Multistep Finite Control Set Model Predictive Control for Power Electronics

Geyer, Tobias; Quevedo, Daniel E.

doi:10.1109/tpel.2014.2306939

Cited by 329 publications

(222 citation statements)

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“…The lines to neutral voltages are transformed from abc into αβγ coordinates by using Equation (17). The results of the transformation are shown in Table 2.…”

Section: Near State Vector Selection-based Model Predictive Controlmentioning

confidence: 99%

Near State Vector Selection-Based Model Predictive Control with Common Mode Voltage Mitigation for a Three-Phase Four-Leg Inverter

et al. 2017

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Abstract:A high computational burden is required in conventional model predictive control, as all of the voltage vectors of a power inverter are used to predict the future behavior of the system. Apart from that, the common mode voltage (CMV) of a three-phase four-leg inverter utilizes up to half of the DC-link voltage due to the use of all of the available voltage vectors. Thus, this paper proposes a near state vector selection-based model predictive control (NSV-MPC) scheme to mitigate the CMV and reduce computational burden. In the proposed technique, only six active voltage vectors are used in the predictive model, and the vectors are selected based on the position of the future reference vector. In every sampling period, the position of the reference current is used to detect the voltage vectors surrounding the reference voltage vector. Besides the six active vectors, one of the zero vectors is also used. The proposed technique is compared with the conventional control scheme in terms of execution time, CMV variation, and load current ripple in both simulation and an experimental setup. The LabVIEW Field programmable gate array rapid prototyping controller is used to validate the proposed control scheme experimentally, and demonstrate that the CMV can be bounded within one-fourth of the DC-link voltage.Keywords: near state vector selection based model predictive control; common mode voltage; ripple content; execution time; computational burden and three phase four leg inverter

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“…The lines to neutral voltages are transformed from abc into αβγ coordinates by using Equation (17). The results of the transformation are shown in Table 2.…”

Section: Near State Vector Selection-based Model Predictive Controlmentioning

confidence: 99%

Near State Vector Selection-Based Model Predictive Control with Common Mode Voltage Mitigation for a Three-Phase Four-Leg Inverter

et al. 2017

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“…Let μ u (t) be the modulation function defined in (18). This modulation function represents the number of modules inserted in the upper arm and takes integer values between 0 and N .…”

Section: Lemma 1 Consider the MMC Model Described Inmentioning

confidence: 99%

“…The computational time can also be reduced by using a restricted control set[12], or sphere decoding methods[18],[19].…”

mentioning

confidence: 99%

Reference design for predictive control of modular multilevel converters

Prades

Quevedo

Aguilera

et al. 2014

2014 4th Australian Control Conference (AUCC)

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This paper proposes a reference design technique for the control of Modular Multilevel Converters. Assuming balanced operation, a reduced-order model for the power converter is developed and its state trajectories are characterized in closed form. This allows one to specify desired references for the current and voltage at the load, and also for the circulating current and capacitor voltages in the converter. A simulation study using finite-set constrained predictive control illustrates advantages of the proposed method.

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“…The previously mentioned FCS-MPC strategies were based on one-sample-ahead prediction to simplify the modeling and analysis. The works in [20][21][22] proposed longer prediction horizons to improve the control performance in a three phase converter. The questions about the complexity of the controller, the increase in the number of calculations, the computational burden, and potential improvements in the performance of the converter are still a research topic in the field of FCS-MPC.…”

Section: Introductionmentioning

confidence: 99%