Incremental Nonlinear Reinforcement Learning Control for a Civil Aircraft with Model Uncertainties and Actuator Faults

Zhang, Qian; Lyu, Weizhi; Yang, Congjie; Chen, Jiaxin; Liu, Shiqian

doi:10.3390/aerospace13040315

Open AccessArticle

Incremental Nonlinear Reinforcement Learning Control for a Civil Aircraft with Model Uncertainties and Actuator Faults

by

Qian Zhang

,

Weizhi Lyu

,

Congjie Yang

,

Jiaxin Chen

and

Shiqian Liu

^*

The School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China

^*

Author to whom correspondence should be addressed.

Aerospace 2026, 13(4), 315; https://doi.org/10.3390/aerospace13040315

Submission received: 11 February 2026 / Revised: 24 March 2026 / Accepted: 25 March 2026 / Published: 27 March 2026

(This article belongs to the Special Issue Challenges and Innovations in Aircraft Flight Control (2nd Edition))

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Abstract

The problem of fault-tolerant attitude tracking control for the civil aircraft with model uncertainties and actuator faults is studied. A robust multiple inversion-based incremental nonlinear dynamic inversion (RMI-INDI) fault-tolerant control method is proposed for the problem. Firstly, considering that the higher-order term is neglected in the INDI method, an RMI method is proposed to deal with the higher-order term and model uncertainties of the INDI control. Secondly, to achieve the optimal control parameters for the INDI controller, a reinforcement learning (RL) method is suggested, where a Deep Deterministic Policy Gradient (DDPG) algorithm with a smooth reward function is designed. Finally, performances of the proposed RL-RMI-INDI fault-tolerant controller are demonstrated by using two scenario simulations. Compared with the SMC control, RMI-NDI control and INDI control without RL, tracking errors and overshoots are greatly reduced by the proposed RL-RMI-INDI controller for attitude tracking missions, even under model uncertainties and actuator faults.

Keywords: civil aircraft; incremental nonlinear dynamic inversion; reinforcement learning; fault-tolerant control; robust multiple inversion

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MDPI and ACS Style

Zhang, Q.; Lyu, W.; Yang, C.; Chen, J.; Liu, S. Incremental Nonlinear Reinforcement Learning Control for a Civil Aircraft with Model Uncertainties and Actuator Faults. Aerospace 2026, 13, 315. https://doi.org/10.3390/aerospace13040315

AMA Style

Zhang Q, Lyu W, Yang C, Chen J, Liu S. Incremental Nonlinear Reinforcement Learning Control for a Civil Aircraft with Model Uncertainties and Actuator Faults. Aerospace. 2026; 13(4):315. https://doi.org/10.3390/aerospace13040315

Chicago/Turabian Style

Zhang, Qian, Weizhi Lyu, Congjie Yang, Jiaxin Chen, and Shiqian Liu. 2026. "Incremental Nonlinear Reinforcement Learning Control for a Civil Aircraft with Model Uncertainties and Actuator Faults" Aerospace 13, no. 4: 315. https://doi.org/10.3390/aerospace13040315

APA Style

Zhang, Q., Lyu, W., Yang, C., Chen, J., & Liu, S. (2026). Incremental Nonlinear Reinforcement Learning Control for a Civil Aircraft with Model Uncertainties and Actuator Faults. Aerospace, 13(4), 315. https://doi.org/10.3390/aerospace13040315

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Incremental Nonlinear Reinforcement Learning Control for a Civil Aircraft with Model Uncertainties and Actuator Faults

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