Efficient Temperature Profile Estimation for Silicon Wafers based on Subspace Observers

Abstract

This work proposes a computationally efficient observation algorithm for the surface temperature profile of heated silicon wafers. The observer exploits the fact that only a few modes of the original large-order model are unstable or slowly converging. In this case, it suffices to modify only these modes by the observer’s output feedback gain. Compared to classical observation techniques, the proposed method allows to compute the feedback gain for a state space of lower dimension, which reduces computational complexity. A comparison of the approach with the extended Kalman-Bucy filter using experimental data shows its appealing performance.