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Adaptive neural network state predictor and tracking control for nonlinear time-delay systems

Author
Na, Jing; Ren, X.; Gao, Y.; Griño, R.; Costa-Castelló, R.
Type of activity
Journal article
Journal
International journal of innovative computing information and control
Date of publication
2010-02
Volume
6
Number
2
First page
627
Last page
639
Repository
http://hdl.handle.net/2117/8058 Open in new window
URL
http://www.ijicic.org/08-230-1.pdf Open in new window
Abstract
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 identificat...
Citation
Na, J. [et al.]. Adaptive neural network state predictor and tracking control for nonlinear time-delay systems. "International journal of innovative computing information and control", Febrer 2010, vol. 6, núm. 2, p. 627-639.
Group of research
ACES - Advanced Control of Energy Systems
CS2AC-UPC - Supervision, Safety and Automatic Control
SAC - Advanced Control Systems

Participants