State estimation in Networked Control Systems

We consider the problem of state estimation in a Networked Control System, where measurements and control inputs are transmitted via a communication network. The network is subject to time-varying delays and stochastic data losses and does not provide acknowledgments of successfully transmitted data packets. A challenge that arises in this configuration is that the estimator has only uncertain information about the actually applied control inputs. In this paper, we derive a multiple-model based estimator that uses the state measurements to estimate the applied control inputs so that the overall state estimation is improved. The efficiency of the proposed approach is demonstrated by means of Monte-Carlo-Simulation runs with an inverted pendulum on a cart.