DocumentCode :
596720
Title :
Low thrust gravity assist trajectory optimization based on hybrid method
Author :
Zunhui Zhao ; Haibin Shang ; Pingyuan Cui ; Xiangyu Huang
Author_Institution :
Key Lab. of Dynamics & Control of Flight Vehicle, Beijing Inst. of Technol., Beijing, China
fYear :
2012
fDate :
18-20 Oct. 2012
Firstpage :
903
Lastpage :
908
Abstract :
The application and advantage of low thrust propulsion system has been validated in practical mission launch even though the trajectory design difficulty is increased. The trajectory optimization problem brought by the use of low thrust propulsion in conjunction with gravity assist is researched. This paper proposes a hybrid technique for solving the strong nonlinear and multiple constraints optimal control problem using a hybrid technique. First, a nonlinear programming problem is proposed by abandoning the terminal constraints brought by Pontryagin maximum principle and treating costates as optimization variables; Then an adjoint control transformation is used for converting costate variables to other variables partially which possess actual bounds and physical meaning; Finally, differential evolution algorithm is employed for searching the initial values of nonlinear programming problem for local accurate optimization. Related low thrust gravity assist trajectories to outer planets by various gravity assists are designed for demonstrating the effectiveness of the proposed hybrid technique.
Keywords :
aerospace propulsion; aircraft control; evolutionary computation; gravity; maximum principle; nonlinear control systems; nonlinear programming; rockets; trajectory control; Pontryagin maximum principle; costate variable; differential evolution algorithm; hybrid method; multiconstraint optimal control problem; nonlinear control problem; nonlinear programming; practical mission launch; thrust gravity assist trajectory optimization; thrust propulsion system; Gravity; Optimal control; Optimization; Planets; Propulsion; Space vehicles; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-1743-6
Type :
conf
DOI :
10.1109/ICACI.2012.6463302
Filename :
6463302
Link To Document :
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