Published: 2024-12-01
Implementation of the Sugeno Fuzzy Method in a Firefighting Robot Prototype with an All-Wheel Drive System
DOI: 10.35870/ijsecs.v4i3.3217
Downloads
Abstract
The purpose of this study is how to implement the Fuzzy Sugeno method to a fire-fighting robot prototype with all wheel drive system. Resculpts by transferring academic input to specific fields of knowledge, as many problems have become increasingly adaptable due to technology or the growth of AI, which is fast becoming the dominant productivity tool. Fuzzy method is a mathematical method used to overcome the problems of small uncertainties and imprecision. The first prototype of the fire-fighting robot which will be able to use all-wheel drive system is meant to mitigate the risk of large fire and to detect as soon as possible. Observational results verify that the Robot prototype follows its intended workflow as well as can complete its mission to both detect and eliminate fire hazards. The speed of the wheel is controlled on three levels slow (0 RPM), moderate (50 RPM), and fast (100 RPM) using Fuzzy Sugeno method. Also, in response time is set by using Fuzzy Sugeno method which is set to 1 second, 2 seconds, and 3 seconds
Keywords
Robotics ; Fuzzy Sugeno Method ; Robot Prototype ; Fire-Fighting ; All-Wheel Drive System
Article Information
This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
-
Issue: Vol. 4 No. 3 (2024)
-
Section: Articles
-
Published: %750 %e, %2024
-
License: CC BY 4.0
-
Copyright: © 2024 Authors
-
DOI: 10.35870/ijsecs.v4i3.3217
AI Research Hub
This article is indexed and available through various AI-powered research tools and citation platforms. Our AI Research Hub ensures that scholarly work is discoverable, accessible, and easily integrated into the global research ecosystem. By leveraging artificial intelligence for indexing, recommendation, and citation analysis, we enhance the visibility and impact of published research.
Sutarmin
Informatics Engineering Study Program, Faculty of Science and Technology, Universitas Panca Sakti Bekasi, Bekasi City, West Java Province, Indonesia
Ajar Rohmanu
Informatics Engineering Study Program, Faculty of Science and Technology, Universitas Panca Sakti Bekasi, Bekasi City, West Java Province, Indonesia
Endang
Informatics Engineering Study Program, Faculty of Science and Technology, Universitas Panca Sakti Bekasi, Bekasi City, West Java Province, Indonesia
-
Abdullah, M. S., Priatna, R. R., Abdullah, M. S., Maulana, M. I., Yusuf, M., & Rosyani, P. (2023). Robotika dalam manufaktur: Kecerdasan buatan mengantarkan otomatisasi dan kolaborasi manusia-robot ke tingkat yang nyata. Biikma Bul. Ilm. Ilmu Komput. Dan Multimed., 1(1), 29–32.
-
Nasution, H. (2020). Implementasi logika fuzzy pada sistem kecerdasan buatan. Elkha J. Tek. Elektro, 4(2), 4–8.
-
Kurniawan, A., Irawan, B. H., & Prihadi, D. (2023). Pendekatan fuzzy logic dalam perhitungan harga rental truck crane. Jurnal JTIK (Jurnal Teknologi Informasi Dan Komunikasi), 7(4), 724–733. https://doi.org/10.35870/jtik.v7i4.1759
-
Tundo, Sodik, Setiawan, K., & Aula, R. F. (2024). Penerapan IoT dengan algoritma fuzzy dan mikrokontroler ESP32 dalam monitoring penyiraman. Jurnal Indonesia: Manajemen Informatika Dan Komunikasi, 5(3), 2915–2924. https://doi.org/10.35870/jimik.v5i3.977
-
Shema, D. I. (2022). Implementasi metode logika fuzzy Sugeno pada prototipe robot pemadam api dengan kemampuan navigasi. J. Teknol. Elektro, 13(1), 55. https://doi.org/10.22441/Jte.2022.V13i1.010
-
Abdul Kadir, E., Syafitri, N., Dedikarni, & Dwi Fikri, T. B. (2023). Pelatihan dasar Arduino untuk robotika cerdas dengan penerapan teknologi kecerdasan buatan untuk sekolah menengah. J. Pengabdi. Masy. Dan Penerapan Ilmu Pengetah., 4(2), 22–28. https://doi.org/10.25299/Jpmpip.2023.14848
-
Sumiati, S., Desmira, D., & Sasongko, S. (2017). Prototype robot pemadam api menggunakan fuzzy inference systems berbasis mikrokontroler AVR Atmega328. Ethos (Jurnal Penelit. Dan Pengabdian), 5(2), 186. https://doi.org/10.29313/Ethos.V5i2.2360
-
Mahasiswa, D. D. A. N., Panca, U., & Bekasi, S. (2024). Panduan penelitian bersama dosen dan mahasiswa. No. 54.
-
I.-M. S. Diskrit, & Undefined (2009). Pembuatan robot sebagai aplikasi kecerdasan buatan. Informatika.Stei.Itb.Ac.Id, 4(2), 2012
-
Darmanto, I. A. (2020). Inovasi sistem robotika pada perpustakaan. Jeecom J. Electr. Eng. Comput., 2(2), 13–16. https://doi.org/10.33650/Jeecom.V2i2.1185
-
Hartono, R., & Firdaus, G. A. (2018). Implementation of intelligent fire extinguisher robots with multi-independent steering. Telekontran J. Ilm. Telekomun. Kendali Dan Elektron. Terap., 6(2), 35–46. https://doi.org/10.34010/Telekontran.V6i2.3798
-
Widiantama, O. (2017). Pengembangan trainer sistem kendali kecepatan motor DC sebagai media pembelajaran praktik robotika. E-Journal Univ. Negeri Yogyakarta, 7(2), 188–196.
