DocumentCode
3349584
Title
Research on fuzzy guidance law based on self-adaptive Genetic Annealing Algorithm
Author
Jin-yong, Yu ; Ru-chuan, Zhang ; Hong-chao, Zhao
Author_Institution
Number Three Dept., Naval Aeronaut. & Astronaut. Univ., Yantai
fYear
2008
fDate
21-24 Sept. 2008
Firstpage
1036
Lastpage
1041
Abstract
A new approach about design of guidance law (GL) for integrated self-adaptive genetic annealing algorithm (SGAA) and fuzzy logic (SGAA-FGL) was proposed in this study. Firstly, Based on traditional fuzzy logic control, the nonlinear variable region function was introduced, thus dynamic change of the fuzzy variable region can be realized. Next the self-adaptive simulated annealing genetic algorithm was employed to optimize the fuzzy rule, which was designed by selecting adaptively the cross probability and mutation probability of the proposed algorithm and improved the stability and convergence of system. Finally, the simulation results were presented to show the validity of the proposed method.
Keywords
adaptive control; fuzzy control; genetic algorithms; nonlinear control systems; simulated annealing; cross probability; fuzzy guidance law; fuzzy logic control; fuzzy rule; fuzzy variable region; mutation probability; nonlinear variable region function; self-adaptive simulated annealing genetic algorithm; Algorithm design and analysis; Design optimization; Fuzzy control; Fuzzy logic; Fuzzy systems; Genetic algorithms; Genetic mutations; Nonlinear dynamical systems; Simulated annealing; Stability; fuzzy control; guidance law; self-adaptive genetic annealing algorithm; variable region;
fLanguage
English
Publisher
ieee
Conference_Titel
Cybernetics and Intelligent Systems, 2008 IEEE Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-1673-8
Electronic_ISBN
978-1-4244-1674-5
Type
conf
DOI
10.1109/ICCIS.2008.4670760
Filename
4670760
Link To Document