摘要
船舶运动控制具有较强的非线性、不确定性、大惯性、大滞后和慢时变特性,加上在航行过程中存在的干扰和噪声,使得航迹控制变得非常复杂,运用常规的PID算法难以达到期望的控制效果,不可能根据船舶动态特性和海况变化实现其参数的自动整定,总是偏离其最佳工作状态.文章首次在船舶运动控制中使用自适应神经网络MFA控制器,减少航迹波动幅度和次数,减小船舶航行时附加阻力.仿真结果表明MFA自动舵具有快速性、鲁棒性和稳定性的优点.
The control of ship movement is characterized by its strong non-linear, uncertain, large inertia, large delay and slow time-varying, with additional hydrodynamic disturbances and noises, all of which make the track control more complicated. Classical PID algorithms are unable to realize self-tuning on its parameters in accordance with ship movement features and sea conditions and always deviates its optimum working conditions. The model free adaptive （MFA ） controller is used in the control of ship movement which reduces amplitude and frequencies of fluctuation as well as course added resistance. The results showed that MFA autopilot have the advantages of high robustness, high speed and high stability.
出处
《船舶工程》
CSCD
北大核心
2008年第1期37-40,共4页
Ship Engineering
基金
高等学校博士学科点专项科研基金(20030151005)
交通部交通应用基础研究项目(200332922505)
中远集团科研项目:2006R02船舶自动操舵仪模拟器.
