We consider simulation-based gradient-estimation and its use in Markov controlled processes with unknown parameters. We consider a Markov reward process controlled by both a set of tunable parameters, and a set of fixed but unknown. We analyze the use a recursive identification procedure, and their application to existing gradient-based algorithms based on simulation. We show that simple modifi...

It has long been thought that bioprocess, with their inherent measurement difficulties and complex dynamics, posed almost insurmountable problems to engineers. A novel software sensor is proposed to make more effective use of those measurements that are already available, which enable improvement in fermentation process control. The proposed method is based on mixtures of Gaussian processes (GP...

Key energetic parameters that control growth and mass transport in clean Ag films and nanostructures on Ag(100) are compiled. These parameters have been derived from a number of different types of experiments, and from increasingly refined lattice-gas modeling, over several years. The modeling based upon these parameters appears to have good predictive capability in the temperature range 120−30...

This paper presents a method for optimizing the machining parameters in rough turning processes to control the vibrations and deformations and minimize the production time per component under practical constraints. The optimization model is formulated, in which piecewise constraints are introduced based on the varying length-to-diameter (L/D ) ratio of the workpiece. The optimization problem is...

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