ADAPTIVE CONTROL OF MULTIDIMENSIONAL NONLINEAR OBJECTS ON THE BASIS OF RADIAL-BASIS NETWORKS

摘要

The problem of adaptive control over multidimensional nonlinear dynamic objects with the use of a neural network model is considered. To train the model, a recurrent least-squares method with exponential weighing of information and, to control an object, the multidimensional Kaczmarz algorithm are used. The results of an experimental investigation of the approach proposed are given.