Using Fuzzy Interacting Observers for Fault Diagnosis in Systems with Parametric Uncertainty

Fault Diagnosis in Nonlinear Systems Using Interconnected Sliding Mode Observers

This paper presents a new technique for fault diagnosis and estimation of unknown inputs in a class of nonlinear systems. The novelty of the approach is governed by the use of two interconnected sliding mode observers. The first of the two observers is used for fault diagnosis and the second is used for the reconstruction of unknown inputs. The two observers exchange their respective reconstruc...

Sensor Fault Detection for a class of Uncertain Nonlinear Systems Using ‎Sliding Mode Observers

This paper deals with the issues of sensor fault detection for a class of Lipschitz uncertain nonlinear system. By definition coordinate transformation matrix for system states and output system, at first the original system divided into two subsystems. the first subsystem includes uncertainties but without any sensor faults and the second subsystem has sensor faults but is free of uncertaintie...

Fault Diagnosis Using Neuro-fuzzy Systems with Local Recurrent Structure

This paper investigates the development of the Adaptive Neuro-Fuzzy Systems with Local Recurrent Structure (ANFS-LRS) and their application to Fault Detection and Isolation (FDI). Hybrid learning, based on a fuzzy clustering algorithm and a gradientlike method, is used to train the ANFS-LRS. The experimental case study refers to an application of fault diagnosis of an electro-pneumatic actuator...

Fault Diagnosis with Static and Dynamic Observers

We study sensor minimization problems in the context of fault diagnosis. Fault diagnosis consists in synthesizing a diagnoser that observes a given plant and identifies faults in the plant as soon as possible after their occurrence. Existing literature on this problem has considered the case of fixed static observers, where the set of observable events is fixed and does not change during execut...

Analysis and Synthesis of Systems with Fuzzy Parametric Uncertainty