Palanisamy Ramasamy
SRM Institute of Science and Technology

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Innovative design and development of attitude determination and control systems for CubeSats with reaction wheels Thamizh Harsha S.; Thamizh Thentral T. M.; Palanisamy Ramasamy; Animesh Pal; Sabarish M.; Swastik Panda; Indraneela Das
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp109-118

Abstract

Attitude determination and control systems (ADCS) represent a critical facet of CubeSat missions, orchestrating the precise orientation and stabilization of these small satellites in the space environment. This paper presents a comprehensive design and development of an ADCS tailored for CubeSats, harnessing a reaction wheel system to deliver a cost-effective and dependable solution for small satellite applications. The research begins by elucidating the requisites and specifications for the ADCS and then delves into the design phase, complemented by intricate modelling and simulation employing MATLAB Simulink and the Webots Simulator. The results of this study underscore the exceptional performance of the proposed ADCS configuration, leveraging the reaction wheel model. This system demonstrates an unparalleled capacity to achieve precise and controlled attitude adjustments, well within the defined parameters. Furthermore, this research underscores the pivotal role played by efficient system design, meticulous simulation, and rigorous testing in the triumphant implementation of ADCS, greatly enhancing CubeSat missions and their contributions to the realm of space exploration and technology innovation. This comprehensive approach to the design and testing of an ADCS for CubeSats ensures that these diminutive satellites continue to make significant strides in space missions, paving the way for an exciting future of space research and technology development.
Long-term power prediction of photovoltaic panels based on meteorological parameters and support vector machine Saurabh Gupta; Palanisamy Ramasamy; Pandi Maharajan Murugamani; Selvakumar Kuppusamy; Selvabharathi Devadoss; Barath Suresh; Vignesh Kumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 2: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i2.pp687-695

Abstract

Solar energy is the most generally accessible energy in the entire globe. Proper solar panel maintenance is necessary to reduce reliance on imported energy. Continuous monitoring of the solar panel's power output is required. The deployment of internet of things (IoT) monitoring of solar panels for maintenance is the basis for the current research. A multi-variable long-term photovoltaic (PV) power production prediction approach based on support vector machine (SVM) is developed in this study with the aim of completely evaluating the influence of PV panels performance and actual operational state factors on the power generation efficiency. This study examines the use of SVM and climatic factors to forecast the long-term output of power from solar panels. A solar power facility in a semi-arid area provided the data utilized in this investigation. Temperature, humidity, wind speed, and sun radiation are some of the meteorological variables that were considered in the study. To anticipate the power generation of the panels, the SVM is trained using the climatic factors and the power generation data. The findings demonstrate that the SVM model consistently predicts the panels' long-term power generation with a high degree of accuracy.