船舶减摇鳍逆模式小波神经网络自适应控制  

Inverse Mode Wavelet Neural Network Adaptive Control of Fin Stabilized System

作　　者：李晖[1] 郭晨[2] 李晓方[3] 

机构地区：[1]大连海事大学自动化与电气工程学院,大连116026 [2]大连海事大学航海动态仿真实验室,大连116026 [3]大连电子学校计算机科,大连116023

出　　处：《系统仿真学报》2004年第2期326-328,355,共4页Journal of System Simulation

摘　　要：根据船舶横摇运动的特点,本文提出以伪随机二元序列信号(PRBS)作为波倾角仿真输入信号,将逆模式小波神经网络自适应控制方法应用于船舶减摇鳍控制系统,取得了良好的减摇效果。仿真实验表明此方法能够克服传统PID 控制适应性差的缺点,具有较好的容错性和较强的适应非线性的能力。Based on the characteristics of ship roll motion, the method of inverse mode wavelet neural network adaptive control is presented and applied to the control system of the fin stabilizer of ship in this paper, in which pseudo random binary signal (PRBS) is adopted as simulation input signal of wave slope angle. Effectiveness of reducing ship roll motion is obviously observed. Simulation results indicate that this method can improve the shortcoming of poor adaptability of conventional PID control, and that the control system has better characteristics of fault tolerance and stronger nonlinear adapting ability.

关 键 词：船舶减摇鳍 伪随机二元序列 逆模式小波神经网络 自适应控制 

分 类 号：U661.3[交通运输工程—船舶及航道工程] TP391.9[交通运输工程—船舶与海洋工程]