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Stability of a class of adaptive nonlinear systems

Andrzej Dzielinski — 2005

International Journal of Applied Mathematics and Computer Science

This paper presents a research effort focused on the problem of robust stability of the closed-loop adaptive system. It is aimed at providing a general framework for the investigation of continuous-time, state-space systems required to track a (stable) reference model. This is motivated by the model reference adaptive control (MRAC) scheme, traditionally considered in such a setting. The application of differential inequlities results to the analysis of the Lyapunov stability for a class of nonlinear...

Neural network-based NARX models in non-linear adaptive control

Andrzej Dzieliński — 2002

International Journal of Applied Mathematics and Computer Science

The applicability of approximate NARX models of non-linear dynamic systems is discussed. The models are obtained by a new version of Fourier analysis-based neural network also described in the paper. This constitutes a reformulation of a known method in a recursive manner, i.e. adapted to account for incoming data on-line. The method allows us to obtain an approximate model of the non-linear system. The estimation of the influence of the modelling error on the discrepancy between the model and real...

Fractional kalman filter algorithm for the states parameters and order of fractional system estimation

Dominik SierociukAndrzej Dzieliński — 2006

International Journal of Applied Mathematics and Computer Science

This paper presents a generalization of the Kalman filter for linear and nonlinear fractional order discrete state-space systems. Linear and nonlinear discrete fractional order state-space systems are also introduced. The simplified kalman filter for the linear case is called the fractional Kalman filter and its nonlinear extension is named the extended fractional Kalman filter. The background and motivations for using such techniques are given, and some algorithms are discussed. The paper also...

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