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Technical Brief

Trajectory Optimization Using Analytical Target Cascading

[+] Author and Article Information
Xiang Li

School of Aerospace Engineering, Beijing Institute of Technology, Beijing, 100081, China
lixiang_0504@yahoo.com

XiaoPeng Wang

Shanghai Electro-Mechanical Engineering Institute, Shanghai, 201109, China
lx_0205@163.com

Houjun Zhang

Beijing System Design Institute of Electro-Mechanic Engineering, Beijing, 100854, China
zhanghoujun123@126.com

Yuheng Guo

School of Aerospace Engineering, Beijing Institute of Technology, Beijing, 100081, China
hh156396@163.com

1Corresponding author.

ASME doi:10.1115/1.4037714 History: Received November 30, 2016; Revised August 12, 2017

Abstract

In the previous reports, analytical target cascading (ATC) is generally applied to product optimization. In this paper, the application area of ATC is expanded to trajectory optimization. Direct collocation method is utilized to convert a trajectory optimization into a nonlinear programming (NLP) problem. The converted NLP is a large-scale problem with sparse matrix of functional dependence table suitable for the application of ATC. Three numerical case studies are provided to show the effects of ATC in solving trajectory optimization problems.

Copyright (c) 2017 by ASME
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