Observer-Based Adaptive Attack Reconstruction for a Class of Uncertain Systems

This paper investigates the attack detection and reconstruction problem for a class of nonlinear systems with unknown parameters and actuator/state attacks. An adaptive sliding mode observer with online parameter estimation is designed to estimate the states and the convergence of estimation errors is guaranteed. By analyzing the features of adaptive sliding mode observers, an attack detection and reconstruction scheme is proposed. It is shown that the reconstruction signal can approximate the attack with any accuracy under a persistent excitation condition. Finally, simulation results are given to verify the effectiveness of the proposed scheme.