A Neural Network-based Model Reference Adaptive Control of Dual Active Bridge Converter for Multi-Phase Shift Modulation

This paper introduces a model reference adaptive control (MRAC) method based on neutral network approximation for dual active bridge (DAB) dc-dc converter. The nonlinear models of the DAB converter are developed for single phase shift (SPS), dual phase shift (DPS), and triple phase shift (TPS) modulation using the harmonic approximation of the switching waveforms. Then, neural network-based adaptive laws and control laws are established which can provide robust control performance and deal with uncertainties of the system. The control method is simulated in Matlab/Simulink and the simulation results demonstrate that the controller tracks the reference voltage effectively while rejecting the disturbance from the source and load side within a very short time.