Comparison Between Ziegler-Nichols and AMIGO Tuning Techniques in Automated Steering Control System for Autonomous Vehicle

Abstract

This paper presents the design of an automated steering control system with a PID controller for Autonomous Vehicle. It is mainly focusing on the implementation and evaluation of the tuning methods by using Ziegler-Nichols and Amigo in providing the important parameters to the PID controller namely, Kp, Ki, and Kd. The objectives of this project are to compare the performance of the Ziegler-Nichols and Amigo tuning method for the PID controller parameters to control the steering angle of the autonomous vehicle in real-time and to improve the vehicle steering dynamics performance. Both tuning methods are simulated in real-time in the laboratory by using a prototype buggy acts as the autonomous vehicle. It applies Raspberry Pi 3B+ as a controller, absolute encoder for feedback sensor, and Vexta brushless motor as the actuator. The system operates based on the input angle set by the user to turn the tire, which 0 degree is taken as the center of the turning point of this autonomous vehicle. When the set value is a positive number, the tire turns to the right. Otherwise, it turns to the left. As a result, the data without PID, using PID with Ziegler-Nichols and Amigo tuning methods are collected and plotted. It is found that the Amigo tuning method has a better response than the Ziegler-Nichols tuning method.