水下机械手水动力学分析及控制方法研究

Research on hydrodynamic analysis and control method of underwater manipulators

水下机械手可以代替人类在水下的极端环境中完成各种复杂作业,目前已得到广泛应用,针对水下机械手控制方法的研究已成为水下机械手领域研究的热点,但目前的研究多局限于静水环境,忽略自然水体中存在的定向流,造成研究环境与实际工况存在较大差异。本研究考虑水体中定向流的影响,建立基于水动力学模型的水下机械手动力学模型,提出基于定向流影响的RBF神经网络进行模型整体逼近的非线性鲁棒自适应控制方法,并进行稳定性分析。通过分析不同速度定向流的轨迹跟踪仿真结果,证明该控制方法在控制误差、稳定性及自适应性方面相比常见的计算力矩法存在明显优势。

Underwater manipulators can replace humans to complete various complex operations in extreme underwater environments and have been widely used.Research on the control methods of underwater manipu⁃lators has become a hot spot in the field of underwater manipulators,but current research is limited in the static water environment,ignoring the directional flow existing in the natural water which causes a big differ⁃ence between the research environment and the actual working conditions.This research considered the influ⁃ence of directional flow in the water body,established a dynamic underwater manipulator model based on hy⁃drodynamic model,and proposed a nonlinear robust adaptive control method using RBF neural network for overall model approximation based on the influence of directional flow.Stability analysis was also carried out.By analyzing the trajectory tracking simulation results of directional flow at different speeds,it is proved that the control method has obvious advantages compared with the common calculation torque method in terms of control error,stability and adaptability.