Dynamic‐Memory Event‐Triggered‐Based Optimal 3D Path‐Following Control for AUV Systems Under Sparse Sensor Attacks

ABSTRACT This paper designs an optimal three‐dimensional path‐following control scheme for the underactuated autonomous underwater vehicle (AUV) incorporating a novel dynamic memory event‐triggered mechanism (DMETM) against sparse sensor attacks. To address system state measurement errors and disturbances caused by sparse sensor attacks leading to a decrease in control effectiveness, an improved estimation algorithm is proposed, which can estimate the outputs of sensors under attacks and reduce the impact of disturbances. In order to reduce the impact of unqualified data on AUV system performance, based on the improved estimation algorithm, additional judging conditions are introduced in DMETM ensuring the accuracy of triggers. The results of stability analysis show all signals in the AUV system are bounded. Finally, some simulation results display the effectiveness of the proposed control scheme.