Title :
A sequential learning algorithm for RBF networks and its application to ship course-changing control
Author :
Bi, Gexin ; Dong, Fang
Author_Institution :
Coll. of Navig., Dalian Maritime Univ., Dalian
Abstract :
In this paper, a sequential learning algorithm for radial basis function (RBF) network is introduced referred to as dynamic orthogonal structure adaptation (DOSA) algorithm. Based on DOSA algorithm, a multi-step predictive control strategy is presented and applied to ship course-changing control. The combination of RBF network identification and predictive control mechanism minimizes the unfavorable effects of shippsilas time-varying dynamics and long time delay, enables accurate and smooth control of ship under various disturbances and random noises. Simulation results of ship course-changing experiment demonstrate the applicability and effectiveness of the RBF-based predictive control strategy.
Keywords :
learning (artificial intelligence); motion control; neurocontrollers; position control; predictive control; radial basis function networks; ships; RBF networks; dynamic orthogonal structure adaptation algorithm; multistep predictive control; radial basis function network; sequential learning algorithm; ship course-changing control; Marine vehicles; Radial basis function networks; Radial Basis Function Network; Sequential Learning; Ship Control;
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
DOI :
10.1109/CCDC.2008.4598038
