Wang, C.; Xie, W.; Gao, J.; Wu, P.; Liu, P.X. Adaptive Event-Based Dynamic Output Feedback Control for Unmanned Marine Vehicle Systems under Denial-of-Service Attack. Electronics2024, 13, 515.
Wang, C.; Xie, W.; Gao, J.; Wu, P.; Liu, P.X. Adaptive Event-Based Dynamic Output Feedback Control for Unmanned Marine Vehicle Systems under Denial-of-Service Attack. Electronics 2024, 13, 515.
Wang, C.; Xie, W.; Gao, J.; Wu, P.; Liu, P.X. Adaptive Event-Based Dynamic Output Feedback Control for Unmanned Marine Vehicle Systems under Denial-of-Service Attack. Electronics2024, 13, 515.
Wang, C.; Xie, W.; Gao, J.; Wu, P.; Liu, P.X. Adaptive Event-Based Dynamic Output Feedback Control for Unmanned Marine Vehicle Systems under Denial-of-Service Attack. Electronics 2024, 13, 515.
Abstract
An event-based dynamic output feedback control (DOFC) strategy for unmanned marine vehicle (UMV) systems is concerned. The whole UMV systems are composed of an UMV closed-loop system, a land-based control unit and the communication network. To increase the effectiveness of data transmission in the network channel and better enable the control unit against attack, an adaptive event-triggered mechanism (AETM) is applied. Moreover, a quantizer is installed between the sampler and the control unit. The quantizer further reduces the communication burden. The occurrence of aperiodic denial-of-service (DoS) attack is considered in the channel from the control unit to the UMV system. Sufficient criterion for ensuring global exponential stability of system with an expected H∞ disturbance attenuation index is obtained. Co-design of the dynamic output feedback controller and the AETM is derived. The effectiveness of the proposed approach is verified in the given illustrative simulation. The simulation results indicate that the reduction percentages of yaw angle amplitudes and yaw velocity accumulative error of the UMV system with the control strategy proposed in this paper are 43.2%and 45.9%, respectively, which are 0.3% and 5.8% improvement in both metrics compared to the previously published work.
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