International Journal of Science, Engineering and TechnologyAuthors: Asma Shibli, Dr Mohd Ilyas, Prof. Anwar Shahzad Siddiqui
Abstract: Precise control performance in dynamic and nonlinear systems remains a significant challenge for traditional PID controllers, primarily due to their fixed-gain nature and limited adaptability under varying operating conditions. This paper presents a fuzzy gain-scheduled PID tuning strategy that dynamically modifies the proportional, integral, and derivative gains based on real-time error and change in error using fuzzy logic inference. The proposed controller integrates the simplicity of a classical PID with the intelligent adaptability of fuzzy reasoning to enhance system stability, minimize overshoot, and accelerate transient response. A comparative performance evaluation is conducted against conventional tuning methods (Ziegler–Nichols and Cohen–Coon), fuzzy logic controllers, and optimization-based approaches (Genetic Algorithm and Particle Swarm Optimization) using standard control performance indices such as rise time, settling time, peak overshoot, steady-state error, and integral error metrics (IAE, ISE, ITAE). Simulation results validate that the proposed fuzzy gain scheduling method significantly improves dynamic performance and robustness while reducing steady-state error and control effort. The results demonstrate that the proposed approach offers an effective and computationally efficient tuning mechanism suitable for real-time applications in nonlinear and time-varying systems.
DOI: http://doi.org/10.5281/zenodo.17431856
