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 :
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