Improvement of Robustness of MPC Adding Repetitive Behavior for the DFIG Current Control

D., Eliomar R. Conde; Lunardi, Angelo; Chaves, Juan Sebastián Solís; Paiva, Tiago dos S.; Fernandes, Darlan A.; Filho, Alfeu J. Sguarezi

doi:10.3390/en15114114

Cited by 6 publications

(7 citation statements)

References 48 publications

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“…In this case, the idea behind the definition of the component ⃗ v f b is to express it as a function of the variation of the stator current vector due to the errors associated with the plant parameters. So, ⃗ v f b using ( 12) is defined in (13).…”

Section: Table 1 Switching States and Voltage Vectors Of Vsimentioning

confidence: 99%

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Robust Finite Control Set Model Predictive Current Control for Induction Motor Using Deadbeat Approach in Stationary Frame

et al. 2023

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The model predictive control increased its prominence in the field of induction machine drives. However, the performance of this strategy depends on the accuracy of the machine model parameters. In order to overcome this deficiency, this paper proposes a robust model predictive current control employing indirect field-oriented control in stationary reference frame using the stator current and the rotor flux vectors as state and stator voltage vector as the input. The control algorithm combines the classical model predictive control with the deadbeat approach in order to calculate the applied stator voltage vector in two components: one element considers the stator current reference, and another employs the disturbances caused due to the parameter errors, which allows to compensate the parameter mismatches in the plant model. The minimized cost function employs the predicted stator voltage vector to select the voltage vector to be applied to the stator terminals of the motor. The control method performance was verified using an experimental test bench analyzing the system steady-state and dynamic actions. In this way, the results corroborate the proposed controller robustness against parametric variations.

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Section: Table 1 Switching States and Voltage Vectors Of Vsimentioning

confidence: 99%

“…Recently, some MPC strategies have been proposed in order to increase the robustness against parameters mismatch of the machines as presented in [10]- [13]. In [14], the ordinary MPC employs the nonlinear model considering the taylor representation of IM for each equilibrium point.…”

Section: Introductionmentioning

confidence: 99%

Robust Finite Control Set Model Predictive Current Control for Induction Motor Using Deadbeat Approach in Stationary Frame

et al. 2023

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“…O cálculo de ⃗ v f b (k) é realizado usando (8) com um período de amostragem de atraso, conforme mostrado em (10).…”

Section: Tabela I Estados De Comutação E Vetores Tensão Do Vsiunclassified

“…Recentemente, algumas estratégias de MPC foram propostas para aumentar a robustez contra a incompatibilidade entre os valores dos parâmetros da máquina e do controlador, conforme apresentado em [8]- [10]. Em [11] o MPC comum emprega um modelo não linear considerando a representação de Taylor do MI para cada ponto de equilíbrio.…”

Section: Introductionunclassified

Controle Preditivo Robusto De Corrente Por Estados Finitos Para Motor De Indução Usando Abordagem Deadbeat No Referencial Síncrono

Oliani¹,

Santos²,

Figueiredo³

et al. 2023

Eletrônica de Potência

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O controle preditivo baseado em modelo tem ganhado destaque na área de acionamentos de máquinas de indução. Entre as suas principais vantagens estão o alto desempenho, a flexibilidade e a simplicidade de implementação. No entanto, eventuais variações nos parâmetros da planta comprometem o desempenho do controle. Propostas para o aumento da robustez dessa técnica têm sido objeto de pesquisa com diferentes abordagens, como modificações no modelo matemático da planta e projetos de novos observadores de fluxo. Este trabalho propõe um controle preditivo robusto baseado em modelo de corrente, empregando o controle indireto orientado por campo no referencial síncrono. A corrente do estator e o fluxo do rotor são tomados como variáveis de estado e o vetor tensão do estator é tido como a entrada. O seu diferencial com relação à estratégia de controle preditivo por estados finitos clássica está na construção do algoritmo de controle. O vetor tensão é calculado em duas componentes, combinando o controle preditivo clássico com a abordagem deadbeat: uma considera a referência de corrente do estator e a outra considera as perturbações causadas por erros de parâmetros. O desempenho do método de controle foi verificado através da condução de ensaios em bancada de teste experimental ao se analisar o comportamento estacionário e dinâmico do sistema. Os resultados corroboram a eficácia da proposta de controle robusto contra variações paramétricas.

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“…The study of MPC type controller using the singular values began in our research group with the publication [33]. The authors analyzed the MPC in conjunction with the repetitive controller (PRC, Predictive Repetitive Control) by varying the parameters of the Double Fed Induction Generator (DFIG) for wind generation.…”

mentioning

confidence: 99%

Robust Model Predictive Control of a Renewable Energy Converter Under Parametric Uncertainty Conditions

Costa,

Lunardi,

Fernandes

et al. 2024

IEEE Open J. Power Electron.

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The advanced control technique Model predictive control (MPC) is gaining popularity in power electronics for converters with distributed energy resources. It combines closedloop control and minimizes errors and control effort. As a model-based control technique, MPC's performance can degrade due to plant disturbances, such as parametric errors or large perturbations in grid voltage or load current. Our research used an MPC with modulation on a converter connected to the grid with an inductive filter for integrating renewable energy sources. The margin of robust stability (RS), derived from the singular Value Decomposition (SVD), provides a theoretical investigation of the robustness of the MPC controller tuning in dependency on the cost function weight factors and the time horizons. In the experiments conducted on a 2 kW workbench, it was confirmed that the proposed controller is stable and robust in nominal and under severe parametric uncertainty conditions, addressing the power quality criteria defined in IEEE Std. 519-2014. The experimental results show that the proposed MPC controller tuning outperforms the classical PI current controller in nominal conditions and is more robust to uncertainty in the passive filter of the grid-connected converter.

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Improvement of Robustness of MPC Adding Repetitive Behavior for the DFIG Current Control

Cited by 6 publications

References 48 publications

Robust Finite Control Set Model Predictive Current Control for Induction Motor Using Deadbeat Approach in Stationary Frame

Robust Finite Control Set Model Predictive Current Control for Induction Motor Using Deadbeat Approach in Stationary Frame

Controle Preditivo Robusto De Corrente Por Estados Finitos Para Motor De Indução Usando Abordagem Deadbeat No Referencial Síncrono

Robust Model Predictive Control of a Renewable Energy Converter Under Parametric Uncertainty Conditions

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