Designs of Particle-Swarm-Optimization-Based Intelligent PID Controllers and DC/DC Buck Converters for PEM Fuel-Cell-Powered Four-Wheeled Automated Guided Vehicle

Abstract

For automatic guided vehicles (AGVs), maximizing the operating time with maximum energy efficiency is the most important factor that increases work efficiency. In this study, the fuel-cell-powered AGV (FCAGV) system was modeled and optimized control and design were carried out to obtain high tracking performance with minimum power consumption. Firstly, a full mathematical model of FCAGV, which involves the AGV, the fuel cell, DC/DC converters and motors, was obtained. Then, particle swarm optimization (PSO)-based intelligent PID and I controllers were developed for maximizing the route-tracking performance of AGV and voltage-tracking performance of the DC/DC converter with reduced power consumption. PSO was used to determine the optimal parameters of controllers and the values of DC/DC converters' components. The performance of the full AGV system was analyzed for different paths. The results show that the sufficient path-tracking and voltage-tracking performance was obtained for AGV and DC/DC converters, respectively. The average tracking errors according to global coordinate system are 0.0061 m at the x axis, 0.0572 m at the y axis and 0.0228 rad at rotational axis. The obtained average voltage-tracking errors for each DC/DC converters were approximately 0.8033 V. These results indicate that the developed controllers with optimal coefficients work successfully with small voltage and path-tracking errors. During this motion, the average consumed power from the fuel cell was observed as 58.2675 W. These results show that the designed optimized intelligent controllers have sufficient performance with high energy efficiency and maximum route tracking.