A Cascaded Quasi Z-Source Scheme Step up DC-DC Converter Using ANN Based Control

Modern renewable generation systems need smart and integrated power converters ensure for high efficiency of power conversion .This project intend s to the Artificial Neural Network (ANN) based cont rol step up DC-DC converter family with a cascaded Quasi Z-source network (qZS-scheme).The cascaded (two-stage) qZSnetwork could be derived by the adding of one diode , one inductor, and two capacitors to the tradition al single stage quasi-Z-source inverter (qZSI). The proposed cascad ed qZSI giving as same all the advantages of the tr aditional solution (voltage boost and buck functions in a sin gle stage, continuous input current ,and improved reliability).As compared to the conventional qZSI, the proposed sol ution reduces the shoot-through duty cycle at the s ame voltage boost factor ,and without adding additional switch es. The ANN based controller ensuring the better re sult compare to the conventional PI controller .The two-stage qZ SI in the shoot-through and non-shoot-through opera ting modes are described. The proposed and conventional closed loop results are compared.