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超空泡高速航行体动力学建模与控制设计
引用本文:王京华,张嘉钟,于开平,魏英杰,黄文虎,吕瑞.超空泡高速航行体动力学建模与控制设计[J].哈尔滨工业大学学报,2010,42(9):1351-1355.
作者姓名:王京华  张嘉钟  于开平  魏英杰  黄文虎  吕瑞
作者单位:哈尔滨工业大学 航天学院,哈尔滨 150001,哈尔滨工业大学 航天学院,哈尔滨 150001,哈尔滨工业大学 航天学院,哈尔滨 150001,哈尔滨工业大学 航天学院,哈尔滨 150001,哈尔滨工业大学 航天学院,哈尔滨 150001,哈尔滨工业大学 航天学院,哈尔滨 150001
基金项目:国家自然科学基金重点资助项目;高等学校博士点基金资助项目;国家自然科学基金资助项目
摘    要:为了研究超空泡航行体的动力学建模和控制问题,根据空泡膨胀独立性原理,研究了空泡的记忆效应及其对空泡形态的影响,详细计算了超空泡航行体各部分所受的流体动力,计算过程中还考虑了空化器的定向效应和空泡尾部的上飘变形,研究了航行过程中尾翼效率变化规律,建立了超空泡航行体非线性动力学模型.设计了基于输入输出精确线性化的鲁棒极点配置控制器,深度跟踪性能较好,不足之处是控制输入饱和问题和滑行力的不利影响.为解决输入饱和问题,设计了预测控制方法并通过约束航行体尾部和空泡壁的距离使尾部不与空泡壁相接触,避免了滑行力的出现,有利于减少摩擦阻力,提高了航行体的运动稳定性.

关 键 词:超空泡  记忆效应  超空泡航行体  滑行力  预测控制

Dynamics modeling and control design for a high-speed supercavitating vehicle
Affiliation:WANG Jing-hua,ZHANG Jia-zhong,YU Kai-ping,WEI Ying-jie,HUANG Wen-hu,LU Rui(School of Astronautics,Harbin Institute of Technology,Harbin 150001,China;WANG Jing-hua,ZHANG Jia-zhong,YU Kai-ping,WEI Ying-jie,HUANG Wen-hu,LU Rui(School of Astronautics,Harbin Institute of Technology,Harbin 150001,China;WANG Jing-hua,ZHANG Jia-zhong,YU Kai-ping,WEI Ying-jie,HUANG Wen-hu,LU Rui(School of Astronautics,Harbin Institute of Technology,Harbin 150001,China;WANG Jing-hua,ZHANG Jia-zhong,YU Kai-ping,WEI Ying-jie,HUANG Wen-hu,LU Rui(School of Astronautics,Harbin Institute of Technology,Harbin 150001,China;WANG Jing-hua,ZHANG Jia-zhong,YU Kai-ping,WEI Ying-jie,HUANG Wen-hu,LU Rui(School of Astronautics,Harbin Institute of Technology,Harbin 150001,China;WANG Jing-hua,ZHANG Jia-zhong,YU Kai-ping,WEI Ying-jie,HUANG Wen-hu,LU Rui(School of Astronautics,Harbin Institute of Technology,Harbin 150001,China
Abstract:In order to explore dynamics modeling and control of supercavitating vehicles, memory effect of the cavity and its influence on the shape of cavity were researched based on the principle of cavity expansion independence. The cavitator orientation effect and cavity flotation were taken into account in computing the hydrodynamic forces of all parts of the supercavitating vehicle. Efficiency of the fin with the change of the fin immersion depth while the vehicle was traveling underwater was researched. A more precise nonlinear dynamics model of supercavitating vehicle was established. Robust pole placement controller was designed after exact input-output linearization. This controller has good control performance in depth tracking. Its shortcomings are input saturation and adverse effects of planing force. Model predictive control controller was designed to solve the problem of input saturation by restricting the distance between tail part of vehicle and the cavity wall, so that the planing force was avoided, the friction drag was reduced and the motion stability of the vehicle was improved.
Keywords:supercavitation  memory effect  supercavitating vehicles  planing force  predictive control
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