ARV Nonlinear Disturbance Estimation Based on Extended State Observer
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摘要: 自主/遥控式水下机器人(ARV)在水下路径跟踪任务中易受复杂流场的干扰影响, 传统线性观测器面对流场的非线性扰动表现不佳。文中针对“思源号”ARV的非线性扰动估计问题，提出一种动态高增益扩张观测器方法。首先, 构建了ARV的非线性运动学与动力学模型, 并通过海试路径跟踪试验获得了外部干扰数据。其次, 引入动态增益补偿机制处理非线性系统观测问题, 有效克服了传统方法中利普希茨(Lipschitz)函数系数获取困难与参数整定依赖经验的难点, 并且通过引入性能约束参数解决了动态增益收敛性问题。为验证方法有效性, 开展与传统龙伯格观测器的对比仿真实验。结果表明, 所提观测器在干扰力、干扰力矩、纵荡速度、垂荡速度及艏摇角速度等状态估计中具有更快的收敛速度与更高的稳态精度, 显著提升了复杂扰动下的状态跟踪能力。
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关键词:
- 自主/遥控式水下机器人 /
- 扰动估计 /
- 扩张状态观测器
Abstract: Autonomous/remotely-operated vehicles(ARVs) are susceptible to complex flow field disturbances during underwater path tracking missions, where traditional linear observers exhibit suboptimal performance in addressing flow field-induced nonlinear disturbances. This paper proposed a dynamic high-gain extended observer method to resolve the nonlinear disturbance estimation challenge for the “Siyuan” ARV. Firstly, a nonlinear kinematic and dynamic model of the ARV was established, with external disturbance data acquired through sea trial path tracking experiments. Secondly, a dynamic gain compensation mechanism was introduced to address nonlinear system observation, effectively overcoming limitations in conventional methods such as the difficulty in determining Lipschitz function coefficient and empirical dependence in parameter tuning. The convergence of dynamic gains was rigorously ensured through the incorporation of performance constraint parameters. To validate the proposed method, comparative simulation experiments were conducted against traditional Luenberger observers. Results demonstrate that the developed observer achieves superior convergence speed and steady-state accuracy in estimating disturbance forces, disturbance moments, surge velocity, heave velocity, and yaw angular velocity. This advancement significantly enhances state tracking capability under complex disturbances. -
图 7 ARV扰动力合力与合力矩
Figure 7. Disturbance force resultant force and resultant torguet of ARV
图 8 动态高增益扩张观测器扰动力和力矩
Figure 8. Disturbance force and torque via dynamic high-gain expansion observer
图 9 龙伯格扩张观测器扰动力和力矩
Figure 9. Disturbance force and torque via Longberg extended observer
图 10 动态高增益扩张观测器航速和增益轨迹
Figure 10. Speed estimation and gain trajectory via dynamic high gain expansion observer
表 1 “思源号”ARV基本参数
Table 1. Parameters of Siyuan ARV
参数 数值 符号 质量/kg 3 432 m 重心位置/m (0, 0, 0) $({x_G}, {y_G}, {{\textit{z}}_G})$ 浮心位置/m (0, 0, －0.16) $ ({x_B}, {y_B}, {{\textit{z}}_B}) $ 主体长度/m 2.512 ${L_{{\text{arv}}}}$ 转动惯量/(kg·m2) (2 185.20, 3 806.20, 3 975.20) $({I_x}, {I_y}, {I_{\textit{z}}})$ 惯量积/(kg·m2) (20.40, －239.19, 8.10) $({I_{xy}}, {I_{y{\textit{z}}}}, {I_{{\textit{z}}x}})$ 排水体积/m3 3.415 V 
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表 2 无因次水动力系数列表
Table 2. Parameters of flexible intercepting net
系数 数值 系数 数值 ${X'_{\dot u}}$ −1.120$ \times $10−2 ${Z'_{\dot q}}$ −2.453$ \times $10−2 ${X'_{uu}}$ −5.000$ \times $10−2 ${Z'_{\dot w}}$ −1.318$ \times $10−1 $Z'_q$ 4.059$ \times $10−2 $Z'_*$ −1.063$ \times $10−2 $Z'_w $ −3.283$ \times $10−1 $Z'_{w\left| w \right|} $ −2.542$ \times $10−1 $Z'_{\left| w \right|} $ 1.090$ \times $10−2 $Z'_{ww} $ 2.112$ \times $10−1 $ N'_{\dot r} $ 1.062$ \times $10−2 $ N'_{v\left| v \right|} $ −2.157$ \times $10−1 $ N'_{r\left| r \right|} $ −1.424$ \times $10−2 $ N'_{\dot v} $ 9.513$ \times $10−3 $ N'_r $ −1.193$ \times $10−2 $ {N_{\left| v \right|r}} $ −2.775$ \times $10−2 $ N'_v $ −5.309$ \times $10−3
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