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All Journal GEMA TEKNOLOGI Jurnal Elektronika dan Telekomunikasi
Nugroho, Tsani Hendro
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Computer Science & IT Electrical & Electronics Engineering Engineering

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DESAIN SISTEM KENDALI UMPAN BALIK STATE PADA KASUS KONTINYU UNTUK MEJA KERJA CNC Mangkusasmito, Fakhruddin; Nugroho, Tsani Hendro
Gema Teknologi Vol 20, No 2 (2019): October 2018 - April 2019
Publisher : Vocational School Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (697.991 KB) | DOI: 10.14710/gt.v20i2.22641

Abstract

Fakhruddin Mangkusasmito, Tsani Hendro Nugroho in this paper explain that One of the important control system in the manufacturing industry is the position control. Mainly in the Computer Numerical Control (CNC) machine, work-table motion control system is used to regulate work-table movements when the machine process a workpieces on it. On standard machines, work-table movements are two axes (X-Y), which is driven by a motor and lead-screw. The discussion in this research only focus on one axis assuming that the systems on both axes are the same and independent. In this research, MATLAB is used to describe the behaviour of the system and also to design appropriate control system in continuos system using state feedback linear controller such as pole placement , tracking system, full order compensator and reduced order compensator. The goal is to obtain a fast response with a rapid rise time and settling time to a step command, while not exceeding an overshoot of 5%. The specification are than a percent overshoot equal to1%, 0,05s settling time and 0,03s rise time. The performance of each control methods are simulated and analyzed to decide the best suit control method for the systems with such criteria. And the result verify that using tracking system controller method achieve such specification with 0% overshoot, 0,04s settling time and 0,028s rise time.
Performance Comparison of Particle Filter, Optical Flow, and CSRT in Unsupervised Visual Tracking for Mobile Robots Taufiqurrohman, Heru; Muis, Abdul; Wijayanto, Yusuf Nur; Nugroho, Tsani Hendro; Cahya, Zaid
Jurnal Elektronika dan Telekomunikasi Vol 25, No 1 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.688

Abstract

This study addresses the challenges of selecting a suitable visual tracking method for real-time mobile robot applications, particularly in scenarios where the target is moving on the ground. The primary research problem addressed is the need for a flexible, computationally efficient tracking method that does not rely on pre-existing labelled datasets, as is often required by deep learning approaches. Unsupervised methods can overcome this problem by utilizing object motion information in each image frame without prior training. With many unsupervised tracking methods available, choosing an appropriate algorithm that can perform efficiently under dynamic conditions becomes a critical problem. The study compares the performance of three unsupervised visual tracking methods: particle filter, optical flow, and channel and spatial reliability tracker (CSRT) under various tracking conditions. The dataset used includes challenges such as moving target variations, changes in object scale, viewpoint changes, suboptimal lighting, image blurring, partial occlusions, and abrupt movements. Evaluation criteria include tracking accuracy, resistance to occlusion, and computational efficiency. The particle filter with ORB and a constant velocity model achieves a root mean square error (RMSE) of 36.47 pixels at 13 frames per second (fps). Optical flow performs best with an RMSE of 10.79 pixels at 30 fps, while CSRT shows an RMSE of 252.35 pixels at 4 fps. These findings highlight the effectiveness of optical flow for real-time applications, making it a promising solution for mobile robot visual tracking in challenging situations.
Advanced State Estimations for Gravitational Oil/Water Separator Tanks using a Kalman Filter and Multi-Model Hypothesis Testing Cahya, Zaid; Siregar, Parsaulian; Ekawati, Estiyanti; Bahiuddin, Irfan; Cahya, Dito Eka; Nugroho, Tsani Hendro; Taufiqurrohman, Heru; Boudaoud, Mohammed
Jurnal Elektronika dan Telekomunikasi Vol 25, No 1 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.682

Abstract

This paper presents a new application of the Kalman filter with Hypothesis testing for a fast and robust model-based estimator for measuring level interfaces of atmospheric gravitational oil-water separator tanks. A newly developed semi-empirical linearized model is applied in the estimator algorithm. A multi-model hypothesis-testing algorithm for covering more scenarios was deployed. The proposed method provides a cost-effective and straightforward solution for estimating all state variables in an oil-water separator. Our evaluation results demonstrate that the proposed algorithm achieves high accuracy with an observation error of less than 2% and a false alarm rate of 3.3% under 50-70% working conditions. Furthermore, the estimator can effectively handle process noise with a 10% feed offset. The proposed platform requires only a few installed sensors yet can accurately estimate unknown parameters. The proposed approach offers a robust and practical soft sensor solution for gravitational oil/water separators
Co-Authors Abdul Muis Bahiuddin, Irfan Boudaoud, Mohammed Cahya, Dito Eka Cahya, Zaid Ekawati, Estiyanti Fakhruddin Mangkusasmito Parsaulian Siregar Taufiqurrohman, Heru Yusuf Nur Wijayanto, Yusuf Nur