The main contribution of this study involves proposing a reliable fault diagnosis system to detect sensor faults in a wide operational range of the process based on the quasi-LPV framework.
A first part presents a quick recap of the history of fuzzy control: from model-free design, based on human reasoning to quasi-LPV (Linear Parameter Varying) model-based control design via some milestones, and key applications.
This piece is based on structure, not note by note.
A new approach for nonlinear inversion, referred to as the structured quasi-LPV model inverse, is developed and validated.
The observer is based on a quasi-linear parameter variant (quasi-LPV) model of the boiler-turbine unit parameterized with real data of the plant in a wide range of operations, namely, at low, medium, and high loads.
Polarization beam-splitters and optical switches based on subwavelength quasi-periodic structures are presented.
For the purpose of our impact evaluation, we structured the quantitative research component based on a quasi-experimental design [ 42] in the form of a controlled pre- and post-test design with two post-test measurements.
These types of simulations were conducted with a specifically designed atmospheric global model based on a quasi-uniform grid mesh structure and a non-hydrostatic equation system.
When reporting the results, we focused on the lag structure that provided the best fit to the data based on the quasi-likelihood information criterion (QIC) (Pan 2001).
Selection of the mean model and variance-covariance structure was done based on quasi likelihood under the independence model criterion (QIC).
