Partial-Nodes-Based State Estimation for Complex Networks With Constrained Bit Rate
Junyi Li, Zidong Wang, Renquan Lu, Yong Xu
Abstract
In this paper, the partial-nodes-based (PNB) state estimation issue is investigated for a class of discrete-time complex networks with constrained bit rate and bounded noises. Measurements from only a fraction of nodes in a complex network are acquired and used for state estimation. The communication between sensor nodes and estimators is accomplished over a wireless digital communication network with limited bandwidth. A bit rate constraint model is introduced to reflect the bandwidth allocation rules of partially accessible nodes. A sufficient condition is proposed under which the PNB state estimation error system is guaranteed to be ultimately bounded, and then a bit rate condition assuring a specific estimation performance is presented. The estimator gains are derived by solving two optimization problems in order to ensure two estimation performance metrics (i.e. the smallest ultimate bound and the fastest decay rate). Furthermore, the co-design issue of the bit rate allocation protocol and the estimator gains is addressed by means of particle swarm optimization and linear matrix inequalities. Finally, three numerical simulations are provided to verify the validity of the proposed PNB state estimation approach.