-
Syariah, K. B., & Ilmu, G. (2016). Rancang bangun robot pengambil objek bawah air. No. September, 1–6.
-
Dewi, A. O. P. (2020). Kecerdasan buatan sebagai konsep baru pada perpustakaan. Anuva J. Kaji. Budaya, Perpustakaan, Dan Inf., 4(4), 453–460. https://doi.org/10.14710/Anuva.4.4.453-460
-
Safarudin, M., & Patah, A. (2020). Pengembangan purwarupa robot pemadam api dengan kendali berbasis mikrokontroler. Isu Teknol. Stt Mandala, 15(2), 92–98.
-
Vafamand, N. (2020). Global non-quadratic Lyapunov-based stabilization of T–S fuzzy systems: A descriptor approach. Journal of Vibration and Control, 26(19-20), 1765–1778. https://doi.org/10.1177/1077546320904817
-
Chiu, C., & Peng, Y. (2019). Design of Takagi-Sugeno fuzzy control scheme for real-world system control. Sustainability, 11(14), 3855. https://doi.org/10.3390/su11143855
-
Aji, B. (2023). Fuzzy logic algorithm of Sugeno method for controlling line follower mobile robot. Ilkom Jurnal Ilmiah, 15(2), 283–289. https://doi.org/10.33096/ilkom.v15i2.1558.283-289
-
Sofyan, Y., Ihsan, M., & Fitriani, S. (2023). Pengontrolan robot bulu tangkis menggunakan mikrokontroler Atmega128 berbasis Android mobile. J. Comput. Syst. Informatics, 4(3), 501–510. https://doi.org/10.47065/Josyc.V4i3.3527
-
Chiu, C., Hung, Y., & Peng, Y. (2021). Design of a decoupling fuzzy control scheme for omnidirectional inverted pendulum real-world control. IEEE Access, 9, 26083-26092. https://doi.org/10.1109/access.2021.3057658
-
Nikmah, Y. M. (2022). Implementasi program ekstrakurikuler robotika dalam meningkatkan kreativitas siswa di MI Progresif Bumi Shalawat Tulangan Sidoarjo (Undergraduate thesis, Universitas Islam Negeri Sunan Ampel Surabaya).
-
Enemegio, R., Jurado, F., & Villanueva-Tavira, J. (2024). Experimental Evaluation of a Takagi–Sugeno Fuzzy Controller for an EV3 Ballbot System. Applied Sciences, 14(10), 4103. https://doi.org/10.20944/preprints202312.0558.v1
-
Beyhan, S., Lendek, Z., Babuska, R., Wisse, M., & Alci, M. (2011). Adaptive fuzzy and sliding-mode control of a robot manipulator with varying payload. https://doi.org/10.1109/cdc.2011.6160802
-
Morsy, H., El-Khatib, M., Hussein, W., & Mahgoub, M. (2012). Investigation of modern control algorithms in mechatronic systems. The International Conference on Applied Mechanics and Mechanical Engineering, 15(15), 1-20. https://doi.org/10.21608/amme.2012.37057.
-
Adamu, E., Afolayan, M., Umaru, S., & Garba, D. (2018). The modelling and control of the drive system of an Ackermann robot using GA optimization. Nigerian Journal of Technology, 37(4), 1008. https://doi.org/10.4314/njt.v37i4.21
-
Aguilar, A., Pérez-Patricio, M., Camas, J., Hernandez, H., & Ríos, C. (2014). Efficient design and implementation of a multivariate Takagi-Sugeno fuzzy controller on an FPGA. https://doi.org/10.1109/icmeae.2014.8
-
Zhang, J., Wang, X., & Shao, X. (2020). Design and real-time implementation of Takagi–Sugeno fuzzy controller for magnetic levitation ball system. IEEE Access, 8, 38221-38228. https://doi.org/10.1109/access.2020.2971631.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with this journal agree to the following terms:
1. Copyright Retention and Open Access License
Authors retain copyright of their work and grant the journal non-exclusive right of first publication under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
This license allows unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
2. Rights Granted Under CC BY 4.0
Under this license, readers are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, including commercial use
- No additional restrictions — the licensor cannot revoke these freedoms as long as license terms are followed
3. Attribution Requirements
All uses must include:
- Proper citation of the original work
- Link to the Creative Commons license
- Indication if changes were made to the original work
- No suggestion that the licensor endorses the user or their use
4. Additional Distribution Rights
Authors may:
- Deposit the published version in institutional repositories
- Share through academic social networks
- Include in books, monographs, or other publications
- Post on personal or institutional websites
Requirement: All additional distributions must maintain the CC BY 4.0 license and proper attribution.
5. Self-Archiving and Pre-Print Sharing
Authors are encouraged to:
- Share pre-prints and post-prints online
- Deposit in subject-specific repositories (e.g., arXiv, bioRxiv)
- Engage in scholarly communication throughout the publication process
6. Open Access Commitment
This journal provides immediate open access to all content, supporting the global exchange of knowledge without financial, legal, or technical barriers.