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Reinforcement learning-adaptive fault-tolerant IGC method for a class of aircraft with non-affine characteristics and multiple uncertainties

Published online by Cambridge University Press:  05 November 2024

Z. Wang
Affiliation:
Research Center for Unmanned System Strategy Development, Northwestern Polytechnical University, Xi’an, Shaanxi, China National Key Laboratory of Aerospace Flight Dynamics, Northwestern Polytechnical University, Xi’an, Shaanxi, China Northwest Institute of Mechanical and Electrical Engineering, Xianyang, China Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an, Shaanxi, China
Y. T. Hao*
Affiliation:
Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an, Shaanxi, China
J. L. Liu
Affiliation:
Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an, Shaanxi, China
Y. F. Bai
Affiliation:
China Academy of Launch Vehicle Technology, Beijing, China
D. X. Yu
Affiliation:
School of Artificial Intelligence, OPtics and ElectroNlics (iOPEN), Northwestern Polytechnical University, Xi’an, Shaanxi, China
*
Corresponding author: Y. T. Hao; Email: yuting_hao10@163.com

Abstract

In this paper, a brand-new adaptive fault-tolerant non-affine integrated guidance and control method based on reinforcement learning is proposed for a class of skid-to-turn (STT) missile. Firstly, considering the non-affine characteristics of the missile, a new non-affine integrated guidance and control (NAIGC) design model is constructed. For the NAIGC system, an adaptive expansion integral system is introduced to address the issue of challenging control brought on by the non-affine form of the control signal. Subsequently, the hyperbolic tangent function and adaptive boundary estimation are utilised to lessen the jitter due to disturbances in the control system and the deviation caused by actuator failures while taking into account the uncertainty in the NAIGC system. Importantly, actor-critic is introduced into the control framework, where the actor network aims to deal with the multiple uncertainties of the subsystem and generate the control input based on the critic results. Eventually, not only is the stability of the NAIGC closed-loop system demonstrated using Lyapunov theory, but also the validity and superiority of the method are verified by numerical simulations.

Information

Type
Research Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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