极大似然法在水下机器人系统辨识中的应用

APPLICATION OF MAXIMUM-LIKELIHOOD TO IDENTIFICATION OF UNDERWATER VEHICLE

主要探讨了极大似然参数估计法及其松弛算法 ,将它们应用于水下机器人运动模型的辨识中 .利用水下机器人的海上类Z型试验数据 ,辨识得到某智能水下机器人水动力系数 ,并对比了两种算法的结果 ,可看出松弛算法有更好的收敛性 .然后用辨识得到的水动力系数建立了水下机器人的运动模型 ,用运动仿真进行了模型验证 .仿真结果表明辨识得到的数学模型是可靠的 ,本方法对于水下机器人操纵与自适应控制的研究有较大的实际意义 .

Maximum_likelihood (ML) and its relaxation algorithm are discussed which are used to identify the mathematics model of an Underwater Vehicle (UV), the hydrodynamic derivatives of the UV were estimated from the trial data obtained through zigzag tests, and the better astringency of relaxation algorithm can be acquired from the contrast between the two methods.Then a simulation environment based on these parameters is established to verify the validity and effect of these methods.The result shows the model in credible and the methods are very useful for the research of maneuverability and adaptive control of underwater vehicles.