TY - GEN
T1 - Hybrid Hierarchical Reinforcement Learning for Nonlinear Morphing Aircraft Control
AU - Ye, Bolun
AU - Peng, Quanjing
AU - Feng, Hao
AU - Cao, Fangfei
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2026
Y1 - 2026
N2 - Morphing aircraft can adjust geometric configuration during flight, which makes tracking control more difficult than in fixed configuration aircraft. To address this problem, a hierarchical framework integrating twin delayed deep deterministic policy gradient (TD3) algorithm and incremental nonlinear dynamic inversion (INDI) technique is proposed. The TD3 algorithm generates high-level decisions for the coupled loops, while the INDI technique performs fast actuator tracking at the lower layer. The design separates decision making from command execution and improves the coordination of the coupled control process during morphing. Meanwhile, a unified reward formulation is designed to guide policy learning toward accurate and stable control behavior. Simulation results show that the proposed framework achieves favorable performance in tracking accuracy, response smoothness, and coordination of the coupled system.
AB - Morphing aircraft can adjust geometric configuration during flight, which makes tracking control more difficult than in fixed configuration aircraft. To address this problem, a hierarchical framework integrating twin delayed deep deterministic policy gradient (TD3) algorithm and incremental nonlinear dynamic inversion (INDI) technique is proposed. The TD3 algorithm generates high-level decisions for the coupled loops, while the INDI technique performs fast actuator tracking at the lower layer. The design separates decision making from command execution and improves the coordination of the coupled control process during morphing. Meanwhile, a unified reward formulation is designed to guide policy learning toward accurate and stable control behavior. Simulation results show that the proposed framework achieves favorable performance in tracking accuracy, response smoothness, and coordination of the coupled system.
KW - Morphing aircraft
KW - flight control
KW - hierarchical control
KW - nonlinear systems
KW - reinforcement learning
UR - https://www.scopus.com/pages/publications/105045056665
U2 - 10.1109/CSIS-IAC70275.2026.11585035
DO - 10.1109/CSIS-IAC70275.2026.11585035
M3 - Conference contribution
AN - SCOPUS:105045056665
T3 - 2026 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2026
SP - 655
EP - 660
BT - 2026 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2026
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2026 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2026
Y2 - 15 May 2026 through 17 May 2026
ER -