摘要
针对粒子群优化算法易于陷入局部最优的缺点,提出了一种改进的粒子群优化算法,并将改进的算法应用到船舶纵向运动模型的参数辨识。对辨识结果进行了验证,表明,利用改进的粒子群优化算法有较快的收敛速度和稳定性,辨识获得的水动力参数计算的结果误差均在允许范围内,得到的纵向运动的状态参数与理论观测值吻合度较高,辨识算法有效可行。
An improved PSO is proposed to solve the problem that PSO is easily trapped in the local minima. The improved PSO is applied in the parameter identification of ship vertical motions. The verification of parameter identification shows that the improved PSO has higher convergence speed and stability. After the parameter identification, the error between calculating results of hydrodynamic model and the experiment data is in the acceptable range. The state of vertical motions fits well to the theoretical calculation from experiment. The identification algorithm is effective.
出处
《船舶力学》
EI
北大核心
2010年第1期44-50,共7页
Journal of Ship Mechanics
基金
国防科学技术工业委员会基础研究基金资助项目(41314020201)
关键词
参数辨识
粒子群优化
水动力参数
纵向运动
parameter identification
particle swarm optimization （PSO）
hydrodynamic parameter
vertical motions
