ADAPTIVE FUZZY LOGIC–BASED SELF-TUNING PID CONTROLLER FOR NONLINEAR SYSTEMS

Abstract

Proportional–Integral–Derivative (PID) controllers remain the most widely implemented control strategy in industrial automation due to their simplicity and reliability. However, fixed-gain PID controllers exhibit performance degradation in nonlinear, time-varying,

and uncertain systems. This paper proposes an adaptive self-tuning PID controller based on fuzzy logic to dynamically adjust controller gains in real time. The proposed method utilizes error and change in error as linguistic inputs to generate incremental tuning parameters for KpKp​, KiKi​, and KdKd​. Comparative simulation analysis demonstrates that the proposed controller significantly reduces overshoot, improves settling time, enhances disturbance rejection, and increases robustness compared to classical Ziegler–Nichols tuned PID controllers. The results validate the effectiveness of fuzzy-based adaptive tuning for nonlinear control applications.