MRAC design of ship´s course controller based on RBFNN

Author

Gao, Xiaori ; Hong, Biguang ; Li, Tieshan

Author_Institution

Navig. Coll., Dalian Maritime Univ., Dalian, China

fYear

2012

fDate

15-17 July 2012

Firstpage

312

Lastpage

316

Abstract

In order to study ship´s course control system, this paper adopts a model reference adaptive control scheme. In the design procedure, a RBFNN (RBF neural networks) is used to approximate the unknown nonlinear system when the MMG ship mathematical model is considered. The approximation error and external disturbance are counteracted by a robust adaptive compensation algorithm. The approximation weight are obtained by Lyapunov direct method, meanwhile, the stability of closed loop system is proved by this method. Finally, the presented scheme is verified through simulation.

Keywords

Lyapunov methods; closed loop systems; control system synthesis; marine control; model reference adaptive control systems; nonlinear control systems; radial basis function networks; robust control; ships; Lyapunov direct method; MMG ship mathematical model; MRAC design; RBF neural networks; RBFNN; approximation error; closed loop system stability; design procedure; external disturbance; model reference adaptive control scheme; nonlinear system; robust adaptive compensation algorithm; ship course control system; ship course controller; Control systems; Marine vehicles; Mathematical model; Neural networks; Nonlinear systems; Robustness; Simulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Information Processing (ICICIP), 2012 Third International Conference on

Conference_Location

Dalian

Print_ISBN

978-1-4577-2144-1

Type

conf

DOI

10.1109/ICICIP.2012.6391506

Filename

6391506