DocumentCode :
1795351
Title :
Angular constrained guidance law and its optimization with hybrid optimization algorithm
Author :
Chao Tao ; Wang Songyan ; Yang Ming
Author_Institution :
Control & Simulation Center, Harbin Inst. of Technol., Harbin, China
fYear :
2014
fDate :
8-10 Aug. 2014
Firstpage :
2455
Lastpage :
2460
Abstract :
A new guidance law with terminal trajectory angle constraint is designed for bank to turn flight vehicle, which aims at the fixed position ground target. The general form of guidance law with sight angle and sight angle velocity as feedback variables is presented, and the stability of it is proved via finite time convergent stability theory, which makes traditional optimal guidance as a specific example of this general form guidance law. Parameters optimization of this guidance law is proposed using a hybrid optimization algorithm in order to help the designer to find suitable parameters, which can have the specific characteristics they are seeking for. Numerical simulation shows that the proposed guidance law is effective and the hybrid optimization algorithm can get the optimal solution of the guidance law design problem more quickly than before.
Keywords :
aerospace computing; aircraft control; convergence; genetic algorithms; numerical analysis; stability; angular constrained guidance law; finite time convergent stability theory; flight vehicle; genetic algorithm; guidance law design problem; hybrid optimization algorithm; numerical simulation; optimal guidance; parameters optimization; support vector machine; terminal trajectory angle constraint; Equations; Genetic algorithms; Mathematical model; Optimization; Support vector machines; Trajectory; Vehicles; Angular Constraints; Bank to Turn; Genetic Algorithm; Guidance; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4799-4700-3
Type :
conf
DOI :
10.1109/CGNCC.2014.7007554
Filename :
7007554
Link To Document :
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