Fault Diagnosis in Robotic Manipulators Using Joint Torque Sensing

Model uncertainty is an important factor hindering reliability of any modelbased failure detection and identification (FDI) method. Use of joint torque sensing reduces significantly the complexity of robot modeling by excluding hardly-identifiable link dynamics from overall manipulator dynamics. Application of such model in the proposed FDI filter increases reliability of fault monitoring against modeling uncertainty. The proposed filter is based on a smooth velocity observer of degree 2n where n stands for the number of manipulator joints. No velocity measurement and assumption on smoothness of faults are used in the fault detection process.