Muhammad Haryo Setiawan
Universitas Ahmad Dahlan

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Toward an Advanced Gas Composition Measurement Device for Chemical Reaction Analysis Fajriansya Gonibala; Siti Jamilatun; Shinta Amelia; Alfian Ma’arif; Muhammad Haryo Setiawan
Buletin Ilmiah Sarjana Teknik Elektro Vol. 5 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v5i4.9249

Abstract

The research details the development of a reactor-based monitoring system designed to identify and monitor gases generated within industrial chemical reactors. Consisting of nine MQ and DHT11 sensors, this reactor design allows for simultaneous measurement of temperature and humidity within the sample. Using a sensor array methodology, this research utilizes multiple sensors to collect and process analog signals to improve the accuracy of gas identification within samples. These analog signals obtained from the sensors are processed by an Arduino Mega 2560 microcontroller using the Arduino IDE software. The research, conducted on ten different samples, shows methane (CH4), hydrogen (H2), and alcohol (C2H6O) as the most concentrated gases. Notably, certain samples such as batik waste, honey, Robusta coffee, and sambal have a significant impact on methane gas concentrations. In addition, substances such as Robusta Coffee, Sprite, Syrup, and Oyster Sauce have a significant effect on hydrogen gas concentrations, while Robusta Coffee, Sambal, Arabica Coffee, and Pepper have a significant effect on alcohol gas concentrations. In addition, of the nine MQ sensors used, the MQ3, MQ4, and MQ8 are particularly effective at detecting alcohol, methane, and hydrogen gases, respectively, in the samples tested.
Enhancing Speed Estimation in DC Motors using the Kalman Filter Method: A Comprehensive Analysis Muhammad Haryo Setiawan; Alfian Ma'arif; Chokri Rekik; Ahmed J. Abougarair; Atinkut Molla Mekonnen
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 1 (2024): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i1.26591

Abstract

The accurate estimation of speed is crucial for optimizing the performance and efficiency of DC motors, which find extensive applications in various domains. However, the presence of noise ripple, caused by interactions with magnetic or electromagnetic fields, poses challenges to speed estimation accuracy. In this article, we propose the implementation of the Kalman Filter method as a promising solution to address these challenges. The Kalman Filter is a recursive mathematical algorithm that combines measurements from multiple sources to estimate system states with improved accuracy. By employing the Kalman Filter, it becomes possible to estimate the true speed of DC motors while effectively reducing the adverse effects of noise ripple. This research focuses on determining the optimal values for the Kalman Filter parameters and conducting experiments on a DC motor to evaluate the performance of the proposed approach. The experimental results demonstrate that the Kalman Filter significantly improves the control of speed oscillations and enhances the stability of the DC motor system. Furthermore, a comprehensive analysis of the system's response and parameter tuning reveals the impact of different parameter combinations on settling time, overshoot, and rise time. By carefully selecting appropriate parameters, the proposed approach contributes to accurate speed estimation and effective control of DC motors, advancing the understanding and application of the Kalman Filter in various relevant fields. Overall, this research provides valuable insights into enhancing the performance and efficiency of DC motors through the integration of the Kalman Filter method.