Research on a Supervisory Shared Control Strategy for Aircraft Based on CFM

• Published in: Chinese Control and Decision Conference pp. 6485 - 6492
• Main Authors: Song, Wanghang, Fan, Xue, Xie, Rong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 16.05.2025
• Subjects: Accuracy; Adaptation models; Adaptive control; Aerospace control; Aircraft; Capability for Maneuvering (CFM); Control surface failure; Customer relationship management; Indexes; Model Reference Adaptive Control; Shared Control; Stability criteria; Supervisory control; Trajectory tracking
• ISSN: 1948-9447
• DOI: 10.1109/CCDC65474.2025.11090542

This study conducts an in-depth investigation into the impact of control surface efficiency loss on flight trajectory tracking accuracy and flight stability. An elastic supervisory control strategy based on maneuverability (CfM) is proposed, with its core comprising an improved model reference adaptive controller (CRM adaptive controller). Additionally, a CfM index is designed to quantify flight state characteristics, assisting pilots in real-time monitoring of system status and anomalies. By introducing the CfM index and CRM adaptive controller, combined with an elastic supervisory shared control strategy, the approach integrates automated control with active pilot supervision to address the adaptive control challenges under conditions of control surface efficiency loss, achieving a better balance between automation and human-machine interaction. Although this method introduces additional computational steps, such as online parameter updates and human-machine feedback, in the algorithm design, theoretical analysis indicates that its computational complexity only exhibits linear growth, enabling efficient operation under existing flight control hardware conditions. Simulation verification based on the F-16 aircraft demonstrates that the CfM index and CRM adaptive controller significantly improve trajectory tracking accuracy, system stability, and anti-disturbance capability, showing distinct advantages over traditional methods.