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All Journal Mechatronics, Electrical Power, and Vehicular Technology ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Jurnal Otomasi Kontrol dan Instrumentasi Teknomekanik
Tua Agustinus Tamba
Department of Electrical Engineering – University of Notre Dame, 275 Fitzpatrick Hall of Engineering, Notre Dame, IN 46556
Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Journal : Mechatronics, Electrical Power, and Vehicular Technology

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Modelling and Identification of Oxygen Excess Ratio of Self-Humidified PEM Fuel Cell System Leksono, Edi; Pradipta, Justin; Tamba, Tua Agustinus
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 3, No 1 (2012)
Publisher : Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (958.679 KB) | DOI: 10.14203/j.mev.2012.v3.39-48

Abstract

One essential parameter in fuel cell operation is oxygen excess ratio which describes comparison between reacted and supplied oxygen number in cathode. Oxygen excess ratio relates to fuel cell safety and lifetime. This paper explains development of air feed model and oxygen excess ratio calculation in commercial self-humidified PEM fuel cell system with 1 kW output power. This modelling was developed from measured data which was limited in open loop system. It was carried out to get relationship between oxygen excess ratio with stack output current and fan motor voltage. It generated fourth-order 56.26% best fit ARX linear polynomial model estimation (loss function = 0.0159, FPE = 0.0159) and second-order ARX nonlinear model estimation with 75 units of wavenet estimator with 84.95% best fit (loss function = 0.0139). The second-order ARX model linearization yielded 78.18% best fit (loss function = 0.0009, FPE = 0.0009).
Event-triggered robust formation control of multi quadrotors for transmission line inspection Tamba, Tua Agustinus; Cinun, Benedictus Christo Geroda; Nazaruddin, Yul Yunazwin; Romdlony, Muhammad Zakiyullah; Hu, Bin
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 15, No 2 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2024.1106

Abstract

This paper proposes an event-triggered formation control scheme to manage the operation of multiple quadrotors in performing the inspection of a power transmission line. In particular, the problem of controlling such multi quadrotors to track the tower and/or cables of the transmission lines is considered. A multi-agent sliding mode control method is used for this purpose and is equipped with both a radial basis function neural network as an estimator of environmental wind disturbances, as well as an event-triggered scheduling scheme for the control execution framework. The proposed multi quadrotors control method is designed by considering the transmission tower/cable as the reference sliding surface. Simulation results are presented to illustrate the effectiveness of the proposed multi quadrotors control scheme when implemented in a case scenario of tracking the commonly-encountered shape of transmission cables. Simulation results are presented and show how the implementation of a position error-based event-triggered control enables all UAVs to track the desired position and maintain a pre-determined formation. In particular, all UAVs can minimize the tracking error within 0.05 m after reaching the desired positions since the control signal is updated if the error reaches such an error bound.
Co-Authors Ali Sadiyoko AYEGA, IDHAM HANIF Bagus Arthaya Bin Hu Cinun, Benedictus Christo Geroda Darwin, Stevanus Dwi Putra, Ivan Edi Leksono Faruqi, Ismail Idham H. Ayega Justin Pradipta Justin S. Budiman Kamal, Md. Abdus Samad Khayr, Rashad Abul Muhammad Zakiyullah Romdlony Radifsya L. Desvabrahma Reysan, Jason Solaiman, Gabriela Waluya, Muhammad Brahma Widyotriatmo, Augie Yul Yunazwin Nazaruddin