DocumentCode :
3210529
Title :
A Modified PSO Learning Algorithm for PID Neural Network
Author :
Li Ming ; Yang Chengwu
Author_Institution :
Coll. of Power Eng., Nanjing Univ. of Sci. & Techonology, China
fYear :
2006
fDate :
7-11 Aug. 2006
Firstpage :
1123
Lastpage :
1125
Abstract :
Traditional PID neural network adopts BP learning algorithm. However, without accurate gradients, its initial MSE is too large and the procedure of convergence may be unstable. A modified PSO (MPSO) algorithm is introduced to training the PID neural network. The MPSO algorithm does not need any gradient information. It can keep large variety all along and solve premature convergence, which is a major problem in basic PSO algorithm. Simulation results show MPSO algorithm is the best learning algorithm for PID neural network.
Keywords :
learning (artificial intelligence); neurocontrollers; particle swarm optimisation; three-term control; BP learning; PID neural network; modified PSO learning; premature convergence; Artificial intelligence; Convergence; Educational institutions; Electronic mail; MATLAB; Neural networks; Power engineering; Three-term control; PID neural network; PSO algorithm; learning algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2006. CCC 2006. Chinese
Conference_Location :
Harbin
Print_ISBN :
7-81077-802-1
Type :
conf
DOI :
10.1109/CHICC.2006.280575
Filename :
4060254
Link To Document :
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