Investigation of Steering Dynamics Ship Model Identification Based on PSO-LSSVR

摘要：

According to the high-order nonlinearity and parameter uncertainty of the ship steering dynamics, it is difficult to establish the accurate mathematical model by using normal identification methods. To solve this problem, a new kind of Least Squares Support Vector Regression based on the Particle Swarm Optimization (PSO-LSSVR) is proposed. This method can select the parameters of LSSVR automatically without trial and error, thus ensure the accuracy of parameters optimization. Apply this method to the model identification of the ship steering dynamics, and compare the identification effect with the experimental reference data. The PSO-LSSVR is able to establish the system model effectively, the structure is simple and generalization ability is well.

关键词： Ship Maneuvering Particle Swarm Optimization Least Squares Support Vector Regression Nonlinear System Identification

作者: Sheng Liu Jia Song Bing Li Gaoyun Li

作者单位: Department of Automation University of Harbin Engineering Harbin,Heilongjiang Province,150001 China

会议类型: 国际会议

会议名称: The 2nd International Symposium on Systems and Control in Aeronautics and Astronautics(第二届航空航天系统与控制国际会议 ISSCAA 2008)

会议地点: 深圳

会议语种:英文

页码: 537-542

在线出版日期: 2008-12-10（万方平台首次上网日期，不代表论文的发表时间）