In this paper, a fault diagnosis method is developed for a particular class of nonlinear systems described by a polytopic Linear Parameter Varying (LPV) formulation. The main contribution consists in the synthesis of an accurate Fault Detection and Isolation (FDI) filter and also a sensor fault magnitude estimation with a quality factor. This quality factor of the filter underlines if the fault...

Model-based control and monitoring such as feed-forward/feedback control, fault detection and isolation (FDI), and fault-tolerant control (FTC) techniques that utilize Lyapunov-based control laws are implemented on a high recovery reverse osmosis desalination plant model. A detailed mathematical model of a high recovery reverse osmosis plant is developed. This model incorporates the large spati...

Given a number of possibly concurrent faults (and disturbances) that may affect a nonlinear dynamic system, it may not be possible to solve the standard fault detection and isolation (FDI) problem, i.e., to detect and isolate each single fault from all other, possibly concurrent faults and disturbances, due to the violation of the available necessary conditions of geometric nature. Motivated by...

The Orbital Cygnus vehicle is being developed to perform autonomous rendezvous with International Space Station (ISS) and to provide cargo services to the faculty. Safety through fault management has been a primary consideration in the design of the trajectories, GN&C algorithms, and software. This paper describes the approach used to design and validate a fault management system required to me...

Fault detection and isolation (FDI) in dynamic data from an automotive engine air path using artificial neural networks is investigated. A generic SI mean value engine model is used for experimentation. Several faults are considered, including leakage, EGR valve and sensor faults, with different fault intensities. RBF neural networks are trained to detect and diagnose the faults, and also to in...

In this paper, a new method for solving the fault detection and isolation (FDI) problem in general nonlinear stochastic systems is proposed. The proposed method is based on adaptive Monte Carlo filter and likelihood ratio approach. The simulation results on a highly nonlinear system are provided which demonstrate the effectiveness of the proposed method.

The existence of damage in different members of a structure can be posed as a fault detection problem. It is also necessary to isolate structural members in which damage exists, which can be posed as a fault isolation problem. It is also important to detect the time instants of occurrence of the faults/damage. The structural damage detection filter developed in this paper is a model-based fault...

Fault Detection and Isolation (FDI) methods have been developed over the past thirty years but only in the last several years they have been applied to complex real applications. This paper presents a synthesis of ∞ FDI filters for the longitudinal motion of the Boeing 747-100/200 aircraft. The filters are synthesized to detect and isolate faults in the elevator actuator and pitch rate sensor w...

In this paper, a fault detection and isolation (FDI) scheme is derived based on fuzzy rules extracted from the neurofuzzy network that models the residual of the system. First, a fault database (FDB) is constructed from fuzzy rules extracted from the neurofuzzy networks that model all possible faults in the system. By comparing the currently extracted fuzzy rules with those in the FDB using the...

This paper considers a new approach to fault detection and isolation (FDI) for systems modeled as an interconnection of subsystems that are each subject to parametric faults. The paper develops i) the concept of a diagnostic model that parameterizes all possible subsystem faults, ii) an off-line scheme for identification of the diagnostic model, iii) a parity equation that results in a residual...