Abstract Model-based methods are widely used for the fault diagnosis of stochastic dynamic
systems by simply using the input–output relationship of the system. Despite encouraging …

This paper focuses on designing, via the minimization of a suitable cost function, an input
sequence to guarantee active fault diagnosis (AFD) of discrete-time linear parameter …

Bounds for the evolution of state trajectories of systems with uncertainty are important for
various applications such as safety assessment, experimental design, and robust control …

In this paper, design issues of data-driven optimal dynamic fault detection systems for
stochastic linear discrete-time processes are addressed without precise distribution …

This article investigates a class of multiobjective optimization fault detection observer design
problems for linear parameter varying (LPV) systems considering the unknown but bounded …

Data-driven process monitoring methods have attracted great attention due to the case that it
can provide an efficient way to cope with the industrial process without the need of first …

This paper proposes a new input design framework for set-based asymptotic active fault
diagnosis and then applies it to integrated design of active fault diagnosis and control. First …

In this paper, a confidence set-membership filter based on the finite impulse response (FIR)
structure is proposed for time-variant systems that are simultaneously subject to both the …

In this paper, a confidence set-membership state estimator is proposed for a class of
polytopic linear parameter varying (LPV) systems with inexact scheduling variables. The set …

The fault detection (FD) system design aims at optimizing the trade‐off between false alarm
rate (FAR) and fault detection rate (FDR) under stochastic disturbances or uncertainties. A …