Receding horizon control of a 3 DOF helicopter using online estimation of aerodynamic parameters
This study presents a numerical implementation of fast nonlinear model predictive control (NMPC) and nonlinear moving horizon estimation (NMHE) for the trajectory tracking problem of a 3 degree of freedom (DOF) helicopter. The motivation behind using the NMPC instead of its linear counterpart is tha...
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sg-ntu-dr.10356-1433972020-08-31T01:59:32Z Receding horizon control of a 3 DOF helicopter using online estimation of aerodynamic parameters Mehndiratta, Mohit Kayacan, Erdal School of Mechanical and Aerospace Engineering Singapore Centre for 3D Printing Engineering::Mechanical engineering::Robots Engineering::Mechanical engineering::Control engineering Unmanned Aerial Vehicles Quanser 3 Degree of Freedom Helicopter This study presents a numerical implementation of fast nonlinear model predictive control (NMPC) and nonlinear moving horizon estimation (NMHE) for the trajectory tracking problem of a 3 degree of freedom (DOF) helicopter. The motivation behind using the NMPC instead of its linear counterpart is that the helicopter is operated over nonlinear regions. Moreover, this system has cross-couplings that make the control of the system even more complicated. What is more, according to our simulation scenario, the system has a time-varying dynamical model because it has time-varying parameters which are estimated online using NMHE and the extended Kalman filter (EKF) throughout the control. Although NMHE is computationally more demanding, its capability of incorporating the constraints encourages us to utilize NMHE rather than EKF. Two reference trajectories, namely, sinusoidal and square-like, are tracked, and owing to the better learning capability of NMHE over EKF, the NMPC-NMHE closed-loop control framework is able to track both reference signals with more accuracy than the NMPC-EKF control framework, even under parameter uncertainties. Thanks to the ACADO toolkit, the combined average execution time is 4 milliseconds, demonstrating the potential of the proposed framework for real-time aerospace applications using relatively cheaper processors. Ministry of Education (MOE) Accepted version This work was financially supported by the Singapore Ministry of Education (RG191/14) and Singapore Center for 3D Printing. 2020-08-31T01:59:31Z 2020-08-31T01:59:31Z 2018 Journal Article Mehndiratta, M., & Kayacan, E. (2018). Receding horizon control of a 3 DOF helicopter using online estimation of aerodynamic parameters. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 232(8), 1442-1453. doi:10.1177/0954410017703414 0954-4100 https://hdl.handle.net/10356/143397 10.1177/0954410017703414 2-s2.0-85042880847 8 232 1442 1453 en Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering © 2018 Institution of Mechanical Engineers (IMechE). All rights reserved. This paper was published in Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering and is made available with permission of Institution of Mechanical Engineers (IMechE). application/pdf |
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Engineering::Mechanical engineering::Robots Engineering::Mechanical engineering::Control engineering Unmanned Aerial Vehicles Quanser 3 Degree of Freedom Helicopter Mehndiratta, Mohit Kayacan, Erdal Receding horizon control of a 3 DOF helicopter using online estimation of aerodynamic parameters |
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This study presents a numerical implementation of fast nonlinear model predictive control (NMPC) and nonlinear moving horizon estimation (NMHE) for the trajectory tracking problem of a 3 degree of freedom (DOF) helicopter. The motivation behind using the NMPC instead of its linear counterpart is that the helicopter is operated over nonlinear regions. Moreover, this system has cross-couplings that make the control of the system even more complicated. What is more, according to our simulation scenario, the system has a time-varying dynamical model because it has time-varying parameters which are estimated online using NMHE and the extended Kalman filter (EKF) throughout the control. Although NMHE is computationally more demanding, its capability of incorporating the constraints encourages us to utilize NMHE rather than EKF. Two reference trajectories, namely, sinusoidal and square-like, are tracked, and owing to the better learning capability of NMHE over EKF, the NMPC-NMHE closed-loop control framework is able to track both reference signals with more accuracy than the NMPC-EKF control framework, even under parameter uncertainties. Thanks to the ACADO toolkit, the combined average execution time is 4 milliseconds, demonstrating the potential of the proposed framework for real-time aerospace applications using relatively cheaper processors. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Mehndiratta, Mohit Kayacan, Erdal |
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Article |
author |
Mehndiratta, Mohit Kayacan, Erdal |
author_sort |
Mehndiratta, Mohit |
title |
Receding horizon control of a 3 DOF helicopter using online estimation of aerodynamic parameters |
title_short |
Receding horizon control of a 3 DOF helicopter using online estimation of aerodynamic parameters |
title_full |
Receding horizon control of a 3 DOF helicopter using online estimation of aerodynamic parameters |
title_fullStr |
Receding horizon control of a 3 DOF helicopter using online estimation of aerodynamic parameters |
title_full_unstemmed |
Receding horizon control of a 3 DOF helicopter using online estimation of aerodynamic parameters |
title_sort |
receding horizon control of a 3 dof helicopter using online estimation of aerodynamic parameters |
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2020 |
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https://hdl.handle.net/10356/143397 |
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1681059403215667200 |