2013 | OriginalPaper | Buchkapitel
Adaptive NN Control for a Class of Strict-Feedback Discrete-Time Nonlinear Systems with Input Saturation
verfasst von : Xin Wang, Tieshan Li, Liyou Fang, Bin Lin
Erschienen in: Advances in Neural Networks – ISNN 2013
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper, an adaptive neural network (NN) control scheme is proposed for a class of strict-feedback discrete-time nonlinear systems with input saturation. which is designed via backstepping technology and the approximation property of the HONNs, aimed to solve the the input saturation constraint and system uncertainty in many practical applications. The closedloop system is proven to be uniformly ultimately bounded (UUB). At last, a simulation example is given to illustrate the effectiveness of the proposed algorithm.