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-Apr-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
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