Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (26): 223-225.DOI: 10.3778/j.issn.1002-8331.2009.26.067

• 工程与应用 • Previous Articles     Next Articles

Control for swing-up of inverted pendulum based on DRNN

XIE Mu-jun,YANG Hai-rong   

  1. Department of Electrical and Electronic Engineering,Changchun University of Technology,Changchun 130012,China
  • Received:2008-05-22 Revised:2008-08-18 Online:2009-09-11 Published:2009-09-11
  • Contact: XIE Mu-jun

DRNN在倒立摆摆起控制中的研究

谢慕君,杨海蓉   

  1. 长春工业大学 电气与电子工程学院,长春 130012
  • 通讯作者: 谢慕君

Abstract: The swing-up control of an inverted pendulum,a Diagonal Recurrent Neural Network(DRNN) is built to identify the system and self-tuning the PD gains.At the same ranges of swing-up,the system parameters ranged from -50% to 30% for self-tuning PD control based on DRNN,from -40% to 20% for conventional PD controller.The simulation results show that the system,compared with conventional PD controller,the presented control system has great anti-jamming,adaptability and robustness.

Key words: inverted pendulum, diagonal recurrent neural network, PD control, swing-up

摘要: 针对小车一级倒立摆的起摆控制,以DRNN神经网络作为辨识器,在线自适应调整PD控制器的两项参数。在起摆范围相同的情况下,DRNN神经网络控制的倒立摆系统其模型参数变化范围为-50%~30%,传统PD控制倒立摆系统其参数变化范围为-40%~20%。结果表明,基于DRNN神经网络的PD控制器比传统的PD控制器具有较强的抗干扰能力和自适应能力,系统鲁棒性增强,效果明显优于传统的PD控制器。

关键词: 倒立摆, DRNN神经网络, PD控制, 摆起

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