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Título:
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Adaptive neural network state predictor and tracking control for nonlinear time-delay systems
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Autor/a:
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Na, Jing; Ren, Xuemei; Gao, Yan; Griñó Cubero, Robert; Costa Castelló, Ramon
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Otros autores:
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Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. ACES - Control Avançat de Sistemes d'Energia |
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Abstract:
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A new adaptive nonlinear state predictor (ANSP) is presented for a class of
unknown nonlinear systems with input time-delay. A dynamical identification with neu-
ral network (NN) is constructed to obtain NN weights and their derivatives. The future
NN weights are deduced for the nonlinear state predictor design without iterative calcu-
lations. The time-delay and unknown nonlinearity are compensated by a feedback control
using the predicted states. Rigorous stability analysis for the identification, predictor and
feedback control are provided by means of Lyapunov criterion. Simulations and practical
experiments of a temperature control system are included to verify the effectiveness of
the proposed scheme. |
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Materia(s):
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-Àrees temàtiques de la UPC::Informàtica::Automàtica i control
-Time delay systems
-Neural networks (Computer science)
-Feedback control systems
-Nonlinear systems
-Xarxes neuronals (Informàtica)
-Sistemes de control digital
-Sistemes no lineals |
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Derechos:
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Tipo de documento:
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Artículo - Versión publicada
Artículo |
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Compartir:
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