-PI maintains a well-damped DC-link voltage, whereas LADRC exhibits noticeable oscillations. Experimentally, AIMC-PI successfully eliminates the AC-supply current and DC-link voltage ripples present in fixed-λ IMC-PI.
Co-Authors Abobaker Kikki Abobaker Azizah Abdul Razak Fargham Sandhu Fatimah Sham Ismail Muhammad Azmi Ahmed Nawawi Nik Rumzi Nik Idris Norjulia Mohamad Nordin Razman Ayop Tole Sutikno Vahid Behtaji Siahkal Mahalleh