Techniques such as ensembling and distillation promise model quality improvements when paired with almost any base model. However, due to increased testtime cost (for ensembles) and increased complexity of the training pipeline (for distillation), these techniques are challenging to use in industrial settings. In this paper we explore a variant of distillation which is relatively straightforwar...

This paper presents steam temperature models for steam distillation pilot-scale (SDPS) by comparing Pseudo Random Binary Sequence (PRBS) versus Multi-Sine (M-Sine) perturbation signal Both perturbation signals were applied to nonlinear steam distillation system to study the capability of these input signals in exciting nonlinearity of system dynamics. In this work, both linear and nonlinear ARX...

Distillation columns have been widely used in chemical plants for separation process. The high nonlinearity and dynamic behavior of the column make them hard to control. Internal Model Control (IMC) is one of the model based control strategy that have become the central of research to control such column. This paper will review the implementation of IMC in controlling continuous distillation co...

Techniques such as ensembling and distillation promise model quality improvements when paired with almost any base model. However, due to increased testtime cost (for ensembles) and increased complexity of the training pipeline (for distillation), these techniques are challenging to use in industrial settings. In this paper we explore a variant of distillation which is relatively straightforwar...

In this paper, we study the effect of tuning factors on our formerly proposed method [1] for control of distributed multi-rate systems with linear input coupled dynamics. These systems are multi-rate in the sense that neither output measurements nor input updates are available at certain sampling times. Such systems can arise when the number of sensors is less than the number of variables to be...

Techniques such as ensembling and distillation promise model quality improvements when paired with almost any base model. However, due to increased testtime cost (for ensembles) and increased complexity of the training pipeline (for distillation), these techniques are challenging to use in industrial settings. In this paper we explore a variant of distillation which is relatively straightforwar...

We present our work on constructing multi-scale deep convolutional neural networks for automatic speech recognition. Several VGG nets have been trained that differ solely in the kernel size of the convolutional layers. The general idea is that receptive fields of varying sizes match structures of different scales, thus supporting more robust recognition when combined appropriately. We construct...

1,3-butadiene, bd is produced from c4-cut by extractive distillation. the separation of 1,3-butadiene from c4-cut is not possible through the conventional distillation processes, because several mixtures have consisted of close boiling points constituents and make azeotrope. the basf extraction distillation process in bd unit of jam and amirkabir petrochemical company improves the relative vola...

The problem of separating the liquid components which have been recovered from natural gas is discussed. Opportunities for improved efficiency using distributed distillation, recycle coupling, heat pumping, and partial effect distillation are presented. Emphasis is placed upon energy efficiency with potential savings in capital costs as applied to heat driven processes.