Paper Info
Title
Control Of Nonlinear Systems With A Linear State-Feedback Controller And A Modified Neural Network Tuned By Genetic Algorithm
Abstract
This paper presents the control of nonlinear with a neural network. In the proposed neural network, the neuron has two activation functions and exhibits a node-to-node relationship in the hidden layer. By using a genetic algorithm with arithmetic crossover and non-uniform mutation, the parameters of the proposed neural network can be tuned. Application examples are given to illustrate the merits of the proposed neural network.
Year
DOI
Venue
2007
10.1109/CEC.2007.4424666
2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS
Keywords
Field
DocType
neural network,genetic algorithms,transfer functions,genetic algorithm,parameter estimation,activation function,nonlinear system,feedback control,neural networks
Feedforward neural network,Crossover,Control theory,Computer science,Stochastic neural network,Recurrent neural network,Probabilistic neural network,Time delay neural network,Artificial intelligence,Artificial neural network,Machine learning,Genetic algorithm
Conference
Citations 
PageRank 
References 
0
0.34
13
Authors
5
Name
Order
Citations
PageRank
H. K. Lam13618193.15
S. H. Ling260940.29
Herbert H. C. Iu333460.21
C. W. Yeung41076.74
F. H. Frank Leung518316.00