Improvements in DC-DC Converters Using PID and Neural Network-Based Control Systems

Abstract

DC to DC converters are apparatuses that can save electrical power for transforming DC to specific voltage. It can act as necessitate element among systems that operate at distinct voltage levels across the car and other automotive vehicles. By gradually raising the engine’s Hp output, the controller’s known as PID can give back the measured speed to the required speed. A PID controller is added to the converter, which enhances dynamic response and lowers steady-state error. The integrated controller (KI) will reduce the steady-state error, while a derivative controller (KD) will improve the transient responsiveness. However, in large-signal domains with a boost converter, the convex PID doesn’t work as desired. For this, PID-NN can be proposed. The “PID-NN controller” is capable of effectively enhancing the rejection of possible voltage input fluctuations. Additionally, the “PID-NN controller” has been found to be more effective in controlling the output voltage. Hence, the current work has been proposed on the same for high power application of DC to DC converter based on PID-NN.