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Improving Control of SST using Type-2 Neuro-Fuzzy Controller with Elliptic Membership Function

As it is known, the most basic and important components in power systems are classical transformers which are passive interface between high voltage and low voltage systems. Classical transformers have undesirable characteristics such as poor voltage regulation, large size/weight and sensitivity to harmonics etc. In parallel with technological developments, solid state transformers (SSTs) which are considered to be one of the most indispensable components for future electrical energy systems, have attracted intense interest. In this paper, SST structure consisting of three stages is modeled in Matlab/Simulink environment. Type-2 Neuro-Fuzzy Controller (T2NFC) which has robust and adaptive structure is proposed for controlling of all stage of SST. In addition, the Elliptic Membership Function (MF) is used for T2NFC. The proposed controller is applied to SST structure and simulation studies are performed to verify the performance of the controller.