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首页> 外文期刊>Ocean Engineering >Hierarchical image-based visual serving of underwater vehicle manipulator systems based on model predictive control and active disturbance rejection control
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Hierarchical image-based visual serving of underwater vehicle manipulator systems based on model predictive control and active disturbance rejection control

机译：基于模型预测控制和主动扰动抑制控制的水下车辆机械手系统的分层图像视觉服务

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摘要

The image-based visual servoing (IBVS) problem of a redundant underwater vehicle manipulator system (UVMS) with an eye-in-hand camera is investigated in this paper. With consideration of system constraints, dynamic uncertainties, and the absence of vehicle velocity sensors for a typical UVMS, we propose a hierarchical control architecture, which is composed of an unscented Kalman filtering (UKF)-based vehicle motion estimator, a kinematic model predictive IBVS controller, and two decoupled dynamic velocity controllers for the vehicle and the manipulator, respectively. In details, the underwater vehicle velocities are estimated by UKF with visual measurements based on the UVMS kinematic model. With these estimates, a nonlinear model predictive controller (MPC) is designed to solve the IBVS problem of UVMSs and generate velocity commands for the underwater vehicle and the manipulator, simultaneously. The visual kinematic model of UVMSs is used to predict the future trajectories, and the field-of-view, manipulator joint angle, and UVMS velocity constraints are handled when solving the optimization problem. To reduce the system complexity of UVMSs, the high-dimensional UVMS's dynamic model is decoupled into two low-dimensional models of the vehicle and the manipulator, and a dynamic inversion-based active disturbance rejection control (DI-ADRC) method is developed for dynamic controller design. The physical interaction effects between the vehicle and manipulator are considered as external disturbances acting on each other, which are estimated by extended state observers (ESO) in ADRC. The simulation experiments with a typical UVMS are performed to demonstrate the effectiveness of the proposed hierarchical IBVS controller in dealing with system redundancy, constraints and uncertainties.
机译：冗余水下车辆用机械手系统（UVMS）与眼睛在手相机的基于图像的视觉伺服（IBVS）的问题在本文中进行了研究。通过考虑系统的限制，动态不确定，并且不存在车辆速度传感器，用于典型UVMS，我们提出了分层控制体系结构，它是由一个无迹卡尔曼滤波（UKF）系车辆运动估计器，运动模型预测IBVS的控制器，以及两个分别解耦用于车辆和机械手动态速度控制器，。详细地说，所述水下航行速度由UKF基于所述UVMS运动学模型视觉测量估计。与这些估计，非线性模型预测控制器（MPC）被设计为解决UVMSs的IBVS问题并生成用于所述水下航行器和操纵器的速度的命令，同时进行。 UVMSs的视觉运动模型被用来预测未来的轨迹，和场的视图，求解优化问题时机械手的关节角度，和UVMS速度约束的处理方式。为了减少UVMSs的系统复杂性，高维UVMS的动态模型被解耦成在车辆和操作器，和基于反转动态抗扰控制的两个低维模型（DI-ADRC）方法被用于动态开发控制器的设计。车辆和机械手之间的物理相互作用的影响被认为是作用于互相外部干扰，这是由在ADRC伸长状态观察员（ESO）估计。仿真实验具有典型UVMS进行展示在处理系统冗余，约束和不确定性所提出的分层IBVS控制器的有效性。

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