Adaptive deadband control of a drifting process with unknown parameters

Zilong Lian and Enrique del Castillo

Statistics & Probability Letters, 2007, vol. 77, issue 8, 843-852

Abstract: Adjusting a drifting process to minimize the expected sum of quadratic off-target and fixed adjustment costs is considered under unknown process parameters. A Bayesian approach based on sequential Monte Carlo methods is presented. The benefits of the resulting "deadband" adjustment policy are studied.

Keywords: Fixed; adjustment; cost; Sequential; Monte; Carlo; methods; Random; walk; Bounded; adjustment (search for similar items in EconPapers)
Date: 2007
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