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Adaptive neural network state predictor and tracking control for nonlinear time-delay systems
Na, Jing; Ren, Xuemei; Gao, Yan; Griñó Cubero, Robert; Costa Castelló, Ramon
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. ACES - Control Avançat de Sistemes d'Energia
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.
-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
Article - Published version
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