Design and optimization of a fuzzy-pid controller using a genetic algorithm for overhead crane control

Abstract

An overhead crane (OC) is an electromechanical system with nonlinear dynamics and is significantly affected by load oscillations (LO), which are commonly modeled as a double-pendulum (D-P) system. Oscillations (O) of the hook and payload (H&P) degrade trolley (T) positioning (P) accuracy and may lead to mechanical damage and safety hazards. To mitigate these limitations, a combined FLC–PID control scheme is introduced with the aim of improving the operational performance of an OC. In the proposed scheme, the fuzzy controller enhances the system’s dynamic response under large tracking errors, thereby ensuring fast positioning of the T at the desired location. The PID controller ensures system stability as the T approaches the setpoint, employing a genetic algorithm (GA) to optimize parameters for oscillation suppression and P accuracy enhancement. The effectiveness of the proposed approach is validated through MATLAB/Simulink simulations. Simulation results demonstrate improved P accuracy, significant reduction of H&P O, and fast, stable system responses.