GA based optimization of NN-SANARX model for adaptive control of nonlinear systems

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.