DESAIN STEERING CONTROL PADA AUTONOMOUS VEHICLE MENGGUNAKAN METODE IMPROVED SWERVE DRIVE BERBASIS ALGORITMA FUZZY LOGIC TYPE-1

ALPIAN, BADAR and Suprapto, Bhakti Yudho (2025) DESAIN STEERING CONTROL PADA AUTONOMOUS VEHICLE MENGGUNAKAN METODE IMPROVED SWERVE DRIVE BERBASIS ALGORITMA FUZZY LOGIC TYPE-1. Undergraduate thesis, Sriwijaya University.

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Abstract

This research presents the design and implementation of a steering control system for an Autonomous Electric Vehicle (AEV) using the Improved Swerve Drive method based on a Type-1 Fuzzy logic algorithm. The system is developed to enhance vehicle maneuverability and stability under various operational conditions. Structural analysis of the vehicle frame was conducted using SolidWorks, and the results indicate that the mechanical design can withstand loads up to 8000 N with a maximum stress of 19.454 MPa—well below the yield strength of Alloy Steel at 620.422 MPa—and a deformation of only 0.119 mm, demonstrating structural safety. The fuzzy control system was tested through MATLAB simulations using 3, 5, and 7 membership functions. The results show that the configuration with seven membership functions delivers the best performance, achieving an overshoot of 7.33% and a steady-state error of 0.0324, outperforming both other fuzzy configurations and conventional PID control. Real-time prototype testing was carried out across five scenarios: straight path, 90° turning, parallel parking, obstacle avoidance, and in-place maneuvering. The fuzzy 7-MF controller consistently demonstrated fast, precise, and adaptive responses, while the PID controller exhibited limitations in dynamic environments. The findings indicate that the Type-1 Fuzzy logic algorithm with seven membership functions, applied to an Improved Swerve Drive system, effectively enhances the accuracy and efficiency of steering control in autonomous vehicles. This system shows strong potential for further development at full scale, with the integration of visual sensors and closed-loop control for real-world application.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Autonomous Electric Vehicle (AEV), Steering Control, Improved Swerve Drive, Fuzzy logic Type-1
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1-9971 Electrical engineering. Electronics. Nuclear engineering > TK1 Electrical engineering--Periodicals. Automatic control--Periodicals. Computer science--Periodicals. Information technology--Periodicals. Automatic control. Computer science. Electrical engineering. Information technology.
Divisions:	03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User:	Badar Alpian
Date Deposited:	03 Sep 2025 01:45
Last Modified:	03 Sep 2025 01:45
URI:	http://repository.unsri.ac.id/id/eprint/183448

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