Dynamical Response Model for Tanker Steering Using GEBF Based Fuzzy Neural Networks
In this paper, we propose a novel dynamical response model for tanker steering by using the promising Generalized Ellipsoidal Function Based Fuzzy Neural Network (GEBF-FNN) algorithm. Based on a group of well established nonlinear differential equations for tanker maneuvering dynamics, training data samples are generated for the GEBF-FNN method to online identify the K and T parameters of the tanker response model in the form of Nomoto steering model. The GEBF-FNN model starts with zero fuzzy rules and online recruits efficient fuzzy rules via rule node generation criteria and parameter estimation. As a consequence, it results in a dynamical response model for tanker steering with high accuracy and transparent structures consisting of a group of fuzzy rules. In order to demonstrate that the proposed response model is effective, simulation studies are conducted on typical zig-zag maneuvers. Moreover, comprehensive comparisons are carefully presented. Simulation results indicate that the GEBF-FNN based response model achieves promising performance in terms of approximation and prediction.
Tanker Steering Response Model Fuzzy Neural Network Generalized Ellipsoidal Basis Function
WANG Ning WANG Dan LI Tieshan
Marine Engineering College, Dalian Maritime University, Dalian 116026, P. R. China Navigation College, Dalian Maritime University, Dalian 116026, P. R. China
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
7032-7037
2012-07-01（万方平台首次上网日期，不代表论文的发表时间）