Improving the Performance of Buck Converter PID Controller using Genetic Algorithm 2013-01-2874
DC/DC converters are switching regulator specially used for voltage level conversion application, and one of crucial entity for fuel cell. In absence of which fuel cell real world application is difficult to conceive. Numerous works have been contributed using PID controller to regulate the output voltage and improve DC/DC converter dynamic performance. Due to switching operation, nonlinearity causes complexity in DC/DC converter control. In present article, PID controller optimization for a DC/DC buck converter is devised specifically for fuel cell application. Linearization and averaging technique is employed to generate State Space Average Model (SSAM) of DC/DC buck converter. PID controller weight factor's reference value i.e. Kp, Ki and Kd are selected based on values obtained by traditional Ziegler-Nichols method. Fine-tuning of PID weight factors are accomplished using Genetic Algorithm. Based on system step response suitable performance-measuring function has been selected, for Genetic Algorithm. Finally, tuned PID controller is applied to the DC/DC buck converter circuit model in consideration of fuel cell. All the simulation and optimization have been completed using MATLAB/SIMULINK. Result of simulation shows the much-improved dynamic performance of DC/DC buck converter with proposed method compare to traditional method.