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计算机工程 ›› 2009, Vol. 35 ›› Issue (17): 163-166. doi: 10.3969/j.issn.1000-3428.2009.17.056

• 人工智能及识别技术 • 上一篇    下一篇

2-DOF并联机构动力学建模与迭代学习控制

王跃灵,沈书坤,王洪斌   

  1. (燕山大学电气工程学院工业计算机控制工程河北省重点实验室,秦皇岛 066004)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-09-05 发布日期:2009-09-05

Dynamic Modeling and Iterative Learning Control of 2-DOF Parallel Mechanism

WANG Yue-ling, SHEN Shu-kun, WANG Hong-bin   

  1. (Key Lab of Industrial Computer Control Engineering of Heibei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-09-05 Published:2009-09-05

摘要: 针对一种直线电机驱动的2-DOF并联机构,结合直线电机的动力学特性,采用Lagrange方法对其进行动力学建模。考虑该机构重复性动作及其不确定性和非线性特点,提出一种自适应神经网络迭代学习控制方法。在该控制算法的作用下,系统输出能较好地跟踪给定输入。严格证明及仿真结果验证了该算法的有效性。

关键词: 动力学建模, 迭代学习控制, 并联机构, 不确定性

Abstract: The dynamic model of a kind of 2-DOF parallel mechanism driven by linear motor is established by Lagrange method combined with the dynamics characteristic of the linear motor. Adaptive neural network iterative learning control is proposed considering repetitive action, uncertainty and nonlinearity of the system. Using this control algorithm, the outputs of the system can track the desired trajectories. The strict proof and simulation results validate the validity of the controller.

Key words: dynamic modeling, iterative learning control, parallel mechanism, uncertainty

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