Networked Iterative Learning Fault Diagnosis Algorithms for systems with communication constraints

This paper is devoted to develop a wireless networked iterative learning algorithm (WNILA) based fault estimation for systems with packet losses and quantizer measurements. To do so, state variables, Markov chain process of random packet losses, and a logarithmic quantizer are introduced to establish an extended-state-space system model. Then, based on this model, Lyapunov-Krasovskii functional is constructed and compute the stability theory for linear repetitive processes and linear matrix inequality (LMI) technique, an observer gain and learning gain are obtained and a WNILA based fault estimation is constructed. In addition, based on the proposed WNILA, an experimental real-time fault estimation of DC-Servomotor through wireless network is provided to show the effectiveness of the proposed WNILA using ZigBee Xbee, LabVIEW Software and Arduino board.