Projection-Based Online Parameter Estimation of a Tilt-Rotor VTOL Aircraft and Experimental ValidationSource: ASME Letters in Dynamic Systems and Control:;2026:;volume( 006 ):;issue:002::page 2395DOI: 10.1115/1.4070611Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Abstract. The vertical take-off and landing (VTOL) aircraft exhibit complex and rapidly varying dynamics during the transition flight phase, which poses significant challenges for accurate modeling and aerodynamic parameter estimation. This article presents a parameter estimation framework to identify unknown aerodynamic coefficients governing the transition flight, leveraging experimental flight data of a tilt-rotor VTOL unmanned aerial vehicle (UAV) in outdoor experiments. The VTOL UAV has a hybrid configuration with two tilting rotors, two static rotors, and fixed wings. A nonlinear dynamic model describing the longitudinal motion is developed and reformulated into a regression structure suitable for parameter estimation. A projection-based constrained recursive least-squares algorithm is then applied to estimate critical aerodynamic parameters, including lift, drag, and thrust coefficients, under physical constraints. The convergence and accuracy of estimation algorithm for time-varying coefficients are first verified by simulation. The parameter estimation is further validated by six experimental flight tests with different tilting rates of 12 deg/s and 14 deg/s. Experimental results demonstrate the accurate estimation by accurate predictions of the aircraft states vx, vz, ωy with root mean square error of 0.7230 m/s, 0.0990 m/s, and 0.0508 rad/s, respectively.
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| contributor author | He, Tianyi | |
| contributor author | Burton, Samantha | |
| contributor author | Spencer, Clayton | |
| contributor author | Wei, Wenpeng | |
| date accessioned | 2026-08-23T07:59:42Z | |
| date available | 2026-08-23T07:59:42Z | |
| date copyright | 2026/04/01 | |
| date issued | 2026 | |
| identifier issn | 2689-6117 | |
| identifier other | aldsc-25-1057.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4315917 | |
| description abstract | Abstract. The vertical take-off and landing (VTOL) aircraft exhibit complex and rapidly varying dynamics during the transition flight phase, which poses significant challenges for accurate modeling and aerodynamic parameter estimation. This article presents a parameter estimation framework to identify unknown aerodynamic coefficients governing the transition flight, leveraging experimental flight data of a tilt-rotor VTOL unmanned aerial vehicle (UAV) in outdoor experiments. The VTOL UAV has a hybrid configuration with two tilting rotors, two static rotors, and fixed wings. A nonlinear dynamic model describing the longitudinal motion is developed and reformulated into a regression structure suitable for parameter estimation. A projection-based constrained recursive least-squares algorithm is then applied to estimate critical aerodynamic parameters, including lift, drag, and thrust coefficients, under physical constraints. The convergence and accuracy of estimation algorithm for time-varying coefficients are first verified by simulation. The parameter estimation is further validated by six experimental flight tests with different tilting rates of 12 deg/s and 14 deg/s. Experimental results demonstrate the accurate estimation by accurate predictions of the aircraft states vx, vz, ωy with root mean square error of 0.7230 m/s, 0.0990 m/s, and 0.0508 rad/s, respectively. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Projection-Based Online Parameter Estimation of a Tilt-Rotor VTOL Aircraft and Experimental Validation | |
| type | Journal Paper | |
| journal volume | 6 | |
| journal issue | 2 | |
| journal title | ASME Letters in Dynamic Systems and Control | |
| identifier doi | 10.1115/1.4070611 | |
| journal fristpage | 2395 | |
| journal lastpage | 2409 | |
| page | 15 | |
| tree | ASME Letters in Dynamic Systems and Control:;2026:;volume( 006 ):;issue:002 | |
| contenttype | Fulltext |