{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T09:31:14Z","timestamp":1793525474546,"version":"4.5.0"},"reference-count":31,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T00:00:00Z","timestamp":1704931200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Aerospace"],"abstract":"<jats:p>The upset state is an unexpected flight state, which is characterized by an unintentional deviation from normal operating parameters. It is difficult for the pilot to recover the aircraft from the upset state accurately and quickly. In this paper, an upset recovery strategy and pilot assistance system (PAS) based on reinforcement learning is proposed. The man\u2013machine closed-loop system was established and the upset state, such as a high angle of attack and large attitude angle, was induced. The upset recovery problem was transformed into a sequential decision problem, and the Markov decision model of upset recovery was established by taking the deflection change of the control surface as the action. The proximal policy optimization (PPO) algorithm was selected for the strategy training. The adaptive pilot model and the reinforcement learning method proposed in this paper were used to make the aircraft recover from the upset state. Based on the correspondence between the flight state, the recovery method, and the recovery result, the aircraft upset recovery safety envelopes were formed, and the four-level upset recovery PAS with alarm warning, coordinated control, and autonomous recovery modes was constructed. The results of the digital virtual flight simulation and ground flight test show that compared with a traditional single pilot, the aircraft upset recovery strategy, the upset recovery safety envelopes, and the PAS established in this study could reduce the handling burden of the pilot and improve the success rate and effect of upset recovery. This research has certain theoretical reference values for flight safety and pilot training.<\/jats:p>","DOI":"10.3390\/aerospace11010070","type":"journal-article","created":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T05:24:12Z","timestamp":1704950652000},"page":"70","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Aircraft Upset Recovery Strategy and Pilot Assistance System Based on Reinforcement Learning"],"prefix":"10.3390","volume":"11","author":[{"given":"Jin","family":"Wang","sequence":"first","affiliation":[{"name":"School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Zhao","sequence":"additional","affiliation":[{"name":"Chinese Flight Test Establishment, Xi\u2019an 710000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhe","family":"Zhang","sequence":"additional","affiliation":[{"name":"Chinese Flight Test Establishment, Xi\u2019an 710000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ting","family":"Yue","sequence":"additional","affiliation":[{"name":"School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1643-931X","authenticated-orcid":false,"given":"Hailiang","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lixin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,11]]},"reference":[{"key":"ref_1","unstructured":"ICAO (2014). Manual on Aeroplane Upset Prevention and Recovery Training, ICAO."},{"key":"ref_2","unstructured":"Martin, E. (2023). Statistical Summary of Commercial Jet Airplane Accidents Worldwide Operations 1959\u20132022, Airbus."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Jones, S.M., and Reveley, M. (2003, January 17\u201319). An Overview of the NASA Aviation Safety Program Assessment Process. Proceedings of the AIAA\u2019s 3rd Annual Aviation Technology, Integration, and Operations (ATIO) Forum, Denver, CO, USA.","DOI":"10.2514\/6.2003-6706"},{"key":"ref_4","unstructured":"AURTA (2024, January 04). Airplane Upset Prevention and Recovery Training Aid 3.0. Available online: https:\/\/www.icao.int\/safety\/loci\/auprta\/index.html."},{"key":"ref_5","unstructured":"FAA (2015). Upset Prevention and Recovery Training, FAA."},{"key":"ref_6","unstructured":"CAAC (2024, January 04). Aircraft Pilot Training Guide\u2014Upset Prevention and Recovery Training (UPRT). Available online: https:\/\/apstraining.com\/wp-content\/uploads\/2020\/05\/APS-UPRT-Online-Study-Guide.pdf."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Wilborn, J., and Foster, J. (2004, January 16\u201319). Defining Commercial Transport Loss-of-Control: A Quantitative Approach. Proceedings of the AIAA Atmospheric Flight Mechanics Conference and Exhibit, Providence, RI, USA.","DOI":"10.2514\/6.2004-4811"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"863","DOI":"10.2514\/1.G001728","article-title":"Design of a Flight Envelope Protection System for NASA\u2019s Transport Class Model","volume":"40","author":"Tekles","year":"2017","journal-title":"J. Guid. Control Dyn."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"847","DOI":"10.2514\/1.G001729","article-title":"Autonomous Flight Envelope Estimation for Loss-of-Control Prevention","volume":"40","author":"Schuet","year":"2017","journal-title":"J. Guid. Control Dyn."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1461","DOI":"10.1016\/j.cja.2018.05.006","article-title":"Envelope protection for aircraft encountering upset condition based on dynamic envelope enlargement","volume":"31","author":"Zheng","year":"2018","journal-title":"Chin. J. Aeronaut."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Engelbrecht, J.A., Pauck, S.J., and Peddle, I.K. (2013, January 19\u201322). A Multi-Mode Upset Recovery Flight Control System for Large Transport Aircraft. Proceedings of the AIAA Guidance, Navigation, and Control (GNC) Conference, Boston, MA, USA.","DOI":"10.2514\/6.2013-5172"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Dongmo, J.