Structural health monitoring (SHM) is the main contributor of the future's smart city to deal
with the need for safety, lower maintenance costs, and reliable condition assessment of …

In the conventional approaches to the design of fault diagnosis systems, little effort is usually
paid to the selection of the parity vectors. As a result, the systems' performance can be …

The present work deals with the application of coevolutionary algorithms and artificial neural
networks to perform input selection and related parameter estimation for nonlinear black-box …

Real-time information on the plant water status is an important prerequisite for the precision
irrigation management of crops. The plant transpiration has been shown to provide a good …

This paper reviews structural health monitoring (SHM) techniques of bridge structures based
on machine learning (ML) algorithms. Regular inspections and the use of non-destructive …

This work presents a sensor-fault-tolerant design applied to a decentralized dissolved
oxygen control in an activated sludge process subject to sensor faults such as bias and slow …

In this paper a virtual refrigerant charge sensor (VRCS) for a booster refrigeration system
with a receiver unit is developed and proposed. The VRCS estimates the liquid charge in the …

In this paper, the parameter estimation issue of Wiener system with random time delay and
missing output data is studied. The linear part of Wiener system is described by Finite …

In this paper, an iterative learning recursive least squares (ILRLS) identification method is
developed by considering a class of repetitive systems. First, considering a repetitive …

New design conditions on the observer based residual filter design for the linear discrete-
time linear systems with zoned system parameter faults are presented. With respect to time …