A Comparative Study of Conventional and Fuzzy Logic Control of DC Drive with Power Factor Correction

Abstract

Power electronics circuits are the major part of the industry and so are the electrical drives. To control the electrical drives power electronics circuits are used dominantly. But there are some disadvantages of power electronics circuits, like mains current in an AC/DC converter contains periodic current pulses due to the action of rectifier and output filter capacitor. The high current peaks cause harmonic distortion of the supply current and low power factor. This results in poor power quality, voltage distortion, poor power factor at input AC mains, slowly varying rippled DC output at load end and low efficiency. So it is very important to improve the power factor of rectifier circuits, and it can be done by reducing the input current harmonics by using some filter or other techniques. In any of the control application, controller design is the most important part. There are different types of controller architectures available in control literature. The controller can be conventional in nature or can be intelligent in nature. The conventional controller doesn’t possess the human intelligence; where in the intelligent controller human intelligence is embed with the help of certain soft computing algorithms. After the design of controller is performed, the performance evaluation part comes in to light. The designed controller has to give optimal control results irrespective of every situation like plant and equipment non linearity, equipment saturation. So this dissertation looks in to performance evaluation of different conventional and intelligent controllers implemented with a clear objective to control the speed of DC motor including power factor improvement topology. First of all mathematical modeling of the process is performed. After the mathematical modeling the control objective is set and different kind of controllers are designed to meet the control objective. During the design of fuzzy based hybrid controller, the designer meets two key design challenges namely, optimization of existing fuzzy rule base and identification, estimation of new membership function or optimization of existing membership function. These issues play a vital role in controller design in real time.