Three-dimension path planning and trajectory tracking control for quadrotor unmanned aerial vehicle

被引：4

作者：

Fang, Xu ^{[1
]}

Liu, Jin-Kun ^{[1
]}

机构：

[1] School of Automation Science and Electrical Engineering, Beihang University, Beijing

来源：

Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2015年 / 32卷 / 08期

关键词：

Artificial potential field; Asymptotic stability; Control algorithms; Path planning; Quadrotor unmanned aerial vehicles; Space circle interpolation;

D O I：

10.7641/CTA.2015.50049

中图分类号：

学科分类号：

摘要：

Path planning of unmanned aerial vehicle (UAV) is to design a reasonable path which satisfies task requirements according to the distribution of terrains and threats. In order to meet three-dimension rapid path planning requirements, a three-dimension path planning method based on artificial potential filed is proposed. Firstly, the virtual force functions of goal and threats are defined, and three-dimension parameter constraint equations are deduced. The concept of combination of threats is proposed by us to deal with the space local minimal problem and the oscillation problem. Secondly, space circle interpolation is introduced to generate the smooth path. Besides, the time domain method for planning the smooth path is employed because it is convenient to UAV path tracking control. Finally, By virtue of global asymptotic stability theory, a closed-loop system that is global Lipschitz is designed, which guarantees the strict overall stability tracking control in the internal and the external loop. Simulations results validate the designed performance of path planning method and tracking control. ©, 2015, South China University of Technology. All right reserved.

引用

页码：1120 / 1128

页数：8

共 12 条

[1] Su J., Zhang R., Wang X., Et al., Controlling a four-rotor aircraft based on noise-attenuation differentiator, Control Theory & Applications, 26, 8, pp. 827-832, (2009)
[2] Lee D.B., Nataraj C., Burg T.C., Et al., Adaptive tracking control of an underactuated aerial vehicle, 2011 American Control Conference, 7, pp. 2326-2331, (2011)
[3] Takahashi O., Schilling R.J., Motion planning in a plane using generalized Voronoi diagrams, IEEE Transactions on Robotics and Automation, 5, 2, pp. 143-150, (1989)
[4] Kavraki L.E., Svestka P., Latombe J.C., Et al., Probabilistic roadmaps for path planning in high-dimensional configuration spaces, IEEE Transactions on Robotics and Automation, 12, 4, pp. 566-580, (1996)
[5] Higashino S., Kim J., Kuroyanagi S., Et al., Hierarchical flight management and control of autonomous UAVs based on evolutionary computation and total energy concept, AIAA 3rd Unmanned Unlimited Technical Conference, Workshop and Exhibit, 9, pp. 1-11, (2004)
[6] Richards N.D., Sharma M., Ward D.G., A hybrid A*/automation approach to online path planning with obstacle avoidance, AIAA 1st Intelligent Systems Technical Conference, 1, pp. 141-157, (2004)
[7] Liu L., Yu C., Wang Z., Et al., Fast 3D route planning method for small UAV, System Engineering and Electronics, 35, 12, pp. 2521-2526, (2013)
[8] Yao Y., Zhou X., Zhang K., Et al., Dynamic trajectory planning for unmanned aerial vehicle based on sparse A* search and improved artificial potential field, Control Theory & Applications, 27, 7, pp. 953-959, (2010)
[9] Dong Z., Zhang R., Chen Z., Et al., Study on UAV path planning approach based on fuzzy virtual force, Chinese Journal of Aeronautics, 23, 3, pp. 341-350, (2010)
[10] Wang W., Wang H., Real-time obstacle avoidance trajectory planning for missile borne air vehicle based on constrained artificial potential field method, Journal of Aerospace power, 29, 7, pp. 1738-1743, (2014)

← 1 2 →