Modeling of Nonlinear Parameters on Ship With Fuzzy CMAC Neural Networks

摘要：

An intelligent model for the ship’s nonlinear parameters was established based on fuzzy cerebellar model arithmetic computer (FCMAC) neural network. Firstly, the system design comprises the structure determination, and then applies the least square estimation with adaptive learning rate to train the mean and variance of the membership functions and the weights of FCMAC. With the learning algorithm, a wellparameterized FCMAC can be achieved for the required performance. Secondly, with the experimental data of HD702 ship, a research based on FCMAC was done on hydrodynamic parameters’ nonlinear function of three dimensional space, resulting in a nonlinear parameter model which can selfadaptive to change with different navigating speed, ocean condition, and course. Finally, simulation results indicate that the modeling method with FCMAC has high speed and high accurate, with the error rate below 10％. And the algorithm is proved to be effective.

关键词： fuzzy CMAC hydrodynamic parameters nonlinear parameter model neural network

作者: Yuntao Dai Liqiang Liu Xiren Zhao

作者单位: Department of Science Harbin Engineering University Harbin,Heilongjiang Province,China Department of AutomationHarbin Engineering University Harbin,Heilongjiang Province,China Department of Automation Harbin Engineering University Harbin,Heilongjiang Province,China

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-6

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）