NARMAX Self-Tuning Controller for Line-of-Sight-Based Waypoint Tracking for an Autonomous Underwater Vehicle
NARMAX Self-Tuning Controller for Line-of-Sight-Based Waypoint Tracking for an Autonomous Underwater Vehicle
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DOI：
10.1109/tcst.2016.2613969
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发表时间：
2017-07
影响因子：
4.8
通讯作者：
R. Rout;B. Subudhi
中科院分区：
文献类型：
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作者：
R. Rout;B. Subudhi
本文针对自主水下航行器（AUV）的航向和下潜运动，考虑参数变化和算法的实际实现，设计了一种约束自校正控制器（CSTC）。AUV动力学中的参数可能由于有效载荷或物理结构的变化而变化。利用显著性回归量设计了非线性自回归滑动平均外生（NARMAX）模型，分别对AUV航向和下潜动力学进行辨识。在每个时刻使用递归扩展最小二乘算法更新NARMAX模型的参数。此外，使用所识别的模型，CSTC法律设计使用视线制导律跟踪期望的航路点。控制器增益更新在每个时刻满足执行器的约束和计算效率进行了研究，以实现开发的算法的实际实施。基于NARMAX的CSTC算法跟踪给定参考的有效性进行了验证，在实验环境中与有效载荷的变化和外部干扰。从所得到的结果，它的结论是，开发的控制算法是有效的AUV跟踪所需的航路点或航向/潜水参考。
In this brief, a constrained self-tuning controller (CSTC) is developed for the heading and diving motions of an autonomous underwater vehicle (AUV) considering the parameter variation and practical realization of the algorithm. Parameters in the AUV dynamics may vary due to change in payload or physical structure. A Nonlinear Auto-Regressive Moving Average eXogenous (NARMAX) model is designed using the significant regressors to identify the AUV heading and diving dynamics, respectively. The parameters of the NARMAX model are updated using a recursive extended least square algorithm at each time instant. Furthermore, using the identified model, a CSTC law is designed to track desired waypoints using line of sight guidance law. The controller gains are updated at each instant satisfying the actuator constraint and computational efficiency is studied in view of achieving the practical implementation of the developed algorithm. The efficacy of the developed NARMAX-based CSTC algorithm to track a given reference is verified in an experimental environment with payload variation and external disturbance. From the obtained results, it is concluded that the developed control algorithm is effective for an AUV to track desired waypoints or heading/diving reference.