Robust post-stall perching with a simple fixed-wing glider using LQR-Trees
Source abstract
Abstract
Birds routinely execute post-stall maneuvers with a speed and precision far beyond the capabilities of our best aircraft control systems. One remarkable example is a bird exploiting post-stall pressure drag in order to rapidly decelerate to land on a perch. Stall is typically associated with a loss of control authority, and it is tempting to attribute this agility of birds to the intricate morphology of the wings and tail, to their precision sensing apparatus, or their ability to perform thrust vectoring. Here we ask whether an extremely simple fixed-wing glider (no propeller) with only a single actuator in the tail is capable of landing precisely on a perch from a large range of initial conditions. To answer this question, we focus on the design of the flight control system; building upon previous work which used linear feedback control design based on quadratic regulators (LQR), we develop nonlinear feedback control based on nonlinear model-predictive control and 'LQR-Trees'. Through simulation using a flat-plate model of the glider, we find that both nonlinear methods are capable of achieving an accurate bird-like perching maneuver from a large range of initial conditions; the 'LQR-Trees' algorithm is particularly useful due to its low computational burden at runtime and its inherent performance guarantees. With this in mind, we then implement the 'LQR-Trees' algorithm on real hardware and demonstrate a 95 percent perching success rate over 147 flights for a wide range of initial speeds. These results suggest that, at least in the absence of significant disturbances like wind gusts, complex wing morphology and sensing are not strictly required to achieve accurate and robust perching even in the post-stall flow regime.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Aerospace and Aviation Technology · Target Tracking and Data Fusion in Sensor Networks · Adaptive Control of Nonlinear Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (44)
Show source-provided references
1. 10.2514/6.1995-36210.2514/6.1995-362 ↗
2. 10.1242/jeb.01041310.1242/jeb.010413 ↗
3. 10.1242/jeb.03810910.1242/jeb.038109 ↗
4. 10.2514/2.423110.2514/2.4231 ↗
5. 10.2514/6.2007-681810.2514/6.2007-6818 ↗
6. Carruthers A C · Aeronaut. J. · 2010 · 114 · 67310.1017/S0001924000004152 ↗
7. Carruthers A C · 45th AIAA Aerospace Sciences Meeting and Exhibit · 2007
8. 10.1242/jeb.01119710.1242/jeb.011197 ↗
9. Cory R · Proc. 2007 Symp. on Flying Insects and Robots (FIR) · 2007
10. 10.2514/6.2008-725610.2514/6.2008-7256 ↗
11. Cory R E · 2008
12. Dang T · IEEE Conf. on Decision and Control · 2008
13. Desbiens A L · IEEE Int. Conf. on Robotics and Automation (ICRA) · 2010
14. Donze A · Hybrid Systems: Computation and Control · 2007
15. 10.2514/6.2007-631810.2514/6.2007-6318 ↗
16. Gill P E · User's Guide for SNOPT Version 7: Software for Large-Scale Nonlinear Programming · 2006
17. Gillula J H · IEEE Int. Conf. on Robotics and Automation (ICRA) · 2010 · 1649
18. Green P R · J. Exp. Biol. · 1998 · 201 · 330910.1242/jeb.201.24.3309 ↗
19. Green W E · American Control Conf. · 2006
20. Lukens J M · Proc. 49th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conf. · 2008
21. Majumdar A · 2012
22. 10.1109/TAC.2005.85143910.1109/TAC.2005.851439 ↗
23. 10.2514/6.2009-195910.2514/6.2009-1959 ↗
24. Moore J · IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS) · 2011
25. Moore J · Proc. IEEE Conf. on Decision and Control · 2012
26. 10.1073/pnas.91.16.753410.1073/pnas.91.16.7534 ↗
27. Parrilo P A · 2000
28. Poole A · The Birds of North America Online · 2005
29. 10.1109/TAC.2003.82300010.1109/TAC.2003.823000 ↗
30. 10.1109/AERO.2001.93122010.1109/AERO.2001.931220 ↗
31. Reich G · 47th AIAA Aerospace Sciences Meeting · 2009
32. Roberts J W · Proc. American Control Conf. (ACC) · 2009
33. Seiler P · Proc. IEEE Conf. on Decision and Control · 2010 · 3337
34. Spong M · Proc. IEEE Int. Conf. on Intelligent Robots and Systems · 1994 · 31410.1109/IROS.1994.407375 ↗
35. Tan W · Allerton Conf. on Communication, Control and Computing · 2004 · 210
36. 10.2514/6.2005-59110.2514/6.2005-591 ↗
37. Tedrake R · Course Notes for MIT 6.832 (Working Draft Edition) · 2012
38. 10.1177/027836491036918910.1177/0278364910369189 ↗
39. Tobenkin M M · Proc. 18th IFAC World Congress · 2011
40. 10.1007/3-540-27167-8_310.1007/3-540-27167-8_3 ↗
41. von Stryk O · Users Guide For Dircol: A Direct Collocation Method For The Numerical Solution Of Optimal Control Problems · 1999
42. 10.2514/1.2019710.2514/1.20197 ↗
43. 10.2514/1.3381910.2514/1.33819 ↗
44. Wu F · Proc. American Control Conf. (June 2004) · 2004