Set-Membership Estimation for Complex Networks Under FlexRay Protocol Based on the Proportional-Integral Observer With Probability Constraint

Abstract

This paper explores the design of proportional-integral observer (PIO) for a type of time-varying stochastic nonlinear complex networks in which the network dynamics are corrupted by the unknown but bounded noises. With the aim to efficiently regulate the data exchange between network nodes, a transmitting scheme called FlexRay protocol (FRP) is adopted. It is the primary objective to provide a proportional-integral (PI) estimation approach with the capability of driving all estimation errors at individual nodes into a desired region with a predetermined probability. Sufficient conditions are presented, via certain optimization techniques, to enure the existence of desired PIO and corresponding observer parameters. Subsequently, within the established framework, we solve two sub-optimization problems to guarantee the locally optimal estimation performance. Finally, the effectiveness of the proposed paradigm is shown via a numerical simulation example.

Keywords

• FlexRay protocol (FRP)
• proportional-integral observer (PIO)
• probability-guaranteed estimation
• set-membership estimation
• complex networks