A Covariance Function Based Approach to Networked System Identification

System identification for networked control is considered. Due to the random time-delays in the network, it can be difficult to work with a discrete-time model and a continuous-time model is therefore chosen here. A covariance function based method is proposed for estimating the parameters, which relies on the second order statistical properties of the output signal and that the input signal samples can be taken from a discrete-time white noise sequence. Numerical studies indicate that the method is robust to additive measurement noise and packet dropouts.