Modern process control is based on process modeling. Advanced process control (APC), real time optimization (RTO), process monitoring, operator training simulation, abnormal situation management (ASM) and fault detection and isolation (FDI) are all based on some kind of process modeling. Models are a very effective way to embed “knowledge” in process automation, which has increased its “autonom...

This paper presents a robust model{based technique for the diagnosis of faults in a chemical process. The diagnosis system is based on the robust estimation of process outputs. A dynamic non{linear model of the process under investigation is obtained by a procedure exploiting T akagi{Sugeno (T-S) multiple{ model fuzzy iden ti cation. The combined iden ti cation and residual generation schemes h...

This paper considers the best sensor configuration and fault accommodation problem for inertial navigation systems which use seven inertial sensors such as gyroscopes and accelerometers. We prove that when six inertial sensors are used, the isolation of a double fault cannot be achieved for some combinations of fault magnitudes, whereas when seven inertial sensors are used, the isolation of any...

The paper focuses on the problem of robust fault detection using analytical methods and soft computing. Taking into account the model-based approach to Fault Detection and Isolation (FDI), possible applications of analytical models, and first of all observers with unknown inputs, are considered. The main objective is to show how to employ the bounded-error approach to determine the uncertainty ...

This paper deals with the analysis of nonlinear reachability and fault tolerant properties of multiactuator nonlinear systems. In this case, the process is a steam generator process containing a set of actuators. After occurrence of one or several actuator faults detected and isolated by Fault Detection and Isolation (FDI) approaches, a quantitative analysis of the faulty system properties help...

To ensure safe operation of unmanned aerial vehicles (UAVs), component hazards need to be dealt with robustly through effective fault diagnosis. The extended Kalman filter (EKF) has proven popular in this realm, though it is known to suffer from linearisation errors that can degrade performance. This paper presents results from initial simulation trials that address sensor fault detection and i...

In this paper Principal Components Analysis (PCA) is used for detecting faults in a simulated wastewater treatment plant (WWTP). PCA is a multivariate statistical technique used in multivariate statistical process control (MSPC) and fault detection and isolation (FDI) perspectives. PCA reduces the dimensionality of the original historical data by projecting it onto a lower dimensionality space....

In this paper, a baseline system which utilizes dual-channel sensor measurements for aircraft engine on-line diagnostics is developed. This system is composed of a linear on-board engine model (LOBEM) and fault detection and isolation (FDI) logic. The LOBEM provides the analytical third channel against which the dual-channel measurements are compared. When the discrepancy among the triplex chan...

We propose a novel soft computing (SC) based approach to design fault detection and isolation (FDI) systems for industrial plants, in particular a highly nonlinear CNC X-axis drive system's component fault detection. The aim of this paper is twofold. One is to present a general description of various concepts such as the novel fuzzy-neuro architecture that uses fuzzy clustering to build a nomin...

We propose an integrated numerically reliable computational approach to solve fault detection and isolation (FDI) problems for periodic systems. For this purpose, a bank of periodic fault detection filters providing a structured residual set is designed using a new least order synthesis technique of periodic fault detection filters. The synthesis procedure relies on a recently developed numeric...