Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Stall and spin recovery using optimal trajectory planning
Thesis (MEng)--Stellenbosch University, 2021.
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | en_ZA |
| Published: |
Stellenbosch : Stellenbosch University
2021
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867614128714022912 |
|---|---|
| access_status_str | Open Access |
| author | Babl, Martin Ludwig Dietrich |
| author2 | Engelbrecht, Jacobus Adriaan Albertus |
| author_browse | Babl, Martin Ludwig Dietrich Engelbrecht, Jacobus Adriaan Albertus |
| author_facet | Engelbrecht, Jacobus Adriaan Albertus Babl, Martin Ludwig Dietrich |
| author_sort | Babl, Martin Ludwig Dietrich |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MEng)--Stellenbosch University, 2021. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/110025 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:47:07.138Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/110025 Stall and spin recovery using optimal trajectory planning Babl, Martin Ludwig Dietrich Engelbrecht, Jacobus Adriaan Albertus Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. UCTD Flight control Trajectory optimization Airplanes -- Spin Airplanes -- Stalling Thesis (MEng)--Stellenbosch University, 2021. ENGLISH ABSTRACT: Aircraft pilots and autopilots would greatly benefit from a system that assists in recovering an aircraft after a severe flight upset such as a spin or stall. This system needs to perform the aerodynamic recovery that recovers the aircraft to its normal flight envelope. Once the aerodynamic recovery is completed the pilot or existing flight control system should perform the attitude, flight path angle, and airspeed recovery. Therefore, a stall and spin recovery system for aircraft using optimal trajectory planning is designed, implemented,and verified. A deep stall is a condition where an aircraft is trapped in a nose-high stall condition. While in a deep stall the aircraft’s elevator control surface cannot produce enough nose-down pitching moment to recover the aircraft from the stall. Spin is a condition where an aircraft naturally starts to rotate about the vertical axis after having stalled and follows a downward tight spiral trajectory. The NASA Generic Transport Model (GTM) is used as the basis for the design andverification of the system. The aerodynamic model of the NASA GTM simulation modelis modified to exhibit deep stall and spin behaviour. Simulations are performed to show that the modified aircraft model can be pushed into deep stall and spin, and cannot be recovered using elevator actions only. The deep stall and spin recovery task is formulated as an optimal control problem and solved using an A* and an RRT search algorithms.These algorithms find the optimal sequence of control actions and the resulting optimal state trajectory to escape from the deep stall or spin.The deep stall and spin recoveries are verified in simulation using the NASA GTM aircraft model. Simulation results show that the recovery sequences generated by the algorithms successfully perform the aerodynamic recovery. The deep stall recovery sequence first commands the rudder to yaw the horizontal tail plane out of the aircraft’s own wake to regain elevator effectiveness, and then commands the elevator to pitch the nose of the aircraft down and recover from the stall. The spin recovery sequence first commands the rudder to reduce the rolling and yawing angular rates and then commands the elevator to pitch the nose of the aircraft down. A trajectory regulator, in the form of a linear quadratic regulator(LQR), and a controls witch are implemented. The trajectory regulator provides robustness against external disturbances and model uncertainty. The control switch determines when the aircraft enter sa stall or spin condition and also when the aerodynamic envelope is recovered. The controls witch transfers the control authority of the aircraft from the deep stall or spin recovery system to the existing flight control or the pilot once the recovery is complete.General deep stall and spin recovery strategies were identified from the calculated recovery sequences. During a deep stall or spin recovery, it is possible to command the appropriate general recovery sequence and thereby nullify the calculation time required to plan the recovery sequence. When commanding the general recovery sequence the trajectory regulator regulates