This paper studies the issue of generating optimal air-to-ground guided bomb delivery trajectories for unmanned combat aerial vehicles (UCAVs), and proposes a strategy based on the Gauss pseudospectral method (GPM) to deal with difficulties of traditional methods in processing vehicle kinematic and dynamic constraints. First, a high-fidelity 3-DOF nonlinear model of a UCAV is built which takes into consideration its aerodynamic characteristics, thrust and fuel consumption characteristics and atmospheric characteristics. Second, a fast algorithm is developed for searching the envelope of a guided bomb’s launch acceptable region (LAR), which is expressed as a final constraint in order to ensure attack accuracy. Third, GPM transforms the trajectory planning problem into a nonlinear programming problem, which can be solved using a sequential quadratic programming (SQP) algorithm. To improve computation efficiency and reduce the complexity of initial guess, a multistage iterative optimization strategy is presented. Finally, numerical examples for a minimum time-consumption trajectory as well as a minimum fuel-consumption trajectory are used to demonstrate the merits of the proposed algorithm. The results show that the algorithm can generate both feasible and optimal weapon delivery trajectories.
ZHANG Yu, ZHANG Wanpeng, CHEN Jing, SHEN Lincheng
. Air-to-ground Weapon Delivery Trajectory Planning for UCAVs Using Gauss Pseudospectral Method[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2011
, 32(7)
: 1240
-1251
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DOI: CNKI:11-1929/V.20101228.1334.003
[1] Hurni M A, Sekhavat P, Ross I M. Autonomous path planning using real-time information updates. AIAA-2008-6305, 2008.
[2] Shimoda S, Kuroda Y, Iagnernrna K. Potential field navigation of high speed unmanned ground vehicles on uneven terrain//International Conference on Robotics and Automation. 2005: 2839-2844.
[3] Kim S H, Bhattacharya R. Motion planning in obstacle rich environments[J]. Journal of Aerospace Computing, Information, and Communication, 2009, 6(7): 433-450.
[4] Lu W C, Mora-Camino F, Achaibou K. A flatness based flight guidance control using neural networks// IEEE the 24th Digital Avionics Systems Conference. 2005: 6.C.1.1-6.C.1.7.
[5] Nikolos I K, Valavanis K P. Evolutionary algorithm based offline/online path planner for UAV navigation[J]. IEEE Transactions on Systems, Man, and Cybernetics, 2003, 33(6): 898-912.
[6] Foo J L, Knutzon J, Kalivarapu V, et al. Path planning of unmanned aerial vehicles using B-splines and particle swarm optimization[J]. Journal of Aerospace Computing, Information, and Communication, 2009, 6(4): 271-290.
[7] Kaneshige J, Krishnakumar K. Artificial immune system approach for air combat maneuvering// Proceedings of the International Society for Optical Engineering. 2007, 6560: 656009.
[8] Frazzoli E, Dahleh M A, Feron E. Real-time motion planning for agile autonomous vehicles[J]. Journal of Guidance, Control, and Dynamics, 2002, 25(1): 116-129.
[9] Kuwata Y, Karaman S, Teo J, et al. Real-time motion planning with applications to autonomous urban driving[J]. IEEE Transactions on Control Systems Technology, 2009, 17(5): 1105-1118.
[10] Lewis L P R. Rapid motion planning and autonomous obstacle avoidance for unmanned vehicles. Monterey: Naval Postgraduate School, 2006.
[11] Williams P. Three-dimensional aircraft terrain-following via real-time optimal control[J]. Journal of Guidance, Control, and Dynamics, 2007, 30(4): 1201-1205.
[12] Bryson A E, Desal M N, Hoffman W C. Energy-state approximation in performance estimation of supersonic aircraft[J]. Journal of Aircraft, 1969, 6(6): 481-487.
[13] 耿丽娜. 制导炸弹投放区计算研究. 长沙: 国防科学技术大学, 2009. Geng Lina. Study on release region calculation for guided bombs. Changsha: National University of Defense Technology, 2009. (in Chinese)
[14] West W J. Developmental testing of a laser-guided bomb simulation. AIAA-2008-1629, 2008.
[15] Siewert V L, Sussingham J C. 6-DOF enhancement of precision guided munitions testing. AIAA-1997-5522, 1997.
[16] Wilson S A, Vuletich I J, Fletcher D J, et al. Guided weapon danger area & safety template generation—a new capability. AIAA-2008-7123, 2008.
[17] Betts J T. Survey of numerical methods for trajectory optimization[J]. Journal of Guidance, Control, and Dynamics, 1998, 21(2): 193-207.
[18] Fahroo F, Ross I M. Advances in pseudospectral methods for optimal control. AIAA-2008-7309, 2008.
[19] Benson D A, Huntington G T, Thorvaldsen T P, et al. Direct trajectory optimization and costate estimation via an orthogonal collocation method[J]. Journal of Guidance, Control, and Dynamics, 2006, 29(6): 1435-1440.
[20] Huntington G T, Benson D, Rao A V. A comparison of accuracy and computational efficiency of three pseudospectral methods. AIAA-2007-6405, 2007.
[21] Benson D. A Gauss pseudospectral transcription for optimal control. Bostom: Massachusettes Institute of Technology, 2004.
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