Fault diagnosis of an automated guided vehicle with torque and motion forces estimation: A case study.

The paper is devoted to developing a new fault detection scheme for an Automated Guided Vehicle (AGV) on the basis of so-called virtual sensors (VSs) which provide the information regarding the current status of a vehicle. This set contains the estimates of lateral and longitudinal forces as well as the torque. The paper proposes a novel robust VSs design scheme which yields such estimates taking into account inevitable disturbances/noise and modelling uncertainty without any knowledge about tire models used in the AGV. The obtained estimates are used to generate the residuals and to diagnose the current status of the vehicle. Finally, the paper shows the experimental results concerning the application of the developed methods to fault detection of the self-designed and constructed AGV.