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Model Predictive Controller Design for Buck Converter in MATLAB

Model Predictive Controller Design for Buck Converter in MATLAB

Welcome to LMS Solutions. In today's session, we delve into the intricacies of implementing a Model Predictive Controller (MPC) for a Buck Converter using MATLAB. This simulation model demonstrates the design process, from determining the converter's parameters to implementing the controller for optimal performance.


Designing the Buck Converter:

The first step is to design the Buck Converter. Key parameters include power rating, input voltage, switching frequency, output voltage, and load resistance. MATLAB is employed to calculate inductor and capacitor values using relevant equations. The resulting values are utilized to build the Buck Converter simulation model in Simulink, incorporating components like a DC source, IGBT, diode, inductor, capacitor, and load resistor.

Identifying the Transfer Function:

To implement MPC, a transfer function model of the Buck Converter is needed. The simulation model captures input and output data using workspace blocks. This data is then imported into the System Identification Toolbox in MATLAB, where a transfer function model is estimated based on the collected data. The resulting transfer function is exported and integrated into the Simulink model.

Model Predictive Controller Implementation:

The MPC design process involves configuring the MPC block in Simulink. The plant output is connected to the MPC, and a reference command is set for the desired output voltage. A linear time-invariant system is defined, and the MPC block is designed based on the transfer function.

Simulation and Analysis:

The simulation involves introducing changes in reference commands to observe how the MPC-controlled Buck Converter responds. The MPC's ability to regulate the output voltage is evident in its response to step changes in the reference command. Through simulation, the MPC's effectiveness in maintaining stability and desired output voltage is showcased.

Conclusion:

The implementation of a Model Predictive Controller for a Buck Converter exemplifies advanced control strategies for power electronics. MATLAB and Simulink provide a robust environment for designing, simulating, and analyzing such systems. This tutorial has offered insights into the step-by-step process of designing and implementing an MPC for a Buck Converter.

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