Exponentially stable trajectory following of robotic manipulators under a class of adaptive controls. In this paper we investigate the problem of fault diagnosis in rigid-link robotic manipulators. A learning architecture, with neural networks as on-line approximators of the oo-nominal system behavior, is used for monitoring the robotic system for faults. The approximation of the oo-nominal beh...

this paper presents a new observer design methodology for a time varying actuator fault estimation. a new linear matrix inequality (lmi) design algorithm is developed to tackle the limitations (e.g. equality constraint and robustness problems) of the well known so called fast adaptive fault estimation observer (fafe). the fafe is capable of estimating a wide range of time-varying actuator fault...

Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, the classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as evolutionary algorithms and neural networks become more and more popular in industrial applications of fault diagnosis. The main objective of this p...

An Iterative Learning Observer (ILO) updated successively and iteratively by immediate past system output error and ILO input is proposed for a class of time-delay nonlinear systems for the purpose of robust fault diagnosis. The proposed observer can estimate the system state as well as disturbances and actuator faults so that ILO can still track the post-fault system. In addition, the observer...

The rotating machinery is a common class of machinery in the industry. The root cause of faults in the rotating machinery is often faulty rolling element bearings. This paper presents a novel technique using artificial neural network learning for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (harmmean and median), whic...

Fault detection, fault isolation and fault diagnosis are addressed within a statistical framework. The corresponding inference problems are stated. Several statistical tools for solving these inference problems are described. Particular emphasis is put on dealing with nuisance parameters and deciding between multiple hypotheses. How to use these tools for solving FDI problems is discussed. An e...

FPGAs are important in many different applications, and represent a lot of money in the computer engineering community. They are highly reconfigurable, and thus highly complex. FPGAs must work reliably, and so methods of detection, diagnosis, and fault tolerance have been found to make sure that FPGAs work when they are needed, regardless of present circumstances. Methods of detection include c...

Transformer fault diagnosis and repair is a complex task that includes many possible types of faults and demands special trained personnel. In this paper, Petri Nets are used for the simulation of transformer fault diagnosis process and the definition of the actions followed to repair the transformer. An oil thermometer and a Buchholz relay are used for transformer fault detection. Simulation r...