Title :
Ship course steering predictive control based on RBF neural network
Author :
Zhang, Xu ; GUO, Chen ; Ye, Guang
Author_Institution :
Sch. of Mech. Eng., Dalian Jiaotong Univ., Dalian
Abstract :
Because the ship steering control is uncertain, nonlinear and time-varying. A predictive control algorithm based on RBF neural network is adopted to the ship steering control. Recursive k-means clustering algorithm and recursive least squares algorithm are used to adjust the RBF neural network. And clonal selection algorithm is used in predictive control algorithm to ensure the global optimal solution. The simulation results show that the predictive control algorithm based on RBF neural network possesses good control performance and strong robustness.
Keywords :
least squares approximations; neurocontrollers; nonlinear control systems; position control; predictive control; radial basis function networks; recursive functions; ships; steering systems; time-varying systems; uncertain systems; RBF neural network; clonal selection algorithm; nonlinear control; recursive k-means clustering algorithm; recursive least squares algorithm; ship course steering predictive control; ship steering control; time-varying control; uncertain control; Automatic control; Automation; Clustering algorithms; Electronic mail; Intelligent control; Marine vehicles; Mechanical engineering; Neural networks; Prediction algorithms; Predictive control; RBF neural network; predictive control; ship steering control;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4594199
