Araştırma Makalesi

Fuzzy Decision Based Modeling of Rheostatic Brake System for Autonomous Land Vehicles

Cilt: IDAP-2022 : International Artificial Intelligence and Data Processing Symposium 10 Ekim 2022
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Fuzzy Decision Based Modeling of Rheostatic Brake System for Autonomous Land Vehicles

Öz

The most fundamental characteristic of autonomous vehicles (AVs) is their autonomy. However, due to the dynamic operating environment of the vehicle, their control algorithms may make imprecise, approximate, and unreliable decisions. Therefore, there is a need for the creation of more robust driving algorithms, notably consistent obstacle avoidance algorithms. Occasionally, the vehicle must come to a complete stop in order to avoid obstacles. In this situation, the engine brake control of the car can be engaged. In this study, a fuzzy model was proposed to effectively brake autonomous land vehicles, with an electrical braking system known as rheostatic braking. Since a rheostatic braking system (RBS) is employed, the input values of the fuzzy controller for this designed modeling are vehicle speed and ground slipperiness, and the output value is the rheostat resistance value. In the developed fuzzy controller, Mamdani inference and Aggregation methods were utilized. In addition to these two methods, the fuzzy controller also provides the output of the centroid, bisector, average of the maximum, smallest of the maximum and largest of the maximum sharpening methods to the user. Finally, using the Python programming language and the Tkinter library, the graphical user interface displays the linguistic expression and membership degree of the user's inputs, the final fuzzy output graph, and the exact outputs from all clarification methods (GUI).

Anahtar Kelimeler

Kaynakça

  1. Bao, D. Q., & Zelinka, I. (2019). Obstacle avoidance for swarm robot based on self-organizing migrating algorithm. Procedia Computer Science, 150, 425–432.
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  3. Chen, X., & Li, Y. (2006). Smooth path planning of a mobile robot using stochastic particle swarm optimization. 2006 International Conference on Mechatronics and Automation, 1722–1727.
  4. Chengqing, L., Ang, M. H., Krishnan, H., & Yong, L. S. (2000). Virtual obstacle concept for local-minimum-recovery in potential-field based navigation. Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No. 00CH37065), 2, 983–988.
  5. Engedy, I., & Horváth, G. (2009). Artificial neural network based mobile robot navigation. 2009 IEEE International Symposium on Intelligent Signal Processing, 241–246.
  6. Godfrey, A. J., & Sankaranarayanan, V. (2018). A new electric braking system with energy regeneration for a BLDC motor driven electric vehicle. Engineering Science and Technology, an International Journal, 21(4), 704–713.
  7. Günay, M., Korkmaz, M. E., & Özmen, R. (2020). An investigation on braking systems used in railway vehicles. Engineering Science and Technology, an International Journal, 23(2), 421–431.
  8. Kadlec, P., & Raida, Z. (2011). A Novel Multi-Objective Self-Organizing Migrating Algorithm. Radioengineering, 20(4).

Ayrıntılar

Birincil Dil

İngilizce

Konular

Yapay Zeka, Yazılım Mühendisliği (Diğer), Kontrol Mühendisliği, Mekatronik ve Robotik

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

10 Ekim 2022

Gönderilme Tarihi

11 Eylül 2022

Kabul Tarihi

16 Eylül 2022

Yayımlandığı Sayı

Yıl 2022 Cilt: IDAP-2022 : International Artificial Intelligence and Data Processing Symposium

Kaynak Göster

APA
Sünkün, S., Parlak, B. O., Yıldırım, A., & Yavaşoğlu, H. A. (2022). Fuzzy Decision Based Modeling of Rheostatic Brake System for Autonomous Land Vehicles. Computer Science, IDAP-2022 : International Artificial Intelligence and Data Processing Symposium, 144-150. https://doi.org/10.53070/bbd.1173849
AMA
1.Sünkün S, Parlak BO, Yıldırım A, Yavaşoğlu HA. Fuzzy Decision Based Modeling of Rheostatic Brake System for Autonomous Land Vehicles. JCS. 2022;IDAP-2022 : International Artificial Intelligence and Data Processing Symposium:144-150. doi:10.53070/bbd.1173849
Chicago
Sünkün, Semir, Berke Oğulcan Parlak, Alper Yıldırım, ve Hüseyin Ayhan Yavaşoğlu. 2022. “Fuzzy Decision Based Modeling of Rheostatic Brake System for Autonomous Land Vehicles”. Computer Science IDAP-2022 : International Artificial Intelligence and Data Processing Symposium (Ekim): 144-50. https://doi.org/10.53070/bbd.1173849.
EndNote
Sünkün S, Parlak BO, Yıldırım A, Yavaşoğlu HA (01 Ekim 2022) Fuzzy Decision Based Modeling of Rheostatic Brake System for Autonomous Land Vehicles. Computer Science IDAP-2022 : International Artificial Intelligence and Data Processing Symposium 144–150.
IEEE
[1]S. Sünkün, B. O. Parlak, A. Yıldırım, ve H. A. Yavaşoğlu, “Fuzzy Decision Based Modeling of Rheostatic Brake System for Autonomous Land Vehicles”, JCS, c. IDAP-2022 : International Artificial Intelligence and Data Processing Symposium, ss. 144–150, Eki. 2022, doi: 10.53070/bbd.1173849.
ISNAD
Sünkün, Semir - Parlak, Berke Oğulcan - Yıldırım, Alper - Yavaşoğlu, Hüseyin Ayhan. “Fuzzy Decision Based Modeling of Rheostatic Brake System for Autonomous Land Vehicles”. Computer Science IDAP-2022 : INTERNATIONAL ARTIFICIAL INTELLIGENCE AND DATA PROCESSING SYMPOSIUM (01 Ekim 2022): 144-150. https://doi.org/10.53070/bbd.1173849.
JAMA
1.Sünkün S, Parlak BO, Yıldırım A, Yavaşoğlu HA. Fuzzy Decision Based Modeling of Rheostatic Brake System for Autonomous Land Vehicles. JCS. 2022;IDAP-2022 : International Artificial Intelligence and Data Processing Symposium:144–150.
MLA
Sünkün, Semir, vd. “Fuzzy Decision Based Modeling of Rheostatic Brake System for Autonomous Land Vehicles”. Computer Science, c. IDAP-2022 : International Artificial Intelligence and Data Processing Symposium, Ekim 2022, ss. 144-50, doi:10.53070/bbd.1173849.
Vancouver
1.Semir Sünkün, Berke Oğulcan Parlak, Alper Yıldırım, Hüseyin Ayhan Yavaşoğlu. Fuzzy Decision Based Modeling of Rheostatic Brake System for Autonomous Land Vehicles. JCS. 01 Ekim 2022;IDAP-2022 : International Artificial Intelligence and Data Processing Symposium:144-50. doi:10.53070/bbd.1173849

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