Optimal Flight Path Planning of Cruising Phase with No-Fly Zone Constraints Based on Dynamic Programming Algorithm

Article Preview

Abstract:

The purpose of flight path planning is to find the optimal path from the real-time and conflict-free airspace to meet the targets, according to one or several performance index. Effective avoiding the no-fly zones, such as the areas of martial movement and the areas of rain and thunderstorm, has great significance to the current flight management system (FMS) that is real-time and effective implementation of the flight plan. The dynamic optimization method of level route based on DP (Dynamic Programming) algorithm without no-fly zone constraints is discussed. Quick and effective to find out an optimal path from the waypoints of arbitrary selection and input can be realized. On this basis, the situation of adding no-fly zone constraints is focused on. In order to ensure that the aircraft is able to effectively avoid no-fly zone constraints in actual flight, Gauss Kruger projection method to convert geographic coordinates to plane coordinates is adopted. Simulation results show that the method used can not only effectively avoid no-fly zone constraints, and the path passed is still optimal.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 433-440)

Pages:

5911-5917

Citation:

Online since:

January 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Du Ping and Yang Chun, Introduction of Air Vehicle Path Planning Algorithms, Flight dynamics, Vol. 23 No. 2, June (2005).

Google Scholar

[2] Igor Alonso-Portillo and Ella M. Atkins. Adaptive Trajectory Planning for Flight Management Systems, AAAI Technical Report SS-01-06.

Google Scholar

[3] Luo Jia, Flight Management Systems: Optimization and Generation of Flight Trajectories, Beijing University of Aeronautics and Astronautics, (1988).

Google Scholar

[4] Wang Yingxun and Chen Zongji, Genetic Algorithms (GA) Based Flight Path Planning with Constraints, Journal of Beijing University of Aeronautics and Astronautics, Vol. 25 No. 13, June (1999).

Google Scholar

[5] Hu Xiaobing, Wu Shufan, and Jiang Ju, On-Line Optimization of Fli ght Line Based on GA. Aeronautical Computer Technique,. Vol. 31 No. 2, June (2001).

Google Scholar

[6] Yeonju Eun and Hyochoong Bang, Cooperative Task Assignment and Path Planning of Multiple UAVs Using Genetic Algorithm, AIAA Infotech@Aerospace 2007 Conference and Exhibit 7-10 May 2007, Rohnert Park, California, AIAA 2007-2982.

DOI: 10.2514/6.2007-2982

Google Scholar

[7] Gopal. V and Schulz. R, 2-D Multiaircraft conflict resolution with interior point methods, Sixth SIAM Conference on Optimization, Atlanta, GA, (1999).

Google Scholar

[8] Arvind U. Raghunathan, Vipin Gopal, Dharmashankar Subramanian Lorenz T. Biegler and Tariq Samad, 3D Conflict Resolution of Multiple Aircraft via Dynamic Optimization, AIAA Guidance, Navigation, and Control Conference and Exhibit 11-14 August 2003, Austin, Texas, AIAA 2003-5675.

DOI: 10.2514/6.2003-5675

Google Scholar

[9] Timothy R. Jorris, Christopher S. Schulz, and Franklin R. Friedl. Constrained Trajectory Optimization Using Pseudospectral Methods, AIAA Atmospheric Flight Mechanics Conference and Exhibit 18-21 August 2008, Honolulu, Hawaii, AIAA 2008-6218.

DOI: 10.2514/6.2008-6218

Google Scholar

[10] Chelsea Sabo, Kelly Cohen, Manish Kumar, and Shaaban Abdallah. Effectiveness of 2D Path Planning in Real Time using Fuzzy Logic, 48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition 4-7 January 2010, Orlando, Florida, AIAA 2010-417.

DOI: 10.2514/6.2010-417

Google Scholar

[11] Sara Bagassi, Tiziano Bombardi, and Daniela Francia, 3D Trajectory Optimization for UAS Insertion in Civil Non-Segregated Airspace, AIAA Modeling and Simulation Technologies Conference 10-13 August 2009, Chicago, Illinois, AIAA 2009-5840.

DOI: 10.2514/6.2009-5840

Google Scholar

[12] Francesca De Crescenzio, Giovanni Miranda, Franco Persiani, and Tiziano Bombardi, 3D Obstacle Avoidance Strategies For UAS (Unihabited Aerial Systems) Mission Planning And Re-planning, The 26th Congress of International Council of the Aeronautical Sciences including 14-19 September 2008, Anchorage, Alaska, AIAA 2008-8962.

DOI: 10.2514/6.2008-8962

Google Scholar

[13] Timothy R. Jorris and Richard G. Cobb, Multiple Method 2-D Trajectory Optimization Satisfying Waypoints and No-Fly Zone Constraints, Journal of Guidance, Control, and Dynamics, Vol. 31 No. 3, May–June, (2008).

DOI: 10.2514/1.32354

Google Scholar

[14] Timothy R. Jorris and Richard G. Cobb, Three-Dimensional Trajectory Optimization Satisfying Waypoint and No-Fly Zone Constraints, Journal of Guidance, Control, and Dynamics, Vol 32 No 2, March–April, (2009).

DOI: 10.2514/1.37030

Google Scholar

[15] Patrick H agelauer and Felix Mora-Camino, A Soft dynamic Prog-ramming Approach for On-line Aircraft 4D-trajectory Optimization, European Journal of Operational Research 107 (1998) 87-95.

DOI: 10.1016/s0377-2217(97)00221-x

Google Scholar

[16] Massimiliano Mattei and Luciano Blasi, Smooth Flight Trajectory Planning in the Presence of No-Fly Zones and Obstacles, Journal of Guidance, Control, and Dynamics, Vol. 33 No. 2, March–April (2010).

DOI: 10.2514/1.45161

Google Scholar

[17] Hu Xiaobin, Wu Shufan, and Jiang Ju, The Simulation Study On On-Line Real -Time Optimization of Commercial Aircraft's Flight Paths, Computer Simulations, Vol. 18 No, 3, May (2001).

Google Scholar

[18] Hu Shousong, Wang Zhiquan, and Hu Weili, Optimal Control Theory and System, Science Press, May (2005).

Google Scholar

[19] Guangzhong liu, Dynamic Programming-Theory and Application, December (1991).

Google Scholar

[20] Zhu Yunqiang, Gong Huili, and Xu Huiping, Map Projection Transfor-mation of GIS, Journal of Capital Normal University(Natural Science Edition), Vol. 22 No. 3, September (2001).

Google Scholar

[21] Liu Jian and Liu Gaofeng, Algorithm of Coordinates Conversion in Gauss - Kruger Projection, Computer Simulations, Vol. 22 No. 10, October (2005).

Google Scholar