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Test-time Forgery Detection with Spatial-Frequency Prompt Learning 期刊论文  OAI收割
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2024, 页码: 16
作者:  
  |  收藏  |  浏览/下载:8/0  |  提交时间:2024/09/09
Double inverted pendulum control based on three-loop PID and improved BP neural network (EI CONFERENCE) 会议论文  OAI收割
2011 2nd International Conference on Digital Manufacturing and Automation, ICDMA 2011, August 5, 2011 - August 7, 2011, Zhangjiajie, Hunan, China
作者:  
Fan Y.
收藏  |  浏览/下载:37/0  |  提交时间:2013/03/25
To deal with the defects of BP neural networks used in balance control of inverted pendulum  such as longer train time and converging in partial minimum  this article reaLizes the control of double inverted pendulum with improved BP algorithm of artificial neural networks(ANN)  builds up a training model of test simulation and the BP network is 6-10-1 structure. Tansig function is used in hidden layer and PureLin function is used in output layer  LM is used in training algorithm. The training data is acquried by three-loop PID algorithm. The model is learned and trained with Matlab calculating software  and the simuLink simulation experiment results prove that improved BP algorithm for inverted pendulum control has higher precision  better astringency and lower calculation. This algorithm has wide appLication on nonLinear control and robust control field in particular. 2011 IEEE.