【作者】 王冠；

【导师】 白涛； 王孟军；

【作者基本信息】 哈尔滨工程大学 ， 控制工程（专业学位）， 2018， 硕士

【摘要】 当航行体在水中高速航行时,航行体表面压力会下降到此时的饱和压力,水会汽化形成空泡。超空泡的形成可以大幅地提高水下航行体的速度,但空泡的产生和溃灭引起的力学效应对航行体的稳定航行会产生重要影响,特别是由于空泡形态的变化使超空泡航行体受力产生强非线性关系,使得超空泡航行体控制研究具有很大难度,因此超空泡形态的估计成为超空泡航行体运动控制中的关键问题之一。本文将以超空泡航行体的缩比模型的水洞实验为依据,通过在水流中控制空化器的攻角变化,来模拟水下航行体在实际应用环境中的运动控制,继而使用强跟踪卡尔曼滤波算法对超空泡的形态进行估计问题研究,并使用仿真手段验证了估计算法的正确性及此种算法能够满足某种实际环境中的超空泡航行体控制的需要。论文的主要研究内容如下:首先,利用已有的理论知识建立超空泡航行体的数学模型。由于作用在空化器上的流体动力以及航行体尾部与空泡壁作用产生的滑行力都容易受到外部干扰而产生强非线性特性,且对于此类条件的建模目前没有成熟的方案,因此文中在此部分首先在理想条件下建立超空泡航行体数学模型,然后以后续的实验数据为基础,研究实际噪声对模型的扰动,从而对模型进行完善。其次,利用搭建好的重力式水洞实验平台,完成实验相关的内容。文中介绍了实验相关设备的安装和调试等工作流程,其中包括实验平台的搭建;航行体模型的安装;伺服电机控制系统的结构及功能;加压通气设备的功能;流量及压力检测设备的安装及调试;记录空化过程的高速摄像机的调试等,并将记录下来的实验数据根据超空泡形态研究的需要进行初步处理。再次,以空化器在运动过程中的超空泡内、外压力和形态数据为基础,并根据传感器的测量范围和实际情况对测量数据进行野值剔除,然后使用强跟踪卡尔曼滤波算法对超空泡形态进行估计,完善超空泡航行体的数学模型。最后,对超空泡航行体模型在Matlab环境下进行控制仿真,仿真结果表明,本文设计的超空泡形态估计算法能够在实际噪声干扰环境中对超空泡的形态进行较为准确的估计,估计误差在超空泡航行体控制器的允许范围内,不会对超空泡航行体的运动稳定性造成影响,证实本文设计的超空泡形态估计算法的正确性。更多还原

【Abstract】 When the vehicle moves in the water with high-speed,the pressure of vehicle’s surface will drop to the saturation pressure at the same time,the water will be vaporized to form a bubble.The formation of supercavitation can greatly improve the speed of underwater vehicles,but the formation and collapse of the supercavitation caused the mechanical effects which will have an important impact on the stability of the navigation,the strong nonlinear relationship caused by supercavitation makes the study of cavitation theory difficult.Therefore,the estimation of the supercavitation morphology is a key problem in the motion control of the supercavitation vehicle.In this paper,we will estimate the shape of the supercavity based on the water tunnel experiment of the shrinkage supercavitation model,simulate the motion of underwater vehicle in the actual application environment by controlling the angle of the cavitation and then use STF to estimate the morphology of supercavitation.Finally,verify the correctness of the estimation algorithm in the simulation method and it can satisfy the the need of control of the supercavitation in some practical environment.The main research contents are as follows:Firstly,use the existing theoretical knowledge to establish the mathematical model of the supercavitation vehicle.As the hydrodynamic on the cavitation device and the sliding force generated by the interaction between the tail of vehicle and the edge of supercavitation are both easy to be subjected to external interference and produce strong nonlinear characteristics,and there is no mature solution to the modeling of such conditions,so in this part,we establish a mathematical model of supercavitation vehicle in ideal conditions first,then study the disturbance of the actual noise to the model and improve the model based on the subsequent experimental data.Secondly,complete the related content of the experiment on the water tunnel experimental platform.In this part,we introduce the whole flow of installation and debugging of experimental equipment,including the construction of experimental platform;installation of the supercavitating vehicle model;the structure and function of the servo motor control system;the function of pressurized ventilation equipment;installation and debugging of flow and pressure testing equipment;high speed camera debugging for recording cavitation process and so on.The recorded experimental data are preliminarily processed according to the need for the study of supercavitation.Thirdly,based on the internal,external pressure and morphological data of the supercavitation during the cavitation movement process,and according to the measuring range of the sensor and actual situation,get rid of the abnormal data from all of the measured data,then use STF to estimate the form of supercavitation and improve the mathematical model for supercavitation vehicles.Finally,make a controlling simulation verification in Matlab environment,the results proof: the STF can accurately estimate the morphology of supercavitation in the environment with actual noise interference,as the estimation error is in the allowable range of the supercavitation vehicle controller,so there is no disturbance on the motion stability of the supercavitation vehicle,the estimation algorithm designed in this paper is proven be correct.更多还原