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.

The difficulty in controlling the operation of the gantry crane (GC) is to face the complex phenomenon of the double pendulum. The oscillation of the hook (H) and the load (L) has reduced the working efficiency, reduced the ability to accurately position the trolley (T) and even caused mechanical damage and unsafe accidents. Therefore, the paper presents a solution to design a sliding mode controller (SMC) to control the gantry crane to reduce the oscillation of the hook and the load, and at the same time increase the ability to position the forklift. The coefficient k_s is optimized according to the fuzzy controller (FC). The stability of the system is proven by the Lyapunov stability theory, which has achieved the accuracy and durability of the entire control system. The sliding mode controller has been tested through MATLAB/Simulink simulation. The simulation results show that when using the sliding mode controller, the system has good control quality.