Partial-Node-Based State Estimation for Complex Networks With Energy Harvesting Sensors

In this paper, the recursive partial-node-based (PN-B) state estimation problem is investigated for a class of time-varying complex networks (CNs) with energy harvesting sensors (EHSs). Measurements are transmitted to the remote state estimator by the EHSs only when the current energy level can compensate for the energy consumption. Only a part of the network nodes' measurements, which are available to the users, are utilized to estimate the network states. The objective of this problem is to design a recursive state estimator for CNs with EHSs based on available measurements observed from partial nodes. The upper bound of the estimation error covariance is first established with the help of intensive scholastic techniques and induction approach. Then, the required estimator gain is determined by minimizing such an upper bound. Finally, an illustrative example is presented to verify the effectiveness of the proposed PNB state estimation method.