Design Of Intelligent Controllers For Dc Dc Converters In Undergraduate Engineering Laboratory

The primary goal of this paper is to develop a vehicle through which undergraduate students may design smart controllers that employ artificial intelligence control tools. This goal can be achieved through the design and construction of intelligent (fuzzy-neural-network) controllers for dc-dc converter topologies, the design of an interface with particular emphasis on laboratory environment, and the design and testing of the different control topologies. The control structure integrates the ideas of fuzzy control system and neural network architecture into an intelligent process. The fuzzy control design is equipped with a learning algorithm to adjust the control angle (or duty ratio) so that the steady state error is minimized and a zero-voltage regulation is achieved. The student has the opportunity to assume the role of a control system designer, who is given the task of designing a cost effective yet flexible controller. The fundamentals governing the design, control and performance of the DC-DC converters are also illustrated. The entire system is built and tested in the laboratory by using off-the-shelf components and software. A comprehensive analysis of the principle of operation, design consideration and experimental implementation of the converter topologies with built-in intelligent controller is developed. A rapid response is expected when the proposed controller is actually implemented in a real-time mode.