迭代學習控制應用於六軸機械手臂之抑振控制

Iterative Learning Control for a Six-Axis Manipulator Vibration Suppression

林嘉亮(Jia-Liang Lin)

指導教授 ： 黃漢邦

國立臺灣大學/工學院/機械工程學研究所/碩士(2018年)

https://doi.org/10.6342/NTU201803330

摘要

本文主要是致力於六軸機械手臂的振動控制。為了深入瞭解六軸機械手臂產生振動的原因，並透過有效的控制方法將振動消除，本文共分為兩個部分。第一部分：使用振動訊號分析，通過運用VMD-HHT的方法分析振動訊號，提取出振動的特徵。第二部分：在振動控制策略上，首先採用平順的軌跡規劃方法，首先消除部分殘餘的振動，然後結合回授控制器和迭代學習控制器進行振動控制。回授控制器用於穩定系統，同時補償彈性扭矩；迭代學習控制器通過手臂重複的操作，不斷補償振動造成的重複性誤差。另外，為提高迭代學習控制器的性能，運用訊號處理的方法，分離出無需學習的資訊，讓其針對振動所造成的誤差訊號作學習。所提出機械手臂振動控制的理論與方法，經模擬及實驗驗證後，成效良好。

關鍵字

六軸機械手臂 ； 振動控制 ； 振動訊號分析 ； VMD-HHT ； 迭代學習控制

並列摘要

his thesis addresses the vibration control for a six-axis manipulator. In order to understand the causes of the vibration in the six-axis manipulator, and then eliminate the vibration through an effective control method, the vibration control structure can be divided into two parts. First, a method of integrating variational mode decomposition (VMD) with the Hilbert-Huang Transform (HHT) algorithm is used to analyze the vibration signal, and extract the vibration characteristics. Second, a smooth trajectory planning method is first used to eliminate the residual vibration, and then the feedback controller and iterative learning controller are used to control the vibration. The feedback controller is used to stabilize the system while compensating the elastic torque. The iterative learning controller compensates for the repetitive error caused by vibration through repeated operation of the arm. In addition, in order to improve the performance of the iterative learning control (ILC), the method of signal processing is used to separate out useless information so that the ILC can learn more quickly how to compensate for the error caused by vibration. The simulation and experimental results verify the performance of the proposed methods for vibration suppression.

並列關鍵字

A Six-Axis Manipulator ； Vibration Control ； VMD-HHT ； Iterative Learning Control

參考文獻

[1] H.-S. Ahn, C.-H. Choi, and K.-B. Kim, “Iterative Learning Control for a Class of Nonlinear Systems,” Automatica, Vol. 29, No. 6, pp. 1575–1578, 1993.

[2] J. H. Ahn, D. H. Kwak, and B. H. Koh, “Fault Detection of a Roller-Bearing System through the EMD of a Wavelet Denoised Signal,” Sensors (Switzerland), Vol. 14, No. 8, pp. 15022–15038, 2014.

[3] A. Albu‐Schäffer, S. Haddadin, C. Ott, A. Stemmer, T. Wimböck, and G. Hirzinger, “The DLR Lightweight Robot - Design and Control Concepts for Robots in Human Environments,” Industrial Robot: An International Journal, Vol. 34, No. 5, pp. 376–385, 2007.

[4] R. Analysis, E. Robots, and I. Introduction, “Robustness Analysis of Nonlinear Decoupling for Elastic-Joint Robots,” IEEE Transactions on Robotics and Automation, Vol. 6, No. 3, pp. 373–377, 1990.

[5] A. Andrew, “Kircanski, Goldenberg - An Experimental Study of Nonlinear Stiffness, Hysteresis, and Friction Effects in Robot Joints with Harmonic Dri.PDF,” The International Journal of Robotics Research, Vol. 16, No. 2, pp. 214–239, 1997.