基于神经网络的水下机器人三维航迹跟踪控制  

Three-dimensional path tracking control for autonomous underwater vehicle based on neural network

作　　者：贾鹤鸣[1] 张利军[2] 齐雪[3] 杨立新[3] 

机构地区：[1]东北林业大学机电工程学院,黑龙江哈尔滨150040 [2]西北工业大学航海学院,陕西西安710072 [3]哈尔滨工程大学自动化学院,黑龙江哈尔滨150001

出　　处：《控制理论与应用》2012年第7期877-883,共7页Control Theory & Applications

基　　金：国家自然科学基金资助项目(61174047);教育部博士点基金资助项目(20102304110003);XX预研项目资助项目(51316080301)

摘　　要：本文研究了水下机器人三维航迹跟踪控制问题.在充分考虑了模型中不确定水动力系数和外界海流干扰的基础上,提出了基于神经网络的自适应输出反馈控制方法.控制器由3部分组成:基于动态补偿器的输出反馈控制项、神经网络自适应控制项和鲁棒控制项.神经网络所需的自适应学习信号由线性观测器提供.基于Lyapunov稳定性理论证明了控制系统的稳定性.最后针对某AUV进行了空间三维航迹跟踪控制仿真实验,结果表明设计的控制器可以较好地克服时变非线性水动力阻尼对系统的影响,并对外界海流干扰有较好的抑制作用,可以实现三维航迹的精确跟踪.Considering the uncertain hydrodynamic coefficients and environmental current disturbances, we propose an adaptive output feedback neural network controller for the three-dimensional path tracking control of an autonomous underwater vehicle （AUV）. The controller consists of three control terms： the output feedback control term of the dynamic compensator, the neural network adaptive control term and the robust control term. An observer is designed to provide the neural network with the adaptive learning signal. The stability of the controller is analyzed by Lyapunov theory. A three- dimensional path tracking simulation is carried out on an experimental AUV; simulations results show that the designed controller provides high tracking precision, effectively suppresses the effect of the time-varying nonlinear hydrodynamic damping on the AUV system, and significantly attenuate the external currents disturbances.

关 键 词：水下机器人 三维航迹跟踪 神经网络 自适应控制 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]