基于模糊神经网络理论对水下拖曳体进行深度轨迹控制  

Depth Trajectory Control of an Underwater Towed Vehicle Based on Fuzzy Neural Network Theory

作　　者：吴家鸣[1] 熊小辉[1] 

机构地区：[1]华南理工大学交通学院,广东广州510640

出　　处：《海洋技术》2006年第2期1-6,共6页Ocean Technology

基　　金：国家自然科学基金资助项目(40276034)

摘　　要：以华南理工大学开发的自主稳定可控制水下拖曳体为研究对象,首先通过水下拖曳体在拖曳水池样机中的试验取得试验数据后作为训练样本,采用LM BP算法,建立基于神经网络理论构建的可控制水下拖曳体轨迹与姿态水动力的数值模型。在此基础上设计了一个控制系统,它主要由两部分组成:基于遗传算法的神经网络辨识器和基于模拟退火改进的遗传算法的模糊神经网络控制器。以满足预先设定的拖曳体水下监测轨迹要求为控制依据,由控制系统确定为达到所要求的运动轨迹而应采用的迫沉水翼转角,以此作为输入参数,通过LM BP神经网络模型的模拟计算预报在这一操纵动作控制下的拖曳体所表现的轨迹与姿态特征。数值模拟计算结果表明:该系统的设计达到了所要求的目的;借助这一系统,可以有效地实现对拖曳体的深度轨迹控制。A neural network model to predict hydrodynamic performance of an underwater towed vehicle under certain control manipulation is first established based on LMBP algorithm. The training samples for the model are provided by towing tank experiments on the prototype of self-stable controllable underwater towed vehicle developed by South China University of Technology. A depth trajectory control system for the towed vehicle is designed in order to accomplish vehicle trajectory manipulation. This system is mainly composed of tow parts ; neural network identification based on genetic algorithm and a fuzzy neural network controller based on simulated annealing genetic algorithm, In numerical simulation on trajectory control of the towed vehicle, deflection of the vehicle＇s depressing wing is adjusted at every time step by the proposed control system to match the trajectory of the vehicle with a pre-designated one. The value of the deflection is taken as input parameter for the LMBP neural network model ;trajectory and attitude behavior of the towed vehicle under the control manipulation can then be predicted by the LMBP model. Numerical simulation result of this paper indicates that design of the depth trajectory control system for the towed vehicle is successful;the trajectory of the towed vehicle can be effectively controlled by means of the proposed depth trajectory control system.

关 键 词：水下拖曳体 深度轨迹控制 神经网络 模糊算法 遗传算法 

分 类 号：TV131.2[水利工程—水力学及河流动力学] P715.5[天文地球—海洋科学]