A robust detection and isolation scheme for incipient and abrupt faults in robot manipulator using neural network

This paper investigates an algorithm for robust fault detection and isolation(FDI) in robot manipulator using an neural network(NN) based observer. The proposed FDI algorithm uses both an nonlinear estimation process and an neural network based learning algorithm. This online monitoring algorithm is used to detect and isolate dynamic changes of a robot manipulator due to both incipient and abrupt faults. Another neural network is used for estimate the uncertainties in robot dynamics. A computer simulation for a two link robot manipulator shows the effectiveness of the proposed algorithm in the fault detection and isolation process.