Robust Continuous Control Set Model Predictive Control in Synchronous Reference Frame for Grid-Tied Inverters

Zamani, Hasan; Abbaszadeh, Karim; Gyselinck, Johan; Karimi, Mohammadhadi

doi:10.1109/jestie.2022.3183474

IEEE J. Emerg. Sel. Top. Ind. Electron.

2023

DOI: 10.1109/jestie.2022.3183474

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Robust Continuous Control Set Model Predictive Control in Synchronous Reference Frame for Grid-Tied Inverters

Hasan Zamani

Karim Abbaszadeh

Johan Gyselinck

et al.

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2024

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Cited by 2 publications

(2 citation statements)

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“…The first group, which is called finite-control-set-MPC (FCS-MPC) solves an optimization problem in real time by considering the limited numbers of switching states of a power converter [15], [16], [17]. FCS-MPC has an excellent performance, which can be implemented for linear or nonlinear systems, but it does not remove the need for AD or PD [17], [18].…”

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confidence: 99%

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Adaptive Model Predictive Control for LCL-Filter Grid-Tied Inverters

Zamani,

Abbaszadeh,

Karimi

et al. 2024

IEEE Trans. Ind. Electron.

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This article proposes adaptive continuouscontrol-set model predictive control (CCS-MPC) for threephase LCL-filter grid-tied inverters in the stationary frame. The proposed control provides stability against the LCLfilter resonance and removes the need for active damping or passive damping. Furthermore, it can track sinusoidal references in the stationary frame close to zero offsets. Inductance variation of a grid is a challenging issue, which can shift the LCL-filter resonance. Even though CCS-MPC generally has good stability for parameter mismatches, the control is optimized for the nominal value of the parameters. A relatively large variation may deteriorate the performance of the control and cause instability in the closed-loop system. To solve this problem, the concept of CCS-MPC is developed to work with a variety of the gridinductance changes. The controller coefficients are chosen with a sensitivity analysis to provide enough gain margins and phase margins for the whole interval of the presumption grid-inductance variation. Also, this selection guarantees the control robustness against mismatches of the LCL-filter capacitance and inductance. The real-time computation of advanced controllers is a challenging issue. The computation burden of the proposed CCS-MPC is mostly performed offline and just some simple numerical expression is executed in real time. Thus, it does not require a powerful but expensive processor for implementation. The simulation and experimental results prove the performance of the proposed controller for handling the LCL-filter resonance, grid-inductance variations, and tracking sinusoidal references.

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“…The other feature of CCS-MPC relies on its ability to track sinusoidal references in the stationary frame. The control is designed in the stationary frame because in the synchronous frame there are heavy cross-coupling terms between the dq axes and the order of the model is larger [18].…”

mentioning

confidence: 99%

Adaptive Model Predictive Control for LCL-Filter Grid-Tied Inverters

Zamani,

Abbaszadeh,

Karimi

et al. 2024

IEEE Trans. Ind. Electron.

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Model Predictive Control With Stability Guarantee for Second-Order DC/DC Converters

Garcés

Riffo

González-Castaño

et al. 2024

IEEE Trans. Ind. Electron.

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Robust Continuous Control Set Model Predictive Control in Synchronous Reference Frame for Grid-Tied Inverters

Cited by 2 publications

References 31 publications

Adaptive Model Predictive Control for LCL-Filter Grid-Tied Inverters

Adaptive Model Predictive Control for LCL-Filter Grid-Tied Inverters

Model Predictive Control With Stability Guarantee for Second-Order DC/DC Converters

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