摘要
舵操纵的稳定性关系到船舶的安全行驶,由于定常回转直径是衡量操纵稳定性的重要指标,常通过建立船舶运动模型并进行舵参数仿真,获取较优的定常回转直径。针对上述优化方法计算量大、效率低等问题,提出采用粒子群算法的舵参数优化方法。通过采用四自由度MMG运动模型,以某教学实习船作为仿真优化对象。利用上述方法优化后的回转直径和横倾角都减小。仿真结果表明,粒子群算法对舵参数的优化能使船舶在回转过程中回转直径和回转横倾效果达到最佳。
The stability of the rudder control is related to the safety of the ship maneuvering, and the constant turning diameter is an important index to measure the handling stability of the ship. The optimal constant turning di- ameter is usually acquired through the establishment of ship motion model and the rudder parameter simulation. For the problem of large amount of calculation and low efficiency in the general optimization method, we proposed a parti- cle swarm optimization （PSO） algorithm for the rudder parameters optimization research. On the basis of four degrees of freedom motion mathematical model （MMG） in this study, a training ship was selected as the optimization object, both the turning diameter and the heeling angle decreased ＂after used this method. The simulation results indicate that the particle swarm optimization algorithm of rudder parameters can make the ship achieve the best rotary diameter and rotary heeling performance in the rotary process.
出处
《计算机仿真》
CSCD
北大核心
2015年第12期332-336,共5页
Computer Simulation
基金
青年教师基金(2013QN111)
关键词
舵参数
回转直径
横倾角
粒子群算法
Rudder parameters
Turning diameter
Roiling angle
Particle swarm algorithm
