Dynamic Characteristics Analysis of DFIG Based on IMC

Ren, Yong; Li, Hanshan; Zhou, Jie; An, Zhongquan; Liu, Jinguo; Hu, Hongbin

doi:10.1109/appeec.2009.4918297

Cited by 2 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2, the system was composed of controlled plant ( ) P z , internal model of the controlled plant ˆ( ) P z , internal model controller ( ) D z , r was input, v was the disturbance and y was output. With this control structure, we can get [6]: In the NNIMC control system, NNC was the inverse model of neural networks, which serve as controller, NNM was the positive model of neural networks, and also the filter was serving as a feed forward compensation.…”

Section: Rotor Side Converter's Vector Control Of Dfigmentioning

confidence: 99%

NN-IMC Control for DFIG Based Wind Power Generation System RSC

Jian

Zhang

2014

AMM

View full text Add to dashboard Cite

The rotor side converter of DFIG with stator flux-oriented vector control was presented with the mathematical model created and the control structure analyzed. The neural networks internal model control was proposed in this control system which composed of NNC and NNM, the NNC was the inverse model of neural networks, which serve as controller, NNM was the positive model of neural networks, the control feature was verified with simulation.

show abstract

Section: Rotor Side Converter's Vector Control Of Dfigmentioning

confidence: 99%

NN-IMC Control for DFIG Based Wind Power Generation System RSC

Jian

Zhang

2014

AMM

View full text Add to dashboard Cite

show abstract

Controlador Robusto Multivariável com Ação Integral Aplicado em um Sistema de Geração Eólica

Pinto¹,

Campos²,

Rocha³

et al. 2011

Eletrônica de Potência

View full text Add to dashboard Cite

Resumo -Este artigo apresenta os resultados experimentais de uma nova aplicação do controlador robusto LQG/LTR (Linear Quadratic Gaussian with Loop Transfer Recovery) com ação integral (LQG/LTRI) em um gerador de indução duplamente alimentado (Doubly-Fed Induction Generator -DFIG). A metodologia de controle proposta assegura a robustez em relação à rejeição do erro de rastreamento, insensibilidade a variações paramétricas, além de permitir que erros de medida e modelagem sejam incorporados no projeto.Resultados experimentais, obtidos em um protótipo de laboratório com uma máquina de 2kW são apresentados para validar e demonstrar o bom desempenho do controlador proposto em um sistema de geração eólica com máquinas DFIG. fed induction generator (DFIG). The proposed control method assures the robustness with respect to the tracking error rejection, insensitivity to parametric variations and permits that measurement and modeling errors are incorporated in the project. Experimental results, obtained in a laboratory prototype with a 2kW machine, are presented to validate and demonstrate the good performance of the proposed controller in a wind power generation system with DFIG machines. Abstract -This paper presents the experimental results of a new application of the LQG/LTR robust controller (Linear Quadratic Gaussian with Loop Transfer Recovery) with integral action (LQG/LTRI) in a doubly

show abstract

Dynamic Characteristics Analysis of DFIG Based on IMC

Cited by 2 publications

References 9 publications

NN-IMC Control for DFIG Based Wind Power Generation System RSC

NN-IMC Control for DFIG Based Wind Power Generation System RSC

Controlador Robusto Multivariável com Ação Integral Aplicado em um Sistema de Geração Eólica

Contact Info

Product

Resources

About