Adaptive Control of Multidimensional Nonlinear Objects on the Basis of Radial-Basis Networks
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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.
Keywordsneural network model training control algorithm
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