Mixed-Delay-Based Augmented Functional for Sampled-Data Synchronization of Delayed Neural Networks With Communication Delay

Distributed filtering for nonlinear time-varying systems with Byzantine attacks and innovation constraints: A FlexRay scheduling mechanism

This paper focuses on the distributed filtering problem for a special type of time-varying systems undergoing stochastic nonlinearities, Byzantine attacks and innovation constraints within the finite-horizon l2-l∞ framework. Taking into account limited network resources, a FlexRay scheduling mechanism incorporating the Round-Robin and weighted try-once-discard protocols is deployed to orchestrate transmission behaviors between sensors and remote filters. A Byzantine attack model is introduced with which the Byzantine nodes falsify the measurements by injecting certain perturbations before sharing them with neighboring nodes. The main purpose of this study is to design a distributed filter for the considered system model such that a finite-horizon l2-l∞ performance is satisfied for the filtering error dynamics. By applying the stochastic analysis method, a sufficient condition is firstly derived to guarantee the existence of desired distributed filter that ensures the prescribed performance index, following which proper filter parameters are designed by solving a set of matrix inequalities. Subsequently, a recursive distributed filtering algorithm is presented, which is friendly for online implementation. Finally, a numerical example is carried out to illustrate the validity of the obtained theoretical results.

Sawtooth-characteristic-based free matrix integral inequality and its application to sampled-data systems

The focus of this article is to present a sawtooth-characteristic-based free-matrix integral inequality and to discuss its application to sampled-data systems (SDSs). Firstly, the free matrix, which is associated with the sawtooth characteristic of the input delay, is presented and incorporated into the integral inequality. In the development of inequality techniques, this is the first time that a free matrix has been associated with the sawtooth characteristic. On this basis, a corresponding sawtooth-characteristic-based free-matrix integral inequality is established, enabling estimation of the integral quadratic terms of the Lyapunov-Krasovskii functional (LKF) derivative. To overcome the challenges posed by second-order terms resulting from the proposed integral inequality, augmented system variables associated with the sawtooth characteristic are also introduced. Thus, the complicated calculation arising from second-order terms and the conservatism caused by the quadratic estimation of the LKF can be avoided. Finally, through the utilization of the sawtooth-characteristic-based free-matrix integral inequality, stability criteria with less conservatism are derived for the SDSs in the form of linear matrix inequalities. The superiority of the proposed approach is illustrated through two numerical examples and a simplified sampled-data based power market.