Abstract
This paper describes a novel type of pendulum-like oscillation controller for micro air vehicle (MAV) hover and stare state in the presence of external disturbances, which is based on linear-quadratic regulator (LQR) and particle swarm optimization (PSO). A linear mathematical model of pendulum phenomenon based upon actual wind tunnel test data representing the hover mode is established, and a hybrid LQR and PSO approach is proposed to stabilize oscillation. PSO is applied to parameter optimization of the designed LQR controller. A series of comparative experiments are conducted, and the results have verified the feasibility, effectiveness and robustness of our proposed approach.
Similar content being viewed by others
References
Eric J, Michael T. Modeling, control, and flight testing of a small-ducted fan aircraft. J Guid, Contr, Dynam, 2006, 29: 769–779
Richard B. Latest unmanned vehicle show features both innovative new vehicles and miniaturization. Industr Robot Int J, 2009, 36: 13–18
Office of the Secretary of Defense. Unmanned aircraft systems roadmap 2005–2030. Washington DC, 2005
Duan H B, Shao S, Su B W, et al. New development thoughts on the bio-inspired intelligence based control for Unmanned Combat Aerial Vehicle. Sci China Tech Sci, 2010, 53: 2025–2031
Li P, Duan H B. Path planning of Unmanned Aerial Vehicle based on improved gravitational search algorithm. Sci China Tech Sci, 2012, 55: 2712–2719
Duan H B, Zhang X Y, Wu J, et al. Max-Min Adaptive ant colony optimization approach to multi-UAVs coordinated trajectory re-planning in dynamic and uncertain environments. J Bionic Eng, 2009, 6: 161–173
Christian S, Oliver M, Natalie F, et al. Using natural features for vision based navigation of an indoor-VTOL MAV. Aerosp Sci Tech, 2009, 13: 349–357
Tsai B J, Fu Y C. Design and aerodynamic analysis of a flapping-wing micro aerial vehicle. Aerosp Sci Tech, 2009, 13: 383–392
Thomas R, Mustapha O, Thierry L M. Longitudinal modeling and control of a flapping-wing micro aerial vehicle. Contr Eng Pract, 2010, 18: 679–690
Pflimlin J M, Binetti P, Soueres P, et al. Modeling and attitude control analysis of a ducted-fan micro aerial vehicle. Contr Eng Pract, 2010, 18: 209–218
Pu H Z, Zhen Z Y, Wang D B, et al. Improved particle swarm optimization algorithm for intelligently setting UAV attitude controller parameters. Trans Nanjing Univ Aeron & Astro, 2009, 26: 52–57
Pu H Z, Zhen Z Y, Wang D B. Modified shuffled frog leaping algorithm for optimization of UAV flight controller. Int J Int Comp Cybern, 2011, 4: 5–39
Osgar O, Paul G, Daniel I. Nondimensional modeling of ducted-fan aerodynamics. J Aircraft, 2012, 49: 126–140
Kennedy J, Eberhart R C. Particle swarm optimization. In: Proceedings of the 1995 IEEE International Conference on Neural Networks, Perth, Australia, 1995. 1942–1948
Shi Y H, Eberhart R C. Parameter selection in particle swarm optimization. Lect Note Comp Sci, 1998, 1447: 591–600
Gerhard V. Particle swarm optimization. In: Proceedings of the 43rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Denver, Colorado, 2002. 22–25
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Duan, H., Sun, C. Pendulum-like oscillation controller for micro aerial vehicle with ducted fan based on LQR and PSO. Sci. China Technol. Sci. 56, 423–429 (2013). https://doi.org/10.1007/s11431-012-5065-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11431-012-5065-5