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Dynamic neural network-based robust observers for uncertain nonlinear systems
Ist Teil von
Neural networks, 2014-12, Vol.60, p.44-52
Ort / Verlag
Kidlington: Elsevier Ltd
Erscheinungsjahr
2014
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
A dynamic neural network (DNN) based robust observer for uncertain nonlinear systems is developed. The observer structure consists of a DNN to estimate the system dynamics on-line, a dynamic filter to estimate the unmeasurable state and a sliding mode feedback term to account for modeling errors and exogenous disturbances. The observed states are proven to asymptotically converge to the system states of high-order uncertain nonlinear systems through Lyapunov-based analysis. Simulations and experiments on a two-link robot manipulator are performed to show the effectiveness of the proposed method in comparison to several other state estimation methods.