Anzeige
Erschienen in:
2013 | OriginalPaper | Buchkapitel
DSC Approach to Robust Adaptive NN Tracking Control for a Class of SISO Systems
verfasst von : Wei Li, Jun Ning, Renhai Yu
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, by employing Radial Basis Function (RBF) Neural Networks (NN) to approximate uncertain functions, the robust adaptive neural networks design for a class of SISO systems was brought in based on dynamic surface control (DSC) and minimal-learning-parameter (MLP) algorithm. With less learning parameters and reduced computation load, the proposed algorithm can avoid the possible controller singularity problem and the trouble caused by "explosion of complexity" in traditional backstepping methods is removed, so it is convenient to be implemented in applications. In addition, it is proved that all the signals of the closed-loop system are uniformly ultimately bounded(UUB), and simulation results on ocean-going training ship ’YULONG’ are shown to validate the effectiveness and the performance of the proposed algorithm.