Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Journal of Robotics and Control (JRC)
Veena, B. S.
Unknown Affiliation
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Journal of Robotics and Control (JRC)

 1 
Enhanced Total Harmonic Distortion Optimization in Cascaded H-Bridge Multilevel Inverters Using the Dwarf Mongoose Optimization Algorithm Salih, Sinan Q.; Mejbel, Basim Ghalib; Ahmad, B. A.; Taha, Taha A.; Bektaş, Yasin; Aldabbagh, Mohammed M; Hussain, Abadal-Salam T.; Hashim, Abdulghafor Mohammed; Veena, B. S.
Journal of Robotics and Control (JRC) Vol. 5 No. 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.23548

Abstract

Total harmonic distortion (THD) is one of the most essential parameters that define the operational efficiency and power quality in electrical systems applied to solutions like cascaded H-bridge multilevel inverters (CHB-MLI). The reduction of THD is crucial due to the fact that improving the system’s power quality and minimizing the losses are key for performance improvement. The purpose of this work is to introduce a new DMO-based approach to optimize the THD of the output voltage in a three-phase nine-level CHB-MLI. The proposed DMO algorithm was also subjected to intense comparison with two benchmark optimization techniques, namely Genetic Algorithm and Particle Swarm Optimization with regards to three parameters, namely convergence rate, stability, and optimization accuracy. A series of MATLAB simulations were run to afford the evaluation of each algorithm under a modulation index of between 0.1 and 1.0. The outcome of the experiment amply proves that in comparison with THD minimization for the given OP, the DMO algorithm was significantly superior to both RSA-based GA and PSO algorithms in their ability to yield higher accuracy while requiring lesser computational time. Consequently, this work could expand the application of the DMO algorithm as a reliable and effective means of enhancing THD in CHB-MLIs as well as advancing the overall quality of power systems in different electrical power networks.
AI-Driven Energy Management Techniques for Enhancing Network Longevity in Wireless Sensor Networks Hadi, AL-Shukrawi Ali Abbas; Wahab, Aeizaal Azman Bin Abdul; Hamzah, Firdaus Mohamad; Veena, B. S.
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

WSNs and mobile systems are critical for monitoring and data collection, but energy efficiency remains one of the biggest challenges due to very limited battery life in sensor nodes. The issue here is the challenge of energy management by adopting sophisticated optimization techniques and AI-driven methodologies. This research develops a Q-learning model of dynamic energy optimization. The proposed method uses MATLAB simulations and real-world testing to validate improvements. The methodology employs adaptive routing and real-time power adjustments, which optimize energy usage. The results show a 34.92% increase in energy savings compared to traditional methods, where baseline energy efficiency was 65%. The Packet Delivery Ratio (PDR) improved from a baseline of 85% to 96.38%, ensuring more reliable data communication. The network latency was reduced by 24 ms, from the initial 50 ms, thus enhancing real-time responsiveness. Q-learning approach was extended for an additional 10 hours against the 7-hour baseline established by conventional systems. These improvements are based on fully dynamic routing with online adjustments, which makes the network adaptive to changing environments. This methodology is promising for energy-efficient and high-performance communication systems in remote and critical applications. The findings contribute to sustainable network operations and reduce the maintenance costs, making WSNs viable for long-term deployments.
Co-Authors Ahmad, B. A. Aldabbagh, Mohammed M BEKTAS, YASIN Hadi, AL-Shukrawi Ali Abbas Hamzah, Firdaus Mohamad Hashim, Abdulghafor Mohammed Hussain, Abadal-Salam T. Mejbel, Basim Ghalib Salih, Sinan Q. Taha, Taha A. Wahab, Aeizaal Azman Bin Abdul