ANALYSIS AND PERFORMANCE EVALUATION OF INTELLIGENT AND CONVENTIONAL CONTROLLERS

Abstract

The evolution of control systems engineering has introduced intelligent controllers as a potential advancement over conventional controllers, traditionally exemplified by Proportional-Integral-Derivative (PID) controllers. Intelligent controllers leverage artificial intelligence techniques to manage complex, nonlinear systems and adapt to dynamic conditions. This research provides a comprehensive analysis and evaluation of both intelligent and conventional controllers, aiming to determine their respective strengths and weaknesses. The study compares these controllers based on key performance metrics such as accuracy, stability, and error minimization. The findings of this research show that the error range for ANN is 0.198% to 0.234% while that of PID is from 0.396% to 0.791%, and the steady state behavior for ANN is smooth and stable, while PID has fluctuating behavior. it was shown that the ANN controller consistently has a lower percentage error compared to the PID controller in all test points. The average percentage error for the ANN controller is approximately 0.216%, while the PID controller’s average error is about 0.512%. The research aims to bridge the gap between theoretical advancements and practical implementations, fostering the adoption of intelligent control technologies where they are most beneficial.