-E. (2012, January 13\u201316). Aircraft Loss-Of-Control Recovery Using Feedback Linearization and High Order Sliding Mode Control. Proceedings of the AIAA Guidance, Navigation, and Control Conference, Minneapolis, MN, USA.","DOI":"10.2514\/6.2012-4548"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2055","DOI":"10.2514\/1.G004180","article-title":"Switching Control Architecture with Parametric Optimization for Aircraft Upset Recovery","volume":"42","author":"Yildiz","year":"2019","journal-title":"J. Guid. Control Dyn."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"920","DOI":"10.2514\/1.G001738","article-title":"Vehicle Upset Detection and Recovery for Onboard Guidance and Control","volume":"40","author":"Richards","year":"2017","journal-title":"J. Guid. Control Dyn."},{"key":"ref_15","first-page":"1492","article-title":"Aircraft Spin Recovery, with and without Thrust Vectoring","volume":"42","author":"Raghavendra","year":"2005","journal-title":"Using Nonlinear Dyn. Invers."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.2514\/1.58028","article-title":"Guidance and Control of Airplanes Under Actuator Failures and Severe Structural Damage","volume":"36","author":"Chowdhary","year":"2013","journal-title":"J. Guid. Control Dyn."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1016\/j.engappai.2017.08.014","article-title":"Proof of concept simulator demonstration of a physics based self-preserving flight envelope protection algorithm","volume":"67","author":"Lombaerts","year":"2018","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1076","DOI":"10.2514\/1.G001739","article-title":"Reinforcement Learning-Based Optimal Flat Spin Recovery for Unmanned Aerial Vehicle","volume":"40","author":"Kim","year":"2017","journal-title":"J. Guid. Control Dyn."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wang, L., Wang, J., Liu, H., and Yue, T. (2023). Decision-Making Strategies for Close-Range Air Combat Based on Reinforcement Learning with Variable-Scale Actions. Aerospace, 10.","DOI":"10.3390\/aerospace10050401"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.cja.2021.03.015","article-title":"Study on the resolution of multi-aircraft flight conflicts based on an IDQN","volume":"35","author":"Sui","year":"2022","journal-title":"Chin. J. Aeronaut."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.cja.2020.12.027","article-title":"Relevant experience learning: A deep reinforcement learning method for UAV autonomous motion planning in complex unknown environments","volume":"34","author":"Hu","year":"2021","journal-title":"Chin. J. Aeronaut."},{"key":"ref_22","first-page":"11","article-title":"Twin-delayed deep deterministic policy gradient algorithm for the energy management of microgrids","volume":"125","year":"2023","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.engappai.2023.106941","article-title":"A deep reinforcement learning algorithm to control a two-wheeled scooter with a humanoid robot","volume":"126","author":"Baltes","year":"2023","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_24","unstructured":"Hueschen, R.M. (2011). Development of the Transport Class Model (TCM) Aircraft Simulation from a Sub-Scale Generic Transport Model (GTM) Simulation, NASA."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Foster, J., Cunningham, K., Fremaux, C., Shah, G., Stewart, E., Rivers, R., Wilborn, J., and Gato, W. (2005, January 15\u201318). Dynamics Modeling and Simulation of Large Transport Airplanes in Upset Conditions. Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, San Francisco, CA, USA.","DOI":"10.2514\/6.2005-5933"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1080\/00207179408923072","article-title":"Fly-by-wire for commercial aircraft: The Airbus experience","volume":"59","author":"Favre","year":"1994","journal-title":"Int. J. Control"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1016\/S1270-9638(99)00107-8","article-title":"Active sidestick technology\u2014A means for improving situational awareness","volume":"3","author":"Hanke","year":"1999","journal-title":"Aerosp. Sci. Technol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"760","DOI":"10.2514\/1.40645","article-title":"Analytical Assessment of Flight Simulator Fidelity Using Pilot Models","volume":"32","author":"Hess","year":"2009","journal-title":"J. Guid. Control Dyn."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1243\/09544100JAERO33","article-title":"Simplified approach for modelling pilot pursuit control behaviour in multi-loop flight control tasks","volume":"220","author":"Hess","year":"2006","journal-title":"Proc. Inst. Mech. Eng. Part G J. Aerosp. Eng."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Jordan, T., Foster, J., and Bailey, R. (2006, January 5\u20138). AirSTAR: A UAV Platform for Flight Dynamics and Control System Testing. Proceedings of the 25th AIAA Aerodynamic Measurement Technology and Ground Testing Conference, San Francisco, CA, USA.","DOI":"10.2514\/6.2006-3307"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"515","DOI":"10.2514\/3.20142","article-title":"Handling qualities and pilot evaluation","volume":"9","author":"Harper","year":"1986","journal-title":"J. Guid. Control Dyn."}],"container-title":["Aerospace"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2226-4310\/11\/1\/70\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:44:35Z","timestamp":1760103875000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2226-4310\/11\/1\/70"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,11]]},"references-count":31,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["aerospace11010070"],"URL":"https:\/\/doi.org\/10.3390\/aerospace11010070","relation":{},"ISSN":["2226-4310"],"issn-type":[{"value":"2226-4310","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,11]]}}}