Adaptive fuzzy proportional integral derivative control for azimuth rotational positioning system

Abstract

This paper presents an adaptive fuzzy logic-based proportional integral derivative (PID) control strategy for an azimuth rotational positioning system characterized by nonlinear angular dynamics. Conventional fixed gain PID controllers often experience performance degradation when operating across varying error regions, resulting in slower responses and residual steady-state errors. To address this limitation, a region-based fuzzy gain scheduling mechanism is proposed to dynamically adjust the proportional (𝐾𝑝), integral (𝐾𝑖), and derivative (𝐾𝑑) gains according to the instantaneous angular error. The proposed controller is implemented on a laboratory-scale embedded platform consisting of a stepper motor actuator, potentiometer-based angular feedback, and an Arduino Nano controller. Experimental evaluations were conducted at reference angles of 45°, 90°, 135°, and 180° and compared with a conventional PID controller. Results demonstrate that the adaptive fuzzy–PID controller completely eliminates steady-state error at all tested setpoints and reduces rise time by up to 56.7%, depending on the operating condition. The adaptive gain adjustment enables faster transient response for large angular deviations while maintaining stable convergence near the setpoint. These findings demonstrate that the proposed embedded region-based adaptive fuzzy–PID approach provides an effective and practical solution for improving positioning accuracy and dynamic performance in rotational positioning systems.