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The paper is concerned with nonlinear filtering under unknown dynamics and high-complexity observations. We propose a convex optimization-based filtering algorithm, and show that the algorithm yields a bounded error if the disturbances are small and bounded, and if the observations are redundant. An experimental result is presented to demonstrate that the algorithm is capable of accurate real-time estimation of patterned wafer parameters in a plasma etching process with optical observation.
Date of Publication: Feb. 2003