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

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. Copyright © 2010 Inderscience Enterprises Ltd.