標題: | Temperature control of rapid thermal processing system using adaptive fuzzy network |
作者: | Lin, CT Juang, CF Huang, JC 電控工程研究所 Institute of Electrical and Control Engineering |
關鍵字: | fuzzy system;adaptive fuzzy network;structure/parameter learning;rapid thermal process;direct inverse control |
公開日期: | 1-四月-1999 |
摘要: | Temperature control of a rapid thermal processing (RTP) system using a proposed self-constructing adaptive fuzzy inference network (SCAFIN) is presented in this paper. First, the physical modeling of a RTP system is done. An integrated model is given for the components that make up a RTP system. These components are the lamp power dynamics, ray-tracing model, and the wafer thermal dynamic model. The models for the components are integrated in a numerical code to give a computer simulation of the complete RTP system. The simulation can be used to investigate the interaction of the furnace, lamp contour, and the control system. Then a direct inverse control scheme using the proposed SCAFIN is adopted to control the temperature of the RTP system. The SCAFIN is inherently a modified TSK-type fuzzy rule-based model possessing neural network's learning ability. There are no rules initially in the SCAFIN. They are created and adapted as on-line learning proceeds via simultaneous structure and parameter identification. Simulation results show that the control approach is able to track a temporally varying temperature trajectory and maintain the uniformity of the spatial temperature distribution of the wafer in the RTP system simultaneously. (C) 1999 Elsevier Science B.V. All rights reserved. |
URI: | http://hdl.handle.net/11536/31428 |
ISSN: | 0165-0114 |
期刊: | FUZZY SETS AND SYSTEMS |
Volume: | 103 |
Issue: | 1 |
起始頁: | 49 |
結束頁: | 65 |
顯示於類別: | 期刊論文 |