Adaptive Control of Machining Process Based on Fuzzy Wavelet Neural Network and Generalized Entropy Square Error

摘要：

In order to improve the slow response and weak robustness of fuzzy control for machining process, combining qualitative knowledge expressiveness of fuzzy control with excellent local property of wavelet analysis and quantitative learning ability of neural network, a new kind of fuzzy wavelet neural network controller (FWNNC) is presented and a generalized entropy square error (GESE) function is also defined. The FWNNC is then applied to the online control of the cutting force under variable cutting conditions. Simulation results show that the proposed controller is superior to the fuzzy control or the neural network control for machining process and it has better static, dynamic performance. Experimental examples are also given to demonstrate the effectiveness of the proposed controller.

关键词： Machining process Adaptive control Fuzzy wavelet neural network Generalized entropy square error

作者: Xingyu Lai Chunyan Yan Bangyan Ye Weiguang Li

作者单位: Department of Mechatronical Engineering, Guangdong Institute of Science and Technology, 351 Kehua St School of Mechanical and Automotive Engineering, South China University of Technology,Wushan Rd., Gu

会议类型: 国际会议

会议名称: 2011 3nd International Conference on Mechanical and Electronics Engineering(2011年第三届机械与电子工程国际会议 ICMEE2011)

会议地点: 合肥

会议语种:英文

页码: 3562-3567

在线出版日期: 2011-09-23（万方平台首次上网日期，不代表论文的发表时间）