Optimization of X-axis servo drive performance using PSO fuzzy control technique for double-axis dicing saw

基于粒子群优化模糊控制技术的双轴切割锯X轴伺服驱动性能优化

阅读:1

Abstract

The dicing saw is a critical piece of equipment in IC processing, primarily used to cut wafers. Due to the high spindle speed, even small errors in the cutting process can result in wafer chipping or cracking. Therefore, the dicing saw requires a high degree of accuracy and stability. In this paper, the accuracy of the X-axis servo response was simulated using an Israeli ADT-8230 dual-axis abrasive wheel dicing saw. The study introduces a novel approach by using a fuzzy controller instead of the traditional position loop proportional integral (PI) controller. In addition, a two-input, two-output fuzzy rule is used for on-line correction of the position loop PI parameters. A heuristic algorithm is used to optimise the position loop fuzzy controller parameters. The quantization and proportionality factors are rectified using Particle Swarm Optimisation (PSO) algorithm and Genetic Algorithm (GA) respectively. By comparing the performance of the PSO fuzzy and GA fuzzy controllers, the optimal control method is derived. The proposed method is validated by simulation in the MATLAB/Simulink development environment using real ADT-8230 servo data. Experimental results show that the PSO-fuzzy structured controller reduces the position control error by 11.8%, improves the tracking performance by 26% and reduces the torque pulsation by 23%. Therefore, in future research, more advanced search algorithms should be further combined to improve the servo accuracy of the dicing saw.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。