APPLIED GENETIC ALGORITHM DESIGN DUAL PID CONTROLLERS TO CONTROL THE GANTRY CRANE FOR COPPER ELECTROLYSIS

Abstract

Gantry crane dedicated to copper electrolysis (CE) acts as a robot in factories to transport and assemble cathode and anode plates. Because the electrolyte panels are so thickly arranged that when the crane moves there is a great fluctuation resulting in inaccurate positioning, even causing unsafety. The article proposes to use dual PID controller with optimized parameters adjusted through genetic algorithm (GA) to control the gantry crane. The first PID controller controls the load oscillations, while the second PID controller controls the position of the crane. Dual PID controllers are tested through MATLAB/ Simulink simulations. Simulation results t_{_xlvt}  = 3.5 s, t__xlgx = 3.3 s, θ__max = 0.12 rad show that when using dual PID controllers quality better control when using a PID controller and when changing system parameters, interference impact on the system shows that the crane is still good quality control.