Fuzzy Trajectory Tracking Control of Under-Actuated Unmanned Surface Vehicles With Ocean Current and Input Quantization
针对欠驱动无人水面艇在未知海流和输入量化下的轨迹跟踪问题，提出了基于扩展状态观测器的制导律和事件触发自适应模糊量化控制律，减少了通信负担并通过仿真验证了有效性。
This article focuses on the trajectory tracking control of under-actuated unmanned surface vehicles subject to unknown ocean current and input quantization. Regarding kinematics, we devise an extended-state-observer-based guidance law capable of compensating for ocean currents to track the intended trajectory. Concerning kinetics, we propose an event-triggered adaptive fuzzy quantization control law using a linear analytical model to depict input quantization, eliminating the need for prior quantization parameter information. A notable aspect is the reduction in both execution frequency and magnitude, thereby mitigating communication burdens. The stability of this control strategy is proofed through input-to-state stability analysis. Simulation experiments are conducted to affirm the viability of the event-triggered adaptive fuzzy quantization control strategy.