Abstract:
Semiconductor technology has been developed rapidly during the decades which allows power electronic converters to be applied and installed in many different fields. In order to achieve a goal of deploying and controlling these kinds of converters effectively in real cases, it is necessary to analyze and develop mathematical models that can describe their dynamic and static behaviours. System parameters (e.g., inductance, capacitance) are needed among the most known models.
Besides, such kind of models does not take into account the discrete variance phenomenon in system parameters caused by external factors such as temperature changes. The project aims to take advantage of nonlinear system identification technology in order to solve these problems. This project will develop and apply particle swarm-based methods to identify nonlinear models for converters.
