Abstract Model-based control strategies are widely used for optimal operation of chemical
processes to respond to the increasing performance demands in the chemical industry. Yet …

Prognostic plays an important role in improving the reliability and durability performance of
fuel cells (FCs); although it is hard to realize an adaptive prognostic because of complex …

In many control applications, it is attractive to describe nonlinear (NL) and time-varying (TV)
plants by linear parameter-varying (LPV) models and design controllers based on such …

This paper presents a nonparametric method for identification of MIMO linear parameter-
varying (LPV) models in state-space form. The states are first estimated up to a similarity …

In this paper, the topic of prognosis for proton exchange membrane fuel cell (PEMFC) is
talked about. The objective is to address the residual life estimation problem in …

The linear parameter-varying (LPV) model is widely used in aero engine control system
design. The conventional local modeling method is inaccurate and inefficient in the full flying …

Today, the need to increase efficiency and performance of dynamical systems leads to
innovative control solutions that rely on accurate representations of the underlying system …

This article presents a two‐stage algorithm for piecewise affine (PWA) regression. In the first
stage, a moving horizon strategy is employed to simultaneously estimate the model …

Obtaining mathematical models that can accurately describe nonlinear dynamics of complex
processes and be further used for model-based control design is a challenging task. In this …

In this paper, a Bayesian nonparametric approach is introduced to estimate multi-input multi-
output (MIMO) linear parameter-varying (LPV) models under the general noise model …