Secure interval estimations for time‐varying delay interconnected systems using novel distributed functional observers

Abstract

In this article, we consider the problem of designing distributed functional observers for time-varying delay interconnected systems under stealthy attacks. Distributed reduced-order observers are first designed to construct bounds for the attack signals. Then, the obtained bounds of the attack signals are utilized to design novel distributed functional observers, which provide interval estimations for linear functions of the state vectors of subsystems when the time-varying delay interconnected system is under stealthy attacks. Existence conditions of the distributed reduced-order observers as well as distributed functional state observers are established, and an effective algorithm for computing unknown observer matrices is provided. A numerical example is used to confirm the effectiveness and advantages of the obtained results.

Design of distributed event‐triggered states and unknown disturbances observers for time‐varying delay interconnected systems

“…For example, large interconnected power systems, 1 interconnected vehicular system, 2 energy management in DC‐grids, 3 linear transportation networks, 4 DC microgrids, 5 switched interconnected non‐affine nonlinear systems under arbitrary switching, 6 DC bus networks, 7 ecological systems, biological systems and energy systems, 8 industrial processes, 9 electrical circuits 10 . On the other hand, the information on state vectors of dynamical systems plays an important role in many applications such as state‐feedback control, system supervision, fault diagnosis of dynamic processes, and so on (see, for example, References 11–18). However, very often, the information on state vectors is often unavailable due to many reasons such as technical, and economic.…”

Interval observers design for systems with ostensible Metzler system matrices

“…The utilization of interval observers for interconnected schemes is often applied in relation to distributed interval estimation and distributed feedback control (Wang et al, 2020;Wang X L et al, 2022;Zhang et al, 2022); this also reflects that their application for continuous linear largescale systems is limited due to the system's complexity (Wang T et al, 2022). These problems are still open in distributed applications since it is difficult to ensure that the system state will be enclosed by the cooperative estimated upper and lower bounds of the observed system state (Huong, 2022;Li et al, 2022), as well as in interval estimation strategy for anti-disturbance control of drones (Yong et al, 2020).…”