Observer-based adaptive secure control for networked switched nonlinear systems under DoS attacks
Zhiyuan Zhang, Ning Zhao, Ben Niu, Xudong Zhao, Adil M. Ahmad
Abstract
This paper investigates an observer-based adaptive neural network (NN) secure control strategy for uncertain networked switched nonlinear systems under denial-of-service (DoS) attacks. In order to identify full state information of systems, an adaptive observer based on radial basis function NN is firstly built for estimating system states. Subsequently, a composite controller containing approximated nonlinear functions and estimated observer states is designed via backstepping method and NN approximation methods. By constructing appropriate Lyapunov functions and applying average dwell time theory, it is proved that the closed-loop system states are ultimately uniformly bounded by using the proposed control strategy. Eventually, simulation results further confirm the effectiveness of the developed control scheme.