Adaptive neural tracking control for high angle of attack maneuver with average dwell time

This article attempts to study the high angle of attack maneuver from the perspective of switched system control. In view of the complex aerodynamic characteristics, an improved longitudinal attitude motion model is presented, which is a switched stochastic nonstrict feedback nonlinear system with distributed delays. The significant design difficulty is the completely unknown diffusion and drift terms and distributed delays with all state variables. Based on a technical lemma and neural networks, an improved smooth state feedback control law for nonstrict feedback systems is proposed without any growth assumptions. To eliminate the influence of distributed delays, an improved Lyapunov-Krasovskii function is constructed, which skillfully removes the constraint of the upper bound of the delay change rate. Then, by combining the average dwell-time scheme and stochastic backstepping technique, an adaptive neural network tracking control law is designed, which extends a newly proposed switched system stability condition to the stochastic switched system. Theoretical analysis and flight control simulation experiments are provided to illustrate the effectiveness of the proposed control method.

Automated summary

This article proposes a study on high angle of attack maneuver from the perspective of switched system control, presenting an improved longitudinal attitude motion model and control method to address the design difficulties caused by complex aerodynamic characteristics. The proposed smooth state feedback control for nonstrict feedback systems successfully eliminates the influence of distributed delays, showcasing its effectiveness through theoretical analysis and flight control simulation experiments.