基于强化学习的准分子激光器能量控制算法研究 
下载： 1010次
孙泽旭, 冯泽斌, 周翊, 刘广义, 韩晓泉. 基于强化学习的准分子激光器能量控制算法研究[J]. 中国激光, 2020, 47(9): 0901002.
Sun Zexu, Feng Zebin, Zhou Yi, Liu Guangyi, Han Xiaoquan. Energy Control of Excimer Laser Based on Reinforcement Learning[J]. Chinese Journal of Lasers, 2020, 47(9): 0901002.
[1] 余吟山, 游利兵, 梁勖, 等. 准分子激光技术发展[J]. 中国激光, 2010, 37(9): 2253-2270.
[2] Watanabe H, Komae S, Tanaka S, et al. Reliable high-power injection locked 6 kHz 60 W laser for ArF immersion lithography[J]. Proceedings of SPIE, 2007, 6520: 652031.
[3] BastingD. Excimer laser technology[M]. New York: Springer, 2001.
[4] 石海燕, 赵江山, 宋兴亮, 等. 光刻用准分子激光器能量稳定性影响因素分析[J]. 红外与激光工程, 2014, 43(11): 3540-3546.
Shi H Y, Zhao J S, Song X L, et al. Analysis on factors affecting energy stability of excimer laser for lithography[J]. Infrared and Laser Engineering, 2014, 43(11): 3540-3546.
[5] Cacouris T, Conley W, Thornes J, et al. New ArF immersion light source introduces technologies for high-volume 14 nm manufacturing and beyond[J]. Proceedings of SPIE, 2015, 9426: 942618.
[6] Cacouris T, Rechtsteiner G, Conley W. Next-generation DUV light source technologies for 10 nm and below[J]. Proceedings of SPIE, 2017, 10147: 1014718.
[7] Cacouris T, Thornes J, Sells M, et al. Advanced light source technologies for memory and logic processes[J]. Proceedings of SPIE, 2018, 10587: 105870Y.
[8] Tanaka S, Tsushima H, Nakaike T, et al. GT40A: durable 45 W ArF injection-lock laser light source for dry/immersion lithography[J]. Proceedings of SPIE, 2006, 6154: 61542O.
[9] Miyamoto H, Kumazaki T, Tsushima H, et al. The ArF laser for the next generation multiple-patterning immersion lithography supporting green operations and leading edge processes[J]. Proceedings of SPIE, 2017, 10147: 1014719.
[10] 陈晓龙, 楼风光, 何宇, 等. 高效率全国产化10 kW光纤激光器[J]. 光学学报, 2019, 39(3): 0336001.
[11] 刘晓东, 秦应雄, 柳洁, 等. 高功率激光大宽度矩形光束抛物带式积分镜研究[J]. 激光与光电子学进展, 2019, 56(19): 191403.
[12] 朱能伟, 方晓东. 基于FLUENT的准分子激光器气体流场数值仿真[J]. 中国激光, 2016, 43(9): 0901007.
[13] 潘宁, 梁勖, 林颖, 等. 准分子激光系统中模拟信号的传输方法[J]. 红外与激光工程, 2019, 48(9): 0905003.
[14] 范元媛, 周翊, 刘广义, 等. 高效率ArF准分子激光复合腔技术研究[J]. 中国激光, 2016, 43(2): 0202001.
[15] 刘斌, 丁金滨, 王魁波, 等. 高重复频率准分子激光器中放电冲击波特性的实验研究[J]. 中国激光, 2019, 46(12): 1201001.
[16] 朱峰, 黄珂, 陶蒙蒙, 等. 重复频率HF激光脉冲能量稳定性的理论分析[J]. 光学学报, 2019, 39(4): 0414001.
[17] 王效顺, 梁勖, 游利兵, 等. 高重复频率ArF准分子激光器能量控制算法研究[J]. 激光技术, 2012, 36(6): 763-766.
[18] 赵读亮, 李文洁, 梁勖, 等. 准分子激光皮肤治疗仪能量稳定性研究[J]. 红外与激光工程, 2017, 46(12): 1206001.
[19] Sandstrom RL, Besaucele HA, Fomenkov IV, et al. 1999-12-21.
[20] Dayan P. Q-learning[J]. Machine Learning, 1992, 8(3/4): 279-292.
[21] Jacobs R A. Increased rates of convergence through learning rate adaptation[J]. Neural Networks, 1988, 1(4): 295-307.
[22] 黄友锐, 曲立国. PID控制器参数整定与实现[M]. 北京: 科学出版社, 2010.
Huang YR, Qu LG. PID controller parameter tuning and implementation[M]. Beijing: Science Press, 2010.
[23] Chiou J S, Tsai S H, Liu M T. A PSO-based adaptive fuzzy PID-controllers[J]. Simulation Modelling Practice and Theory, 2012, 26: 49-59.
孙泽旭, 冯泽斌, 周翊, 刘广义, 韩晓泉. 基于强化学习的准分子激光器能量控制算法研究[J]. 中国激光, 2020, 47(9): 0901002. Sun Zexu, Feng Zebin, Zhou Yi, Liu Guangyi, Han Xiaoquan. Energy Control of Excimer Laser Based on Reinforcement Learning[J]. Chinese Journal of Lasers, 2020, 47(9): 0901002.
PDF全文
