This paper is a brief survey on the existing problems and challenges inherent in model-
based control (MBC) theory, and some important issues in the analysis and design of data …

Early and accurate fault detection and diagnosis for modern manufacturing processes can
minimise downtime, increase the safety of plant operations, and reduce costs. Such process …

Early and accurate fault detection and diagnosis for modern chemical plants can minimise
downtime, increase the safety of plant operations, and reduce manufacturing costs. The …

The Principal Component Analysis (PCA) and the Partial Least Squares (PLS) are two
commonly used techniques for process monitoring. Both PCA and PLS assume that the data …

A typical design procedure for model predictive control or control performance monitoring
consists of: identification of a parametric or nonparametric model; derivation of the output …

Industrial continuous processes may have a large number of process variables and are
usually operated for extended periods at fixed operating points under closed‐loop control …

In this paper, a closed-loop subspace identification approach through an orthogonal
projection and subsequent singular value decomposition is proposed. As a by-product of …

In process engineering, on-line state and parameter estimation is a key component in the
modelling of batch processes. However, when state and/or measurement functions are …

The Kullback information is developed as the natural measure of the error in model
approximation for general model selection methods including the selection of model state …

Subspace identification methods, such as canonical variate analysis (CVA), are noniterative
tools suitable for the state-space modeling of multi-input, multi-output processes, eg …