Fault Detection for Mechanical Arm Systems: An Sliding Mode Observer Approach

This paper considers the fault detection problem about the high-risk operation of the ammunition fuze assembly system, and discusses the fault detection method based on the sliding mode observer. First, a dynamic model of the manipulator is established and its dynamic properties are given. Then, the sliding mode observer equation is proposed, and the RBF neural network is used to approximate the uncertain part, and then the fault detection method is obtained. Finally, the effectiveness of the algorithm is verified by the simulation of the double joint manipulator. The results show that using the sliding mode observer for fault detection can accurately determine the actual fault, accurately estimate the actual state, and ensure the continuous and smooth operation of the system.