Control of buck-boost DC-DC converter with model reference neural controller.

The manuscript presents the synthesis of Buck-Boost DC-DC Converter control, based on the use of one of the most widespread techniques of artificial intelligence - neural networks. This is achieved by using a power circuit model based on the use of switching functions, thereby adequately modeling the behavior of the converter both during transients and in steady state operation. This implementation was done in the MATLAB/Simulink environment, which is very common among engineers, and almost all students have the necessary basic knowledge and competence to work with it. This approach is suitable for use both by new specialists who are being qualified and by established designers and engineers, as it significantly shortens the product development time. On the other hand, the implementation of a model-based approach for control synthesis enables tolerance analysis and robust analysis of devices. [ABSTRACT FROM AUTHOR]