Adaptive robust quantized path following control for the USV-UAV system

This paper presents a neural controller for the coordinated unmanned surface vehicle (USV)-unmanned aerial vehicle (UAV) system considering quantized input signals. In the guidance framework, the reference signals of the USV-UAV system can be derived from the virtual surface vehicle-virtual aerial vehicle (VSV-VAV). In order to reduce transmission load, an adaptive robust quantized controller is constructed based on the splendid approximation capability of the neural network. The hysteresis quantization segment the control signals to reduce undue wear of actuator. In order to tackle the gain of the actuator, novel parameter update laws are introduced. The stability of the close loop system is proved through Lyapunov function. Finally, a simulation experiment validates the robustness of the proposed path-following control scheme.