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System Identification and Controller Design of a Novel Autonomous Underwater Vehicle

机译:一种新型自主水下车辆的系统识别与控制器设计

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摘要

Autonomous underwater vehicle is an effective tool for humans to explore the ocean. It can be used for the monitoring of underwater structures and facilities, which puts forward more accurate and stable requirements for the system operation of the autonomous underwater vehicle. This paper studies the system and structural design, including the parameter identification design and control system design, of a novel autonomous underwater vehicle called “Arctic AUV”. The dynamic mathematical model of the “Arctic AUV” was established, and the system parameter identification method based on the multi-sensor least squares centralized fusion algorithm was proposed. The simplification of the mathematical model of the robot was theoretically derived, and the online parameter identification and motion control were combined, so that the robot could cope with the influence of the arctic water velocity and external turbulence. Based on the hybrid control scheme of adaptive PID and predictive control, the accurate motion control of the “Arctic AUV” was realized. A prototype of “Arctic AUV” was developed, and system parameter identification experiments were carried out in indoor pool water. Hybrid adaptive and predictive control experiments were also carried out. The validity of the parametric design method in this paper was verified, and by comparative experiment, the effect of the control method proposed in this paper was better than the traditional method.
机译:自主水下车辆是人类探索海洋的有效工具。它可用于监控水下结构和设施,这对自动水下车辆的系统操作提出了更准确和稳定的要求。本文研究了一个名为“北极AUV”的新型自治水下车辆的系统和结构设计,包括参数识别设计和控制系统设计。建立了“北极AUV”的动态数学模型,提出了基于多传感器最小二乘集中融合算法的系统参数识别方法。理论地,机器人的数学模型的简化是组合的,并且组合了在线参数识别和运动控制,使得机器人可以应对北极水速度和外部湍流的影响。基于自适应PID和预测控制的混合控制方案,实现了“北极AUV”的准确运动控制。开发了“北极AUV”的原型,系统参数识别实验在室内游泳池水中进行。还进行了混合自适应和预测控制实验。本文的参数化设计方法的有效性进行了验证,并通过对比实验,本文提出的控制方法的效果比传统的方法更好。

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