Reduced-order Modelling of Level-Up DC-DC Converter Using TLBO Algorithm

The proposed research involves approximating a fifth-order SISO high-level DC-DC converter. This approximation is achieved by utilizing the Markov parameters (MPs) and time moments (TMs) of a higher-order system (HOS), as well as the MPs and TMs of a desired lower-order model (LOM). To facilitate this approximation process, the teaching-tearning-based optimization (TLBO) algorithm is employed. Firstly, MPs and TMs of intended LOM and HOS are obtained. The obtained MPs and TMs are used to build the objective-function. The designed OF seeks to reduce the error between MPs and TMs of higher-order (HO) converter system and its corresponding LOM. Further, objective-function is minimized to obtain unknown coefficients of intended lower-order (LO) converter model. Minimization of steady-state error is also ensured in this persistence process via steady-state matching. The Hurwitz stability criterion is employed to guarantee stability of LO converter model. The applicability and potency of the suggested methodology are supported by presenting responses, error indices and time-domain specifications.