Comparative experimental evaluation of a new adaptive identifier for underwater vehicles
Comparative experimental evaluation of a new adaptive identifier for underwater vehicles
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新型水下航行器自适应识别器的对比实验评估
DOI：
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发表时间：
2013
期刊：
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通讯作者：
L. Whitcomb
中科院分区：
文献类型：
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作者：
C. McFarland;L. Whitcomb
本文报道了一种新型水下机器人自适应识别器及其局部稳定性证明和对比实验评价。自适应辨识算法估计了二阶刚体系统在驱动力和力矩影响下的水动力质量、二次阻力、重力和浮力参数。自适应模型辨识方法不需要其他标准方法，如传统的最小二乘法，需要测量车辆加速度。以前的自适应模型辨识方法主要集中在基于模型的自适应跟踪控制器，但这些方法不适用于对象不受控制、处于开环控制下或使用特定自适应跟踪控制器以外的任何控制律的情况；本文报告的自适应辨识器不需要参考轨迹跟踪，因此适用于这些常见的情况。报道了自适应辨识与常规最小二乘参数辨识的实验比较。自适应辨识模型与最小二乘辨识模型相似。
This paper reports a novel adaptive identifier for underwater vehicles as well as its local stability proof and comparative experimental evaluation. The adaptive identification algorithm estimates the hydrodynamic mass, quadratic drag, gravitational force, and buoyancy parameters of a second-order rigid-body plant under the influence of actuator forces and torques. Adaptive model identification methods do not require instrumentation of vehicle acceleration as required of other standard methods, such as conventional least squares. Previous adaptive model identification methods have focused on model-based adaptive tracking controllers however these approaches are not applicable when the plant is either uncontrolled, under open-loop control, or using any control law other than a specific adaptive tracking controller; the adaptive identifier reported herein does not require reference trajectory-tracking, and thus is applicable in these commonly occurring cases. An experimental comparison of adaptive identification and conventional least squares parameter identification is reported. The adaptively identified model is shown to be similar to the least squares identified model.