Neural network-based control for RRP-based networked systems under DoS attacks with power interval

This paper is concerned with the optimal control problem for networked systems with the round-robin protocol (RRP) under the denial-of-service (DoS) attacker with power interval. In the literature, the control design is studied for the linear networked system subject to the DoS attacks with a known constant power or a known constant probability of data-packet dropouts. In this paper, the objective is to control the unknown nonlinear system in the communication network subject to the DoS attacks with a power interval and a time-varying probability of data-packet dropouts. The effects of the DoS attacks with power interval on a networked system under RRP are modeled accurately. A neural network (NN) -based observer is designed for the nonlinear system under the DoS attacks with power interval, and the relationship between the DoS attacker power interval and state estimation error is obtained. The NN actor–critic policy for the optimal control of the RRP-based networked system under the DoS attacks with power interval is found with adaptive dynamical programming, and stability of the resulting control system is analyzed. The proposed control method is demonstrated by a networked uninterruptible power supply system.