Article Per Year (5 Year)
p-Index From 2021 - 2026
1.066
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics International Journal of Robotics and Control Systems
Zakaria, Muhammad Iqbal
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : International Journal of Robotics and Control Systems

 1 
Classifying Gait Disorder in Neurodegenerative Disorders Among Older Adults Using Machine Learning Rahman, Kazi Ashikur; Shair, Ezreen Farina; Abdullah, Abdul Rahim; Lee, Teng Hong; Ali, Nursabillilah Mohd; Zakaria, Muhammad Iqbal; Al Betar, Mohammed Azmi
International Journal of Robotics and Control Systems Vol 5, No 2 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i2.1722

Abstract

Gait disorders are a significant concern for older adults, particularly those with neurodegenerative diseases such as Parkinson’s disease, Huntington’s disease, and Amyotrophic Lateral Sclerosis. Accurately classifying these conditions using gait data remains a complex challenge, especially in older populations, due to age-related changes in gait patterns, comorbidities, and increased variability in mobility, which can obscure disease-specific characteristics. This study explicitly classifies neurodegenerative diseases in older adults by analysing age-specific gait force data. Continuous Wavelet Transform (CWT) was utilised for advanced feature extraction, capturing both temporal and spectral signal characteristics. Classifiers including Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), and Multilayer Perceptron (MLP) were employed. The results demonstrated that SVM achieved an accuracy of 87.5%, outperforming RF and MLP, which achieved 83.3% and 50.0%, respectively. These findings underscore the importance of using tailored machine learning approaches to improve the diagnosis and management of neurodegenerative diseases in older adults. The potential for real-world application includes integration into clinical settings, enabling early detection and personalized interventions for individuals with gait disorders.
Formulation of a Lyapunov-Based PID Controller for Level Control of a Coupled-Tank System Kamarudin, Muhammad Nizam; Md Rozali, Sahazati; Azam, Sazuan Nazrah Mohd; Hairi, Mohd Hendra; Zakaria, Muhammad Iqbal
International Journal of Robotics and Control Systems Vol 5, No 3 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i3.1947

Abstract

This manuscript proposes a Proportional-Integral-Derivative (PID) control algorithm based on Lyapunov stability criteria. To verify the technique, the study is further extended to investigate its feasibility in controlling the liquid level of a coupled-tank system. A comparative study is conducted with the well-established Ziegler-Nichols tuning technique, known for its rapid and aggressive response. While Ziegler-Nichols often achieves quick tuning, it is prone to instability or degraded performance, particularly in systems with slow dynamics, such as the coupled-tank system. The results demonstrate the practical viability of the Lyapunov-based PID approach. The findings show that the Lyapunov-PID controller significantly outperforms the Ziegler-Nichols PID, achieving a 33.63% reduction in overshoot and a 45.14% improvement in settling time. These improvements highlight the advantage of incorporating Lyapunov-based criteria in PID design for systems where stability and performance are critical. However, the proposed approach has limitations such as increased computational complexity and the need for abstract tuning effort, along with difficulty in selecting appropriate Lyapunov functions.
Co-Authors Abdullah, Abdul Rahim Al Betar, Mohammed Azmi Ali, Nursabillilah Mohd Ariffin, Athirah Batrisyia Kamal Azam, Sazuan Nazrah Mohd Aziz Jafar, Muhammad Ihsan Dahlan, Nofri Yenita El Fezazi, Nabil Hairi, Mohd Hendra Lee, Teng Hong Md Rozali, Sahazati Mohamad Murad, Nor Syaza Farhana Muhammad Nizam Kamarudin Munim, Wan Noraishah Wan Abdul Murad, Nor Syaza Farhana Mohamad Rahman, Kazi Ashikur Shair, Ezreen Farina