Event-triggered Fusion Estimation for Nonlinear Stochastic System with Unknown Parameters and Transmission Fading Over Sensor Networks

This paper investigates an event-triggered fusion estimation problem for a class of discrete-time nonlinear stochastic systems with unknown parameters and transmission fading over sensor networks (SNs). The system with unknown and bounded parameters is considered in this paper, which is more practical compared with traditional systems. The fading of local estimation information will occur during the remote transmission. Therefore, the objective of this paper is to design a new fusion method based on unknown parameters and faded local estimation information. With the help of Lyapunov-type analysis approaches and quadratic cost function, sufficient conditions are established to ensure the input-to-state stability (ISS) of the dynamics of estimation errors and obtain the bound of estimation errors in the mean square sense. Finally, an appropriate fusion estimation method is proposed to estimate both unknown parameters and system states. At last, an illustrative simulation is utilized to verify the feasibility of the proposed design scheme.