Suggestions(5)
Exact(7)
Tai-Ji ID is developed for model based process control such as model predictive control (MPC) and linear robust control.
The simple model approach described here represents a rapid and useful method for model based process development of multimodal chromatography.
To encounter these difficulties model based process optimization with several iteration steps has been successfully employed in the past (Kovárová-Kovar et al. 2000).
Tai-Ji ID is designed for process control engineers and process engineers who are involved in model based process control and monitoring.
Systematic sensitivity analyses, made possible by a new iterative approach, allows the identification of key parameters for improved fault detection and model based process control of plasma reactors.
In this paper some aspects of the duality found within the following two tightly interconnected problems are discussed: (i) (model based) process performance optimization, and (ii) information content optimization for model identification.
Similar(53)
We also discuss the calibration methodology for use of the model in TCAD based process and device design.
We build an SVM model based on process and noise model estimates from training data to predict the occurrence of MPM in the testing data.
The method here is distinguished from functional Petri nets by the rule based process model.
Computer Aided Process Engineering (CAPE) requires computer based process models for most of its applications.
It is observed that the neural network based process models developed here exhibit good agreement with experimental results.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com