Free-swinging and locked joint fault detection and isolation in cooperative manipulators

The problem of fault detection and isolation (FDI) in cooperative manipulators is addressed. Free-swinging and locked joint faults are detected and isolated by an FDI system based on neural networks. For each arm, a Multilayer Perceptron (MLP) is used to reproduce the dynamics of the fault-free robot. The outputs of each MLP are compared to the real joint velocities in order to generate a residual vector that is then classified by an RBF network. Simulations and a real application are presented indicating the effectiveness of the FDI system.