CFMPC_Heli.pdf (676.95 kB)
Download fileExplicit non-linear model predictive control for autonomous helicopters
journal contribution
posted on 2012-12-12, 14:52 authored by Cunjia Liu, Wen-Hua Chen, J.D. AndrewsTrajectory tracking is a basic function required for autonomous helicopters, but it also poses challenges to control design due to the complexity of helicopter dynamics. This article introduces an explicit model predictive control (MPC) to solve this problem, which inherits the advantages of non-linear MPC but eliminates time-consuming online optimization. The explicit solution to the non-linear MPC problem is derived using Taylor expansion and exploiting the helicopter model. With the explicit MPC solution, the control signals can be calculated instantaneously to respond to the fast dynamics of helicopters and suppress disturbances immediately. On the other hand, the online optimization process can be removed from the MPC framework, which can accelerate the software development and simplify onboard hardware. Due to these advantages of the proposed method, the overall control framework has a low complexity and high reliability, and it is easy to deploy on small-scale helicopters. The proposed explicit non-linear MPC has been successfully validated in simulations and in actual flight tests using a Trex-250 small-scale helicopter.
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Citation
LIU, C., CHEN, W-H. and ANDREWS, J.D., 2012. Explicit non-linear model predictive control for autonomous helicopters. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 226 (9), pp. 1171 - 1182Publisher
Sage Publications © Institution of Mechanical Engineers (IMechE).Version
- AM (Accepted Manuscript)
Publication date
2012Notes
This article was published in Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering [© Sage and IMechE]. The definitive version is available from: http://dx.doi.org/10.1177/0954410011418585ISSN
0954-4100eISSN
2041-3025Publisher version
Language
- en