Title

Neural Network Model Reference Adaptive Control Of A Surface Vessel

Abstract

A neural network model reference adaptive controller for trajectory tracking of nonlinear systems is developed. The proposed control algorithm uses a single layer neural network that bypasses the need for information about the system's dynamic structure and provides portability. Numerical simulations are performed using a three degree of freedom nonlinear dynamic model of a surface vessel. The results demonstrate the controller performance in terms of tuning, robustness and tracking.

Publication Date

1-1-2004

Publication Title

Proceedings of the IEEE Conference on Decision and Control

Volume

1

Number of Pages

662-667

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/cdc.2004.1428720

Socpus ID

14344257285 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/14344257285

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