In this study, a novel soft sensor modeling approach using Takagi–Sugeno (TS) fuzzy
models and Prediction Intervals (PIs) is presented to quantify uncertainties in Electric Arc …

Electric arc furnaces (EAFs) are intended for the recycling of steel scrap. One of the more
important variables in the recycling process is the tapping temperature of the steel. Due to …

In this paper, two approaches to fuzzy prediction interval modelling of the processes with
scarce output measurements are presented. Many real-world processes exhibit a significant …

The key of Basic oxygen furnace (BOF) endpoint control is to achieve accurate forecast of
the endpoint carbon content and temperature. Due to the highly nonlinear and complex …

As an indispensable component of coal-fired power plants, boilers play a crucial role in
converting water into high-pressure steam. The oxygen content in the flue gas is a crucial …

Strict monitoring and prediction of endpoints in a Basic Oxygen Furnace (BOF) are essential
for end-product quality and overall process efficiency. Existing control models are mostly …

Soft sensors have gained wide popularity in the industrial processes for online quality
prediction in the recent years. In the case of online deployment, it is important to incorporate …

Various data driven soft sensor models have been established for online prediction of the
silicon content in blast furnace ironmaking processes. However, two main disadvantages …

The molten iron quality (MIQ) in the blast furnace (BF) needs on-site sampling and
laboratory tests, which is very unfavorable to the control. To estimate multiple molten iron …

The temperature and silicon content of hot metal are essential parameters for the thermal
control of a blast furnace. However, the physical structure of the blast furnace prevents direct …