NSGAII based multi-objective homing trajectory planning of parafoil system

Jin Tao , Qing-lin Sun , Zeng-qiang Chen , Ying-ping He

Journal of Central South University ›› 2017, Vol. 23 ›› Issue (12) : 3248 -3255.

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Journal of Central South University ›› 2017, Vol. 23 ›› Issue (12) : 3248 -3255. DOI: 10.1007/s11771-016-3390-8
Mechanical Engineering, Control Science and Information Engineering

NSGAII based multi-objective homing trajectory planning of parafoil system

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Abstract

Homing trajectory planning is a core task of autonomous homing of parafoil system. This work analyzes and establishes a simplified kinematic mathematical model, and regards the homing trajectory planning problem as a kind of multi-objective optimization problem. Being different from traditional ways of transforming the multi-objective optimization into a single objective optimization by weighting factors, this work applies an improved non-dominated sorting genetic algorithm II (NSGA II) to solve it directly by means of optimizing multi-objective functions simultaneously. In the improved NSGA II, the chaos initialization and a crowding distance based population trimming method were introduced to overcome the prematurity of population, the penalty function was used in handling constraints, and the optimal solution was selected according to the method of fuzzy set theory. Simulation results of three different schemes designed according to various practical engineering requirements show that the improved NSGA II can effectively obtain the Pareto optimal solution set under different weighting with outstanding convergence and stability, and provide a new train of thoughts to design homing trajectory of parafoil system.

Keywords

parafoil system / homing trajectory planning / multi-objective optimization / non-dominated sorting genetic algorithm (NSGA) / non-uniform b-spline

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Jin Tao, Qing-lin Sun, Zeng-qiang Chen, Ying-ping He. NSGAII based multi-objective homing trajectory planning of parafoil system. Journal of Central South University, 2017, 23(12): 3248-3255 DOI:10.1007/s11771-016-3390-8

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References

[1]

LiC, LuZ-h, HuangW, ShenChao. Guidance navigation & control system for precision fix-point homing parafoil [J]. Journal of Central South University: Science and Technology, 2012, 43(4): 1331-1335

[2]

RogersJ, SlegersN. Robust parafoil terminal guidance using massively parallel processing [J]. Journal of Guidance, Control, and Dynamics, 2013, 36(5): 1336-1345

[3]

ZhuE-l, SunQ-l, TanP-L, ChenZ-q, HeY-ping. Modeling of powered parafoil based on Kirchhoff motion equation [J]. Nonlinear Dynamics, 2015, 79(1): 617-629

[4]

XiongJingResearch on the dynamics and homing project of parafoil system [D], 2005ChangshaNational University of Defense Technology

[5]

PearsonAOptimal control of a gliding parachute system [R], 1972MassachusettsArmy Natick Labs

[6]

GimadievaT. Optimal control of a gliding parachute system [J]. Journal of Mathematical Science, 2001, 103(1): 54-60

[7]

RademacherB J, LuP, StrahanA L, CerimeleC J. In-flight trajectory planning and guidance for autonomous parafoils [J]. Journal of Guidance, Control, and Dynamics, 2009, 32(6): 1697-1712

[8]

LiuZ, KongJ-yi. Path planning of parafoil system based on particle swarm optimization [C]. Computational Intelligence and Natural Computing, 2009Wuhan, ChinaIEEE450-453

[9]

JiaoL, SunQ-l, KangX-feng. Route planning for parafoil system based on chaotic particle swarm optimization [J]. Complex Systems and Complexity Science, 2012, 9(1): 47-54

[10]

ZhangL-m, GaoH-t, ChenZ-q, SunQ-l, ZhangX-hui. Multi-objective global optimal parafoil homing trajectory optimization via Gauss pseudo-spectral method [J]. Nonlinear Dynamics, 2013, 72(1/2): 1-8

[11]

GaoH-t, ZhangL-m, SunQ-l, SunM-w, Chenz-q, KangX-feng. Fault-tolerance design of homing trajectory for parafoil system based on pseudo-spectral method [J]. Control Theory & Applications, 2013, 30(6): 702-708

[12]

LudersB D, SugelI, HowJ P. Robust trajectory planning for autonomous parafoils under wind uncertainty [C]. AIAA Conf on Guidance, Navigation and Control and Co-located Conferences, 2013RestonVA: AIAA1-27

[13]

CleminsonJ. Path planning for guided parafoils: An alternative dynamic programming formulation [C]. AIAA Aerodynamic Decelerator Systems (ADS) Conference, 2013Reston, VAAIAA1-21

[14]

BabuA, SujaV, ReddtyC. Three dimensional trajectory optimization of a homing parafoil [C]. 3rd International Conference on Advances in Control and Optimization of Dynamical Systems, 2014NetherlandsElsevier847-854

[15]

TaoJ, SunQ-l, ZhuE-l, ChenZ-qiang. Quantum genetic algorithm based homing trajectory planning of parafoil system [C]. 34th Chinese Control Conference, 2015Hangzhou, ChinaIEEE2523-2528

[16]

DebK, AgrawalS, PratapA, MeyarivanT. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II [J]. Lecture Notes in Computer Science, 2000, 1917: 849-858

[17]

DebK, PratapA. A fast and elitist multi-objective genetic algorithm: NSGA-II [J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197

[18]

AbolfazlK. Best compromising crashworthiness design of automotive S-rail using TOPSIS and modified NSGA II [J]. Journal of Central South University, 2015, 22(1): 121-133

[19]

LeiY-j, ZhangS-wenGenetic algorithm toolbox and its application [M], 2014Xi’anXi’an University of Electronic Science and Technology Press

[20]

JiaoL, SunQ-l, KangX-f, ChenZ-q, LiuZ-xin. Autonomous homing of parafoil and payload system based on ADRC [J]. Control Engineering and Applied Informatics, 2011, 13(3): 25-31

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