Temperature control of rapid thermal processing system using adaptive fuzzy network

• Published in: Fuzzy sets and systems Vol. 103; no. 1; pp. 49 - 65
• Main Authors: LIN, C.-T, JUANG, C.-F, HUANG, J.-C
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.04.1999; Elsevier
• Subjects: Adaptive fuzzy network; Applied sciences; Computer science; control theory; systems; Control theory. Systems; Direct inverse control; Exact sciences and technology; Fuzzy system; Process control. Computer integrated manufacturing; Rapid thermal process; Structure/parameter learning; Adaptive fuzzy network; Fuzzy system; Rapid thermal process; Structure/parameter learning; Direct inverse control; Rapid thermal processing; Temperature control; Adaptive system; Fuzzy neural nets; Process control
• ISSN: 0165-0114; 1872-6801
• DOI: 10.1016/S0165-0114(97)00178-4

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.