DocumentCode :
441676
Title :
FCMAC based on minesweeping strategy
Author :
Hu, Jing-song ; Hu, Gui-wu ; Wang, Jia-bing ; Liu, Bo
Author_Institution :
Comput. Sci. & Eng. Dept., South China Univ. of Technol., Guangzhou, China
Volume :
2
fYear :
2005
fDate :
18-21 Aug. 2005
Firstpage :
784
Abstract :
The fuzzy cerebellar model articulation controller has been widely used to control complex object, but most learning algorithm of CMAC are greedy and local optimization. So the precision is relative low. A fast global strategy, call minesweeping strategy, are presented to improve the global ability of CMAC. The minesweeping strategy lets the current search "jump out", rather than "climb out" step by step, hardly and wanderingly, as simulating annealing and tabu search do, from the current local minimum by exploiting a new area that is far away from all obtained local minima erenow. Therefore the strategy to solve local minimum problem is more successful and faster than other methods. The new method realizes fine control quality to a nonlinear plant, of which mathematic model is not known.
Keywords :
fuzzy control; learning (artificial intelligence); search problems; simulated annealing; fuzzy cerebellar model articulation controller; greedy algorithm; learning algorithm; local optimization; minesweeping strategy; nonlinear plant; simulating annealing; tabu search; Brain modeling; Computer science; Educational institutions; Electronic mail; Fuzzy control; Inference algorithms; Mathematical model; Mathematics; Neural networks; Simulated annealing; CMAC; Minesweeping strategy; Nonlinear plant;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
Type :
conf
DOI :
10.1109/ICMLC.2005.1527050
Filename :
1527050
Link To Document :
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