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  • 标题:FIELD-ORIENTED INDUCTION MULTI-MACHINE DRIVE USING SINGLE-INVERTER AND DIAGONAL RECURRENT NEURAL NETWORK
  • 本地全文:下载
  • 作者:DEDY KSETIAWAN ; SUPRIHADI P ; B. S. KALOKO
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2017
  • 卷号:95
  • 期号:9
  • 出版社:Journal of Theoretical and Applied
  • 摘要:This paper describes a strategy to develop a model electric car control of induction multi-machine drive using single-inverter under unbalanced load conditions. It is discusses improving existing multi-machine field-oriented control methods using Diagonal Recurrent Neural Network (DRNN), and analyses and compares them from dynamic performance. By this method the speed and current difference for both motors due to load fluctuation was minimized. Therefore, the motors will remain in sync without any slippage speed on the second drive. Based on simulation results is known that the current steady state, the controller DRNN produce both motors speed difference is smaller (2 rad/sec) when compared using the PI controller (7 rad/sec).
  • 关键词:Multi-Machine Induction Motor; Diagonal Recurrent Neural Network; Electric Car Control
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