| 引用本文: | 倪菲,赵言正,叶军,朱婷.动力学效应的动力定位船舶模型在线辨识算法[J].控制理论与应用,2011,28(11):1525~1533.[点击复制] |
| NI Fei,ZHAO Yan-zheng,YE Jun,ZHU Ting.Online dynamic-model recognition for dynamically positioning vessel by dynamic effect[J].Control Theory and Technology,2011,28(11):1525~1533.[点击复制] |
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| 动力学效应的动力定位船舶模型在线辨识算法 |
| Online dynamic-model recognition for dynamically positioning vessel by dynamic effect |
| 摘要点击 2798 全文点击 1998 投稿时间：2010-09-06 修订日期：2010-12-08 |
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| DOI编号 10.7641/j.issn.1000-8152.2011.11.CCTA101033 |
| 2011,28(11):1525-1533 |
| 中文关键词 船舶动力定位 船舶模型在线辨识 无味卡尔曼滤波器 动力学效应 |
| 英文关键词 vessel dynamic positioning online vessel model recognition unsent Kalman filter dynamic effect |
| 基金项目 上海市科委人才计划博士后基金资助项目(10R21421600); 上海市浦东新区博士后基金资助项目(274.10S19). |
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| 中文摘要 |
| 由于船舶模型的高度非线性以及外界干扰力、推进器推力的无法测量性, 导致它们的在线辨识和估计显得十分困难. 本文提出一种以动力学效应为基础, 应用无味卡尔曼滤波器(unscented Kalman filters, UKF)进行动力定位船舶动力学模型、外界载荷以及推进器推力在线辨识的算法. 此算法能够在动力定位过程中不断求解船舶模型和其受到的载荷力, 使得拥有这些参数的船舶模型和载荷所反映出的动力学效应不断逼近传感器检测到的运动反馈. 基于此原理, 用这些参数作为名义上的船舶模型、外界力、推进器推力就能够完成高效、自适应的定位控制. 通过控制仿真, 证明了此算法的有效性和正确性. |
| 英文摘要 |
| Due to the nonlinearity in a vessel model, and the immeasurable disturbance force as well as thruster forces, it is difficult to recognize the vessel model online. An online vessel-model-recognition algorithm based on unscented Kalman filters(UKF) and dynamic effect is proposed. By solving the vessel model associated with external loading forces during dynamical positioning, this algorithm continuously generates the dynamic effect which approaches the sensor feedback. Based on this principle, an effective and adaptive position control can be performed by the nominal vessel model, external and thruster forces. Simulation results in position control validate the effectiveness of the proposed algorithm. |