Nonlinear Identification and Self-learning CMAC Neural Network Based Control System of Laser Welding Process

摘要：

Laser welding process plays a critical role in modern processing technologies. It is a typical nonlinear system which is difficult to model and control. In this paper,a laser welding system in University Kentucky is studied. At first,a SISO nonlinear discrete Hammerstein model is established for this system,the welding speed is selected as input and the welding width is output. This model is identified using Least-Square iterative identification algorithm and validated by simulation experiment of step response. Afterwards,a self-learning CMAC neural network based control system is designed for the laser welding process. To improve the performance,a PID controller is attached to it. Finally,this control system is confirmed effectively by four simulation experiments. Results indicate that the identified model and control system are practicable in real systems.

关键词： nonlinear identification laser welding system self-learning CMAC neural network nonlinear Hammerstein model.

作者: Xi Ye Luona Hu Yusheng Liu

作者单位: Department of Automation,Sichuan University Chengdu 610065,Sichuan,China

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 2568-2573

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）