Title :
GA based optimization of NN-SANARX model for adaptive control of nonlinear systems
Author :
Vassiljeva, Kristina ; Petlenkov, Eduard ; Belikov, Juri
Author_Institution :
Dept. of Comput. Control, Tallinn Univ. of Technol., Tallinn, Estonia
Abstract :
This paper discusses application of dynamic state feedback algorithm for adaptive control of nonlinear MIMO systems. Neural Network based Simplified Additive Nonlinear AutoRegressive eXogenous (NN-SANARX) structure is used for identification of nonlinear MIMO systems. For better and faster adaptation it is important to minimize the number of parameters to be tuned. Therefore, structural identification of the neural network is done by the genetic algorithm. To avoid some of the complications caused by on-line adaptation the model is divided into adaptable and nonadaptable parts.
Keywords :
MIMO systems; adaptive control; autoregressive processes; genetic algorithms; identification; neurocontrollers; nonlinear control systems; state feedback; GA based optimization; NN-SANARX model; adaptive control; dynamic state feedback algorithm; genetic algorithm; nonlinear MIMO systems identification; simplified additive nonlinear autoregressive exogenous structure; Adaptation models; Adaptive control; Artificial neural networks; Biological neural networks; Genetic algorithms; MIMO;
Conference_Titel :
Neural Networks (IJCNN), The 2012 International Joint Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1488-6
Electronic_ISBN :
2161-4393
DOI :
10.1109/IJCNN.2012.6252598
