Data driven identification and current control on dual active bridge systems for low power applications
Arroyo, Jesus(1); Tafur, Julio(1); Sal y Rosas, Damian(2) 1. Control and Automation Engineering Master Degree Program, Pontificia Universidad Catolica del Peru, San Miguel, Lima (Peru). 2. LAAS-CNRS, University of Toulouse, 31031 Toulouse, France 2026-06-27

Abstract

This work presents a data-driven methodology for the identification and control of Dual Active Bridge (DAB) DC–DC converters, aimed at reducing the complexity associated with highly nonlinear analytical models. By exploiting an angle phase-shift representation instead of a detailed PWM-based model, the proposed approach simplifies both system excitation and identification while preserving the essential power-transfer dynamics of the converter. A frequency-domain control strategy is subsequently developed based on the identified model, enabling systematic loop-shaping and robust controller design. The resulting discrete-time controller achieves accurate reference tracking and stable regulation in simulation tests, demonstrating that the proposed pipeline provides an effective and practical alternative to conventional model-based control approaches for DAB systems

Key words: System identification, non lineal systems, dual active bridge, data-driven control.

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