A3C-Based Intelligent Event-Triggering Control of Networked Nonlinear Unmanned Marine Vehicles Subject to Hybrid Attacks

• Published in: IEEE transactions on intelligent transportation systems Vol. 23; no. 8; pp. 12921 - 12934
• Main Authors: Ye, Zehua, Zhang, Dan, Wu, Zheng-Guang, Yan, Huaicheng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: A3C algorithm; Control systems design; deception attack; DoS attack; Feedback control; Hybrid systems; intelligent event-triggering; Marine vehicles; Mathematical models; Nonlinear control; Nonlinear dynamical systems; Nonlinear systems; Nonlinear UMV system; Robust control; Stability analysis; Surges; Systems analysis; T-S fuzzy systems; Uncertainty; Unmanned vehicles; Vehicle dynamics
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2021.3118648

This paper is concerned with the intelligent event-triggering-based positioning control of networked unmanned marine vehicle (UMV) systems with hybrid attacks, where the UMV and control station is connected by a communication network and the DoS attack and Deception attack are studied. Firstly, a stochastic switched Takagi-Sugeno (T-S) fuzzy system model is proposed for the networked nonlinear UMV systems subject to aperiodic DoS attack and random Deception attack. Then, a novel asynchronous advantage actor-critic (A3C) learning-based event-triggering approach is introduced to alleviate the communication load. By using the Lyapunov stability theory and switched system analysis method, the mean-square exponential stability condition of the closed-loop system and the design method of observer-based controller are devised. Finally, an example of a networked UMV system is given to verify the effectiveness of the proposed resilient control strategy.