Title: An improved optimal guidance law with impact angle constraints based on genetic algorithms

Authors: Zongzhun Zheng, Yongji Wang, Hao Wu

Addresses: Department of Control Science and Engineering, Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan, Hubei Province, 430074, China. ' Department of Control Science and Engineering, Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan, Hubei Province, 430074, China. ' Department of Control Science and Engineering, Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan, Hubei Province, 430074, China

Abstract: In this paper, an improved formulation of optimal guidance law (OGL) based on genetic algorithms (GAs) is proposed. Linear quadratic optimal control theory is derived to consider terminal velocity maximisation, also GAs are employed to search weight coefficient matrix of the linear quadratic performance index optimum process problem. In the GAs, a combination of the roulette wheel and elitism methods is adopted, and penalty function is added to performance index. Consequently, terminal position accuracy and impact angle constraints are satisfied. Numerical simulation results illustrate that the proposed OGL based on GAs shows better performance compared with conventional method and is rather robust.

Keywords: optimal guidance law; OGL; impact angle constraints; linear quadratic control; genetic algorithms; GAs; terminal velocity; terminal position accuracy.

DOI: 10.1504/IJMIC.2010.033850

International Journal of Modelling, Identification and Control, 2010 Vol.10 No.1/2, pp.94 - 100

Published online: 02 Jul 2010 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article