Abstract：A virtual force based path following approach is presented for unmanned aerial vehicles (UAVs). Three virtual forces, including a virtual centripetal force, a virtual spring force and a virtual drag force, are designed to calculate the desired heading rate. The virtual centripetal force compensates the influence of the reference curvature. The virtual spring force ensures the vehicle converge to the reference path. Meanwhile, the virtual drag force prevents oscillation in the convergence process. The proposed approach can be used to accurately follow straight-line, circle, as well as curve with time-varying curvature. The approach is equivalent to a proportional-derivative controller when following a straight-line, equivalent to a feedback linearization method when following circular or curved paths. The stability and convergence are analyzed. The influence of the input constraint on the following performance is considered. When using virtual forces to control UAVs, the physical meanings of the parameters are definite, which makes them easy to tune in application. Simulation results demonstrate the effectiveness of the proposed approach, and its performance is better than the NLGL (nonlinear guidance logic) approach.
[1] Wang X, Zhu H, Zhang D, et al. Vision-based detection and tracking of a mobile ground target using a fixed-wing UAV[J]. International Journal of Advanced Robotic Systems, 2014, 11: No.156.
[2] Sujit P B, Saripalli S, Sousa B J. Unmanned aerial vehicle path following: A survey and analysis of algorithms for fixed-wing unmanned aerial vehicles[J]. IEEE Control Systems Magazine, 2014, 34(1): 42-59.
[3] Conte G, Duranti S, Merz T. Dynamic 3D path following for an autonomous helicopter[C]//IFAC Symposium on Intelligent Autonomous Vehicles. 2004.
[4] Ambrosino G, Ariola M, Ciniglio U, et al. Path generation and tracking in 3-D for UAVs[J]. IEEE Transactions on Control Systems Technology, 2009, 17(4): 980-988.
[5] Osborne J, Rysdyk R. Waypoint guidance for small UAVs in wind[C]//Infotech@ Aerospace: Advancing Contemporary Aerospace Technologies and Their Integration. Reston, USA: AIAA, 2005: 459-470.
[6] Fossen T I, Breivik M, Skjetne R. Line-of-sight path following of underactuated marine craft[C]//Proceedings of the 6th IFAC Conference on Manoeuvring and Control of Marine Craft. 2003: 244-249.
[7] Rysdyk R. UAV path following for constant line-of-sight[C]//2nd AIAA ''Unmanned Unlimited'' Conference and Workshop and Exhibit. 2003.
[8] Rysdyk R. Unmanned aerial vehicle path following for target observation in wind[J]. Journal of Guidance, Control, and Dynamics, 2006, 29(5): 1092-1100.
[9] Park S, Deyst J, How J P. Performance and Lyapunov stability of a nonlinear path following guidance method[J]. Journal of Guidance, Control, and Dynamics, 2007, 30(6): 1718-1728.
[10] Kothari M, Postlethwaite I, Gu D W. A suboptimal path planning algorithm using rapidly-exploring random trees[J]. International Journal of Aerospace Innovations, 2010, 2(1-2): 93-104.
[11] Nelson D R, Barber D B, McLain T W, et al. Vector field path following for miniature air vehicles[J]. IEEE Transactions on Robotics, 2007, 23(3): 519-529.
[12] Sun M R, Zhu R M, Yang X G. UAV path generation, path following and gimbal control[C]//IEEE International Conference on Networking, Sensing and Control. Piscataway, USA: IEEE, 2008: 870-873.
[13] Wang B, Dong X X, Chen B M. Cascaded control of 3D path following for an unmanned helicopter[C]//IEEE Conference on Cybernetics and Intelligent Systems. Piscataway, USA: IEEE, 2010: 70-75.
[14] Lee S, Cho A, Kee C. Integrated waypoint path generation and following of an unmanned aerial vehicle[J]. Aircraft Engineering and Aerospace Technology, 2010, 82(5): 296-304.
[15] Li Z, Sun J, Oh S. Handling roll constraints for path following of marine surface vessels using coordinated rudder and propulsion control[C]//American Control Conference. Piscataway, USA: IEEE, 2010: 6010-6015.
[16] Jackson S, Tisdale J, Kamgarpour M, et al. Tracking controllers for small UAVs with wind disturbances: Theory and flight results[C]//47th IEEE Conference on Decision and Control. Piscataway, USA: IEEE, 2008: 564-569.
[17] Cao C, Hovakimyan N, Kaminer I, et al. Stabilization of cascaded systems via L1 adaptive controller with application to a UAV path following problem and flight test results[C]//American Control Conference. Piscataway, USA: IEEE, 2007: 1787-1792.
[18] Aguiar A P, Kaminer I, Ghabcheloo R, et al. Coordinated path following of multiple UAVs for time-critical missions in the presence of time-varying communication topologies[C]//17th IFAC World Congress. Amsterdam, Netherlands: Elsevier, 2008: 16015-16020.
[19] Kaminer I, Yakimenko O, Dobrokhodov V, et al. Coordinated path following for time-critical missions of multiple UAVs via L1 adaptive output feedback controllers[C]//AIAA Guidance, Navigation and Control Conference and Exhibit. Reston, USA: AIAA, 2007: 915-948.
[20] Spears W M, Gordon D F. Using artificial physics to control agents[C]//International Conference on Information Intelligence and Systems. Piscataway, USA: IEEE, 1999: 281-288.
[21] Spears W M, Spears D F, Hamann J C, et al. Distributed, physics-based control of swarms of vehicles[J]. Autonomous Robots, 2004, 17(2-3): 137-162.
[22] Ren W, Beard R W. Trajectory tracking for unmanned air vehicles with velocity and heading rate constraints[J]. IEEE Transactions on Control Systems Technology, 2004, 12(5): 706-716.
[23] Aguiar A P, Hespanha J P. Trajectory-tracking and path-following of underactuated autonomous vehicles with parametric modeling uncertainty[J]. IEEE Transactions on Automatic Control, 2007, 52(8): 1362-1379.
[24] Wang X, Kong W W, Zhang D B, et al. Active disturbance rejection controller for small fixed-wing UAVs with model uncertainty[C]//IEEE International Conference on Information and Automation. Piscataway, USA: IEEE, 2015: 2299-2304.
[25] Wang X, Zhang J Y, Zhang D B, et al. UAV formation: From numerical simulation to actual flight[C]//IEEE International Conference on Information and Automation. Piscataway, USA: IEEE, 2015: 475-480.
