TY - JOUR
T1 - Neuroadaptive high-order fully-actuated system approach for roll autopilot with unknown uncertainties
AU - Wang, Wei
AU - Chen, Shiwei
AU - Shi, Zhongjiao
AU - Wang, Yuchen
N1 - Publisher Copyright:
© 2024
PY - 2024/12
Y1 - 2024/12
N2 - In this paper, a neuroadaptive high-order fully-actuated system approach control scheme incorporating the disturbance observer technique is proposed for the missile roll autopilot, subject to model uncertainties generated by the induced roll moment, along with actuator control efficiency deterioration and external disturbance. To address model uncertainties, the radial basis function neural network is implemented. The external disturbance and approximation error are treated as compound disturbances and estimated by a nonlinear disturbance. To avoid the “differential explosion” inherent in the backstepping technique, the high-order fully-actuated system approach is invoked to track the desired roll angle command. The semi-globally uniformly bounded of the closed-loop system is demonstrated via the Lyapunov method. Numerous simulations under various conditions have been conducted to verify the effectiveness of the proposed roll autopilot.
AB - In this paper, a neuroadaptive high-order fully-actuated system approach control scheme incorporating the disturbance observer technique is proposed for the missile roll autopilot, subject to model uncertainties generated by the induced roll moment, along with actuator control efficiency deterioration and external disturbance. To address model uncertainties, the radial basis function neural network is implemented. The external disturbance and approximation error are treated as compound disturbances and estimated by a nonlinear disturbance. To avoid the “differential explosion” inherent in the backstepping technique, the high-order fully-actuated system approach is invoked to track the desired roll angle command. The semi-globally uniformly bounded of the closed-loop system is demonstrated via the Lyapunov method. Numerous simulations under various conditions have been conducted to verify the effectiveness of the proposed roll autopilot.
KW - High-order fully actuated system
KW - Nonlinear disturbance observer
KW - Radial basis function neural network
KW - Roll autopilot
UR - http://www.scopus.com/inward/record.url?scp=85203437468&partnerID=8YFLogxK
U2 - 10.1016/j.ast.2024.109567
DO - 10.1016/j.ast.2024.109567
M3 - Article
AN - SCOPUS:85203437468
SN - 1270-9638
VL - 155
JO - Aerospace Science and Technology
JF - Aerospace Science and Technology
M1 - 109567
ER -