Attitude Control of a Class of Fixed-Wing UAV with Wiener Noises Based on Barrier Lyapunov Function

In this paper, stochastic system control method based on BLF is studied for unknown attitude control system of fixed wing UAV. By constructing a symmetric BLF, we can ensure that all states of the stochastic system do not exceed their constraint bounds, and then adopt Lyapunov stochastic control method to design the controller of the wiener noise system with uncertain difference. In addition, adaptive RBFNN approximation to unknown nonlinear continuous functions can effectively avoid the obstacles caused by unknown disturbances and random uncertainties. Finally, all control variables in the system are guaranteed to be bounded and the state variables are constrained in a bounded compact set. Simulation results verify the effectiveness of the proposed method, and better convergence speed and robustness are obtained by comparing with other methods.