基于粒子群优化算法的动力定位非线性观测器设计
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引用本文:郭亮琨,杨宣访,王家林?覮,刘蕾.基于粒子群优化算法的动力定位非线性观测器设计[J].计算技术与自动化,2020,(4):1-6
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郭亮琨,杨宣访,王家林?覮,刘蕾 (海军工程大学 电气工程学院湖北 武汉430033) 
中文摘要:针对船舶动力定位控制系统中的状态估计问题,提出了一种非线性状态观测器设计方法。采用类Lyapunov方法设计无源观测器,以估计误差的低通滤波信号作为增广状态变量,通过在观测器方程中引入增广状态变量以减少高频运动分量对低频运动参数估计的影响,采用粒子群优化算法对观测器增益矩阵中的9个关键参数进行组合寻优进一步提高观测器动态性能。还以一艘供给船为例进行仿真分析,验证了所设计非线性观测器的有效性。
中文关键词:动力定位  观测器  粒子群优化
 
Design of Nonlinear Observer for Dynamic Positioning Based on Particle Swarm Optimization Algorithm
Abstract:Aiming at the state estimation problem in ship dynamic positioning control system,a nonlinear state observer design scheme is proposed. The passive observer is designed by Lyapunov-like method,and the low-pass filtered signal of the estimation error is used as an augmented state variable. By introducing augmented state variables in the observer equation to reduce the impact of high-frequency motion components on low-frequency motion parameter estimation,the particle swarm optimization algorithm is used to optimize the nine key parameters in the observer gain matrix to further improve the dynamic performance of the observer. This paper takes a supply ship as an example to analyze and verify the effectiveness of the designed nonlinear observer.
keywords:dynamic positioning  observer  particle swarm optimization
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