the state trajectories of the aircraft to track the planned general recovery state trajectories. The developed recovery system is successful in performing the aerodynamic recovery for the NASA GTM from both deep stall and spin conditions. AFRIKAANSE OPSOMMING: Hierdie tesis beskryf die ontwerp van ’n outomatiese deep stall en spin herstel stelsel vir groot transport vliegtuie wat van optimale baanbeplanning gerbuik maak. Deep stall is ’n toestand waar ’n vliegtuig vasgevang is in ’n neus-hoë stall toestand en die elevator beheeroppervlak kan nie genoeg neus-neer-trap-oomblik skep om die vliegtuig uit die stall te herstel nie. Spin is ’n toestand waar ’n vliegtuig natuurlik begin draai om ’n vertikale as en daan afwaarts in ’n stywe spiraalbaan val. Die NASA Generic Transport Model (GTM) word gebruik as basis vir die ontwerp en verifikasie van die stelsel. Die aërodinamiese model van die NASA GTM-simulasiemodel word aangepas om deep stall en spin gedrag te toon. Simulasies word uitgevoer om aantetoon dat die gemodifiseerde vliegtuigmodel kan deep stall en spin modelleer. In simulasie word dit getoon dat dit nie moontlik is om van deep stall en spin te herstel met die gebruik van net die elevator beheeroppervalk nie. Die taak vir die herstel van die deep stall en spin word geformuleer as ’n optimale beheerprobleem en opgelos met behulp van ’n A∗ soek algoritme om die optimale volgorde van beheeraksies en die gevolglike optimale toestandstrajek te vind om uit die deep stall of spin te ontsnap. Die A∗ -algoritme voer die beplanning uit met hulp van ’n vereenvoudigde drie-grade-van-vryheid (3DOF) vliegtuigmodel wat slegs die vinnige rotasie-dinamika van ’n deep stall modelleer. Die A∗ -algoritme en die RRT algoritme voer die beplanning vir spin herstel uit met hulp van ’n Volledige vliegtuigmodel van ses grade-van-vryheid (6DOF) wat die vinnige rotasie- en transnasionale dinamika van spin modelleer. Die outomatiese herstel van die deep stall en spin word dan in simulasie geverifieer met hulp van die volledige ses-grade-van-vryheid (6DOF) NASA GTM-vliegtuigmodel. Die simulasie-uitslae toon dat die stelsel die vliegtuig suksesvol van deep stall en spin kan herstel. Vir deep stall gebruik die optimale opeenvolging van beheeraksies eers die rudder beheeroppervlak om die horisontale stert vlakte uit die waak van die vliegtuig se hoofvlerke te skuif en dus hestel dit die effektiewetiet van die elevator beheeroppervalk. Die elevator beheeroppervlak word dan gebruik om die neus afwaarts te beweeg en dus van die stall te herstel. Om die robuustheid van hierdie deep stall en spin herstelsreekse te verbeter, word ’n optimale baanreguleerder ontwikkel om die herstel volgorde aantepas in die teenwoordigheid van versteurings. Die baanreguleerder gebruik lineêre kwadratiese beheer gekoppel met ’n skakel funksie wat bepaal wanneer die beheer van die vliegtuig terug na die normale vlugbeheer geplaas moet word. Vir demonstrasie is die normale vlugbeheer ’n proporsionele hoeksnelheids demper. Met die ontleding van die deep stall en spin herstel beheerreekse wat deur die algoritme vir baanbeplanning gegenereer is, is algemene herstelstrategieë van deep stall, links, en regs spin geïdentifiseer. Die algemene herstelstrategieë, gekombineer met die optimale baanreguleerder, sorg vir ’n betroubare deep stall en spin herstelstelsel. Masters 2021-02-24T15:57:55Z 2021-04-21T14:36:58Z 2021-02-24T15:57:55Z 2021-04-21T14:36:58Z 2021-03 Thesis http://hdl.handle.net/10019.1/110025 en_ZA Stellenbosch University 128 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | UCTD Flight control Trajectory optimization Airplanes -- Spin Airplanes -- Stalling Babl, Martin Ludwig Dietrich Stall and spin recovery using optimal trajectory planning |
| title | Stall and spin recovery using optimal trajectory planning |
| title_full | Stall and spin recovery using optimal trajectory planning |
| title_fullStr | Stall and spin recovery using optimal trajectory planning |
| title_full_unstemmed | Stall and spin recovery using optimal trajectory planning |
| title_short | Stall and spin recovery using optimal trajectory planning |
| title_sort | stall and spin recovery using optimal trajectory planning |
| topic | UCTD Flight control Trajectory optimization Airplanes -- Spin Airplanes -- Stalling |
| url | http://hdl.handle.net/10019.1/110025 |
| work_keys_str_mv | AT bablmartinludwigdietrich stallandspinrecoveryusingoptimaltrajectoryplanning |