| Summary: | This paper presents a hybrid model–based control algorithm that combines Model Predictive Control (MPC) and Sequential Action Control (SAC) deployed in a high-speed drive for Brushless DC (BLDC) motor by using a DC-DC converter with Gallium Nitride (GaN) switches. GaN FETs are selected because of their higher speed and lower power loss as compared with traditional Si switches. In the proposed framework, SAC processes the initial values of the control variables as well as their time of application and their duration in MPC loop. After receiving the underlying estimation of future contribution from SAC, MPC consolidates it with current input and predicts future control values by using the system state space model. This hybrid control conserves control effort and reduces sensitivity to initial conditions. In this way, converter’s output voltage is controlled to produce the reference speed at the motor output. National Instrument PXIe-6356 module is utilized as the interface between software and hardware that is a multi-function, LabVIEW-compatible data acquisition device. The viability of the proposed hybrid optimization for the high-speed drive is confirmed numerically by utilizing MATLAB/Simulink and approved experimentally using a Gallium Nitride (GaN) half-bridge DC-DC converter.
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