Event-Sampled Output Feedback Auto-berthing Control of Underactuated Vessels

This work addresses the auto-berthing control problem of the underactuated vessel where the sensor-controller channel is subject to FDI attacks. An event-sampled-based adaptive neural network state observer is designed to inhibit FDI attack signals from entering the closed-loop system. By means of the differential homeomorphism transformation, an equivalent motion model of the underactuated vessel considering FDI attacks is established. To further reduce the network resource consumption, an event-triggered mechanism is established in the control-actuator channel. On this basis, an event-sampled output feedback auto-berthing control scheme is designed. The Lyapunov-based stability theory analyses and demonstrates that all signals of the closed-loop system are bounded. Meanwhile, the comparison of simulation experiments verifies that the developed control scheme is effective and practicable.