Sharif Digital Repository

Fault detection and identification is one of the major issues and challenges in the field of engineering and currently is considered as an active field of research. As the replacement of human in dangerous or inaccessible environments, robotic mechanical systems can be used which exposes to a variety of stresses and actions that causes faults in the actuators or sensors. Accordingly, detection of fault at the earliest possible time after the fault accurence and its identification such that real flaw waveform is being extracted, can prevent more damage to the system without any need to human immediate interference. Model based approach in recent decades has shown their ability to detection... 

Fault detection in swarm robots is one of the most important issues that has drawn a lot of scientists’ attention. Previous studies have shown a lot of problems regarding this issue, such as dependency of data-based methods to mission and high complexity of model-based methods on the condition that nonlinear models are used. Extended information filter is an applicable method for fault detection because it could turn the inverse of a big matrix to a simple summation of information that is so desired in terms of calculations. The goal of this study is to identify the agents with fault in swarm robots online by modifying the extended information filter. In this study, it has been attempted to...