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Stall Recovery Guidance Using Fast Model Predictive Control
Author(s) -
Stefan Schuet,
Thomas Lombaerts,
John Kaneshige,
Kimberlee H. Shish,
Vahram Stepanyan
Publication year - 2017
Publication title -
aiaa guidance, navigation and control conference
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2017-1513
Subject(s) - stall (fluid mechanics) , model predictive control , computer science , control theory (sociology) , control (management) , engineering , artificial intelligence , aerospace engineering
Based on a detailed analysis of recent loss-of-control events, the Aircraft State Awareness Joint Safety Analysis Team has identified the need to develop algorithms and display strategies to provide control guidance for recovery from approach-to-stall or stall. In order to be effective, such guidance should enhance the pilot’s ability to execute the Federal Aviation Administration’s recommended stall recovery procedure. This paper explores the use of a fast model predictive control algorithm that determines near optimal recovery guidance, which quantifies the aircraft configuration and situation dependent recovery information required to maximize the effectiveness of the recovery. This information includes the magnitude of the initial pitch down maneuver, the specific amount of airspeed and thrust needed before pulling out of the recovery dive, as well as the maximum pitch-up rate that can be sustained without causing a secondary stall. The algorithm was integrated and tested with an in-house desktop simulator that implements the General Transport Aircraft model and the associated stall aircraft dynamics. Preliminary results are presented to demonstrate the use of the proposed approach as a recovery aid for pilots.

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