...
首页> 外文期刊>Journal of Hydrodynamics >APPLICATION OF A NEURAL NETWORK PREDICTOR/CONTROLLER TO DYNAMIC POSITIONING OF FLOATING STRUCTURES
【24h】

APPLICATION OF A NEURAL NETWORK PREDICTOR/CONTROLLER TO DYNAMIC POSITIONING OF FLOATING STRUCTURES

机译:神经网络预测器/控制器在浮式结构动力定位中的应用

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

An on-line training functional-link neural network predictor/controller for dynamic positioning of water surface structures is described in this paper. The on-line training neural network predictor acquires the knowledge about the system using a small number of samples of the latest system status measured on board of the structure. The trained function-link neural network is used with an optimal controller to control the output of the system. The accuracy and robustness of the on-line training predictor are demonstrated through the numerical simulations of two ship maneuvers. The on-line training neural network predictor/controller is applied to the dynamic positioning (station-keeping) of a ship in a uniform current with and without external environmental disturbances. The results of the numerical simulations are very satisfactory.
机译:本文描述了一种用于水面结构动态定位的在线训练功能链接神经网络预测器/控制器。在线训练神经网络预测器使用少量在结构板上测量的最新系统状态的样本来获取有关系统的知识。经过训练的功能链接神经网络与最佳控制器一起使用,以控制系统的输出。在线训练预测器的准确性和鲁棒性通过两次船舶操纵的数值模拟得到了证明。在线训练神经网络预测器/控制器被应用到船舶在不受外部环境干扰的情况下以均匀电流进行动态定位(站位维护)。数值模拟的结果非常令人满意。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号