Distributed Non-Fragile State Estimation for Uncertain Nonlinear Systems of Sensor Networks Subject to Sensor Nonlinearities - Tian, Shihui; Xu, Ke; Huang, Fengshan (Sensors (Basel, Switzerland), 2025)
This paper studies the distributed state estimation issue of nonlinear dynamical systems with parameter uncertainties based on sensor networks under the non-fragile control framework. Moreover, all the sensors are in a fully distributed framework with information exchanges to reduce the communication and computation resources. In particular, the sensor nonlinearities in the sensor network and state estimation gain fluctuations are taken into account for more general applicability. With the help of the Lyapunov–Krasovskii approach, sufficient convex optimization criteria can be given so that the passivity performance of its resultant state estimation error system can be guaranteed. The optimized non-fragile state estimation gains can be further determined on the basis of solving the convex optimization. The advantages and usefulness of our developed results are finally demonstrated by two illustrative examples.