Set-Membership Filtering for Time-Varying Complex Networks with Randomly Varying Nonlinear Coupling Structure

This paper is concerned with set-membership filtering for time-varying complex networks with randomly varying nonlinear coupling structure. A novel coupling model governed by a sequence of Bernoulli stochastic variables is proposed. The connection relationships among multiple nodes of complex networks are nonlinear. Utilizing the mathematical induction method, a sufficient condition is derived to remain the filtering error within an ellipsoid region at each time step. Subsequently, the desired filter gain is obtained by minimizing the ellipsoid constraint matrix (in the sense of trace) according to a recursive linear matrix inequalities algorithm. Finally, a simulation example is presented to illustrate the effectiveness of the proposed theory.

Automated summary

This paper focuses on set-membership filtering for time-varying complex networks with randomly varying nonlinear coupling structure. A new coupling model governed by a sequence of Bernoulli stochastic variables is proposed. The connection relationships among multiple nodes of complex networks are nonlinear. A sufficient condition is derived using mathematical induction to ensure that the filtering error remains within an ellipsoid region at each time step. The desired filter gain is obtained by minimizing the ellipsoid constraint matrix (in the sense of trace) using a recursive linear matrix inequalities algorithm. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed theory.