Extended-State-Observer Based Model Predictive Control of a Hybrid Modular DC Transformer
| Autor: | Hang Zhang, Fei Xu, Cong Zhao, Ping Wang, Fanqiang Gao, Zixin Li, Yaohua Li |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | IEEE Transactions on Industrial Electronics. 69:1561-1572 |
| ISSN: | 1557-9948 0278-0046 |
| Popis: | Due to the power interaction between the phase-shifted dual active bridges (PSDABs) and series resonant dual active bridges (SRDABs) in the hybrid modular dc Transformer (HMDCT), it is difficulty to optimize current stress based on the transferred power. An extended-state-observer based model predictive control (ESO-MPC) strategy with the extended phase shift (EPS) is proposed to optimize the current stress of the PSDABs in the HMDCT. The MPC is employed to calculate the optimal transferred power of the PSDABs. Moreover, a first-order ESO is introduced to observe the uncertain output current of the PSDABs. Based on the calculated transferred power, the optimal phase-shifted duty ratios of each PSDAB under EPS, which achieves optimal current stress, are obtained by the Lagrange multiplier method. Because of the ESO-MPC strategy, it enables to achieve the current sensorless control of the HMDCT. Simulations on a four-cell 3kV/500V HMDCT and the extensive experiments of a downscale laboratory platform, using DSP OMPL138 -EZW + FPGA XC7A75T as the core controller, validate the feasibility of the proposed control strategy. |
| Databáze: | OpenAIRE |
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