Regression analysis constitutes an important tool for investigating the effect of explanatory
variables on response variables. When outliers and bias errors are present, the weighted …

In a previous study, a nonlinear dynamic data reconciliation procedure (NDDR) based on
the particle swarm optimization (PSO) method was developed and validated in line and in …

The product quality of some chemical processes is affected by those output variables
exhibiting distributed characteristics. To enable process monitoring and quality analysis …

Data reconciliation has played a significant role in rectifying process data which can meet
the conservation laws in industrial processes. Generally, the actual measurements are often …

In this paper, we propose a robust multiple-model linear parameter varying (LPV) approach
to identification of the nonlinear process contaminated with outliers. The identification …

Instrument Engineers' Handbook, Third Edition: Volume Three: Process Software and Digital
Networks provides an in-depth, state-of-the-art review of existing and evolving digital …

In an industrial scenario, one can find measured data that do not satisfy the mass and
energy laws of conservation. This problem can be approached by applying data …

Due to the complexity of the industrial working environment, controllers are susceptible to
various disturbance signals, resulting in unsatisfactory control performance. Therefore, it is …

To inhibit the effect of disturbance in a system, feedforward control is usually combined with
feedback loops to provide better control. The working environment for feedforward/feedback …

This paper considers the robust identification for dual-rate input nonlinear equation-error
systems with outliers and random time delay. To suppress the negative influence caused by …