Title :
Adaptive RBF Neural Network Sliding Mode Control for Ship Course Control System
Author :
Wei, Meng ; Chen, Guo
Author_Institution :
Sch. of Inf. Sci. & Technol., Dalian Maritime Univ., Dalian, China
Abstract :
For ship course control system, this paper proposes a class of sliding mode variable structure control method (SMVSC) based on RBF neural network. The mathematical model of ship steering system possesses parametric perturbation and external disturbances, which combines the advantages of RBF neural network and sliding mode control. The controller is given by the output of RBF neural network and the weights of neural network can be adjusted online according to the sliding mode reaching law. Simulation results illustrate the effectiveness and robustness of the proposed algorithm.
Keywords :
adaptive control; neurocontrollers; path planning; radial basis function networks; ships; steering systems; variable structure systems; adaptive RBF neural network; radial basis function network; ship course control system; ship steering system; sliding mode control; sliding mode reaching law; variable structure control method; Biological neural networks; Educational institutions; Interference; Marine vehicles; Mathematical model; Sliding mode control; Course Control; RBF Neural Network; Ship; Sliding Mode Control;
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2011 International Conference on
Conference_Location :
Zhejiang
Print_ISBN :
978-1-4577-0676-9
DOI :
10.1109/IHMSC.2011.77