Multi-Sensor-Based Aperiodic Least-Squares Estimation for Networked Systems With Transmission Constraints

This paper investigates the least-squares estimation problem for networked systems with transmission constraints. A group of sensors are deployed to measure the outputs of a plant and send the measurements to an estimator through a common communication channel. Due to the transmission constraints caused by the heterogenous or long-distance deployed sensors, only one sensor is allowed to transmit its measurement over one time slot. In this regard, a stochastic competitive transmission strategy is proposed to schedule the transmission permissions. By using the least-squares estimation approach, an aperiodic multi-step estimation algorithm is proposed for the estimator to aperiodically generate the estimates. Performance analysis is presented for the estimation system with bounded noises and random noises. An upper bound is derived for the expectation of the estimation error and a sufficient condition is presented to ensure the convergence of the obtained upper bound. An illustrative example is provided to demonstrate the effectiveness of the proposed results.