Wavelet analysis is an emerging field of mathematics that has provided new tools and algorithms suited for the type of problems encountered in process monitoring and control. In this paper, a review is presented for the ...

A hybrid control scheme consisting of a generic model control (GMC) and a nonlinear adaptive state estimator (ASE) is designed. The ASE estimates the partially known parameters in the presence of process/predictor mismatch, ...

Soft sensors play an important role in predicting the values of unmeasured process variables from knowledge of easily measured process variables. Online estimation of particle size is vital for efficient control of a ...

Over a number of years, pH control of neutralization process is recognized as a benchmark for modeling and control of nonlinear processes. This paper first describes dynamic modeling of pH neutralization process. Thereafter ...

This paper presents an online implementation of wavelet-based least-square identification (WLSI) and wavelet-based dynamic matrix control (WDMC) in a plate-type heat exchanger unit. Wavelet domain |blocking| and |condensing| ...

This article addresses the issue of outlier detection in industrial data using robust multivariate techniques and soft sensing of clinker quality in cement industries. Feed-forward artificial neural network (back propagation, ...

pH control plays an important role in many modern industrial plants due to strict environment regulations. This paper presents fuzzy logic based pH control scheme for neutralization process in which particle swarm algorithm ...

Use of soft sensors for online particle size monitoring in a grinding process is a viable alternative since physical sensors for the same are not available for many such processes. Cement fineness is an important quality ...

Prediction of primary quality variables in real time with adaptation capability for varying process conditions is a critical task in process industries. This article focuses on the development of non-linear adaptive soft ...