Abstract:

To address the limitations of fixed positions in traditional underactuated surface vessel-unmanned aerial vehicle （USV-UAV） search tasks, as well as issues such as frequent chattering of control inputs and uncertainty model nonlinear parameters in the control system, an event-triggered control algorithm for the USV-UAV based on the asynchronous search guidance is proposed. Firstly, an asynchronous search guidance method is designed, which uses an L₁-based virtual surface vessel （L₁VV） and an L₁-based virtual unmanned aerial vehicle （L₁VA） to generate guidance paths that satisfy the search requirements. Secondly, the radius based function neural network （RBF-NN） is introduced combined with the minimal learning parameter （MLP） method to approximate and simplify the nonlinear terms of unknown model parameters of the system. In the design of control laws, dynamic event-triggered control with a disturbance compensation mechanism is applied to achieve the accuracy and reduce the update frequency of control input. Finally, the proposed control algorithm is proved that satisfies the semi-global uniform ultimate bounded stability by using Lyapunov stability theory, and its effectiveness is further validated through simulation experiments.

Key words: underactuated surface vessel-unmanned aerial vehicle （USV-UAV）, maritime search, radius based function neural network （RBF-NN）, event-triggered control