Abstract
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.
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Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 168–176, March–April 2005.
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Rudenko, O.G., Bessonov, A.A. Adaptive Control of Multidimensional Nonlinear Objects on the Basis of Radial-Basis Networks. Cybern Syst Anal 41, 302–308 (2005). https://doi.org/10.1007/s10559-005-0064-1
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DOI: https://doi.org/10.1007/s10559-005-0064-1