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Feasibility Study of Model Predictive Control for Grid-Connected Twisted Buck–Boost Inverter

Oleksandr Matiushkin, Oleksandr Husev, José Rodríguez, Héctor Young, Indrek Roasto

2021IEEE Transactions on Industrial Electronics24 citationsDOI

Abstract

This article studies the model predictive control (MPC) for a twisted buck–boost inverter based on unfolding circuit. The focus is on the practical implementation of the MPC algorithm for the microcontroller designed for application in power electronics. Selection of proper cost function parameters along with a continuous control set reduced prediction horizon, at the same time keeping good quality of the grid current. The results showed that simplified differential equations and a multicore microcontroller contribute to the sample time reduction, which in turn increases the sampling frequency with the corresponding increase in the output current quality. The simulation and experimental results confirmed theoretical predictions. In conclusion, the MPC technique suits for reducing zero-crossing distortion and in applications based on unfolding circuit.

Topics & Concepts

Model predictive controlControl theory (sociology)InverterMicrocontrollerComputer sciencePower electronicsGridSampling (signal processing)Buck converterPower (physics)Electronic engineeringEngineeringFilter (signal processing)Control (management)MathematicsElectrical engineeringVoltageComputer hardwarePhysicsArtificial intelligenceQuantum mechanicsComputer visionGeometryMultilevel Inverters and ConvertersMicrogrid Control and OptimizationAdvanced DC-DC Converters
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