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题名: Neural Network Predictive R2R Control to CMP Process
作者: Wang L(王亮) ; Hu JT(胡静涛)
作者部门: 工业信息学研究室
会议名称: 2011 4th IEEE International Conference on Computer Science and Information Technology
会议日期: June 10-12, 2011
会议地点: Chengdu, China
会议主办者: IEEE
会议录: 2011 4th IEEE International Conference on Computer Science and Information Technology
会议录出版者: IEEE
会议录出版地: Piscataway, NJ
出版日期: 2011
页码: 9-13
ISBN号: 978-1-61284-836-5
关键词: chemical mechanical polishing ; RBF neural network ; predictive control ; run-to-run control ; PSO rolling optimization
摘要: For chemical mechanical polishing(CMP)process characteristics of nonlinear, time-varying and not being in-situ measured, this paper proposes a CMP process neural network predictive run-to-run(R2R) controller named NNPR2R. RBF neural network predictive model about CMP is constructed by subtractive clustering algorithm and least squares method, thus it solves difficult problem of constructing accurate mathematical model of complicated CMP process and improves the prediction accuracy. Control law of model predictive control is obtained by feedback correction and PSO rolling optimization, therefore it solves the problem that derivative-based optimization technology is easy to fall into local optimum and improves control precision. Simulation results illustrate that performance of NNPR2R controller is better than EWMA, process drifts and shifts is suppressed significantly, product quality variation between different runs is reduced, and root mean squared error for material removal rate(MRR) is brought down substantially.
产权排序: 1
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/8376
Appears in Collections:工业信息学研究室_会议论文

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