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Dananjaya Ariateja
Universitas Pertahanan Republik Indonesia, Bogor, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Transportation

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Empirical characterization of test platform effects on single-axis CubeSat reaction wheel ADCS with IoT-based PID tuning Bayu Nuar Khadapi Hasibuan; Dananjaya Ariateja; Satriya Utama; Rangga Taqwa; Ria Aprilianingsih
International Journal of Enterprise Modelling Vol. 20 No. 2 (2026): May: Enterprise Modelling
Publisher : International Enterprise Integration Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/int.jo.emod.v20i2.193

Abstract

Terrestrial testing of CubeSat Attitude Determination and Control System (ADCS) prototypes presents fundamental validation challenges because no laboratory platform perfectly replicates the free-floating microgravity condition of orbit. The empirical effect of such platform-induced dynamics on closed-loop reaction-wheel control performance, particularly for low-cost academic CubeSat programs, remains insufficiently characterized. This study aims to empirically compare two widely used low-cost test platforms a string suspension and a free bearing for a single-axis reaction-wheel ADCS prototype and to quantify how each platform’s parasitic dynamics constrain PID controller performance. A 1.5U CubeSat-class prototype with an ESP32-based controller, BNO055 IMU, and a Blynk Cloud IoT interface for real-time PID tuning was tested over five sessions (>1 hour of cumulative active testing). Performance was quantified using the Time-in-±5° metric, error standard deviation, settling time, and number of direction reversals. Quantitative results show that the string suspension yields a peak Time-in-±5° of 8.8% with error standard deviation of ±90.7–119.9°, driven by torsional-pendulum dynamics, while the free bearing yields a peak Time-in-±5° of only 1.2% with a stuck-and-jump signature characteristic of stiction. A Karnopp-friction simulation in Python reproduces a permanent steady-state error of ~5° under stiction, quantitatively validating stiction as the dominant non-linearity. The novelty of this work lies in the integrated combination of empirical multi-platform characterization, Karnopp-based stiction validation, and an open-source IoT-based PID tuning framework within a single low-cost experimental system, providing actionable guidance for academic CubeSat ADCS development under limited-facility conditions.
Implementation of GMSK Modulation Using GNU Radio for Cube Satellite De Shepherd Guella Winisia Zega; Dananjaya Ariateja; Herwin Hutapea
International Journal of Enterprise Modelling Vol. 20 No. 2 (2026): May: Enterprise Modelling
Publisher : International Enterprise Integration Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/int.jo.emod.v20i2.196

Abstract

The CubeSat platform has evolved to support a wide range of space missions, modulation schemes, and frequency bands, leading to a need for dependable ground-to-satellite communication systems. Software-defined radio (SDR) has become the modern RF communication system chosen method. The goal of this research is to be able to communicate with a satellite using a configurable SDR and GNU Radio. Other research has conducted GMSK signal simulations, SDR-to-SDR testing, or receiver-side validation only, while this study evaluates GMSK modulation using a CubeSat Engineering Model (EM). Signal was conducted with 276-byte data packets. Unpadded SDR transmissions failed to communicate, whereas a conventional RF signal generator achieved 100% success. Review of the RF generator revealed that it produces 1000 transmission symbols by default, including the data packet. Considering the longer transmission symbols, extra null symbols (zero-padding) were added to the end of the SDR packet in increments of 5 to 50 bytes. Symbol adjustment attempt led to a 100% packet-rate success of the GMSK communication link between the SDR and the EM. Findings revealed that consideration of signal factors such as transmission length, flowgraph configurations, and hardware compatibility is critical for communication performance.
A literature review: image restoration and enhancement techniques for slow scan television Eliana Maharani; Dananjaya Ariateja; Uvi Desi Fatmawati
International Journal of Enterprise Modelling Vol. 20 No. 2 (2026): May: Enterprise Modelling
Publisher : International Enterprise Integration Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/int.jo.emod.v20i2.197

Abstract

This systematic literature study seeks to computationally develop the optimum picture restoration architecture to handle the dual analog-digital degradation (strip noise and motion blur) of Slow Scan Television (SSTV) transmissions in narrowband radio frequencies during emergency operations. The study critically assessed 28 peer-reviewed algorithmic frameworks published between 2007 and 2025 using PRISMA criteria. The data synthesis procedure used a comparative analysis matrix to evaluate algorithms' quantitative efficacy, including PSNR and SSIM, against specific analogue failure instances. Under compounding degradation, individual computational methods fail, as shown by the synthesis. When exposed to severe analogue noise, unguided generative models hallucinate, whereas conventional spatial filters degrade edges. Comparative empirical research shows that a cascaded hybrid framework works best. Using a 5x5 median filter with 1D directed filtering as pre-processing suppresses high-density impulsive anomalies, improving baseline PSNR by 2.4 dB. The kernel-guided diffusion model over the pre-cleaned matrix accurately reconstructs structural weaknesses, raising SSIM indices to 0.92 even in datasets with significant oscillator blur. A quantitatively validated, domain-specific restoration process that combines spatial denoising with advanced generative priors is the main contribution of this research. This study scientifically proves that kernel-based diffusion models need spatial variance pre-filtering to work in radio-degraded scenarios, providing a reliable emergency visual communication framework for authentic signal reconstruction in internet-deprived environments.
Co-Authors Bayu Nuar Khadapi Hasibuan De Shepherd Guella Winisia Zega Eliana Maharani Herwin Hutapea Rangga Taqwa Ria Aprilianingsih Satriya Utama Uvi Desi Fatmawati