Probabilistic-constrained tracking control for stochastic time-varying systems under deception attacks: A Round-Robin protocol

The probabilistic-constrained tracking control issue is investigated for a class of time-varying non-linear stochastic systems with sensor saturation, deception attacks and limited bandwidth in an unified framework. The saturation of sensors is quantified by a sector-bound-based function satisfying certain conditions, and the random deception attacks are considered and modeled by a random indicator variable. To gain more efficient utilization of communication channels, a Round-Robin (RR) protocol is utilized to orchestrate the transmission order of measurements. The main purposes of this study aim to plan an observer-based tracking controller to achieve the following goals: (1) the related performance indicators of the estimation error is less than given bound at each time step; and (2) the violation probability of the tracking error confined in a predefined scope is supposed to be higher than a prescribed scalar and the area is minimized at each instant. In order to reach these requirements, a group of recursive linear matrix inequalities (RLMIs) are developed to estimate the state and design the tracking controller at the same time. Finally, two simulation examples are exploited to illustrate the availability and flexibility of the proposed scheme. (C) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Automated summary

The study focuses on the probabilistic-constrained tracking control issue for a class of time-varying non-linear stochastic systems with sensor saturation, deception attacks, and limited bandwidth. It utilizes RLMIs to estimate the state and design the tracking controller while arranging the transmission order of measurements using the RR protocol.