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Nonlinear Model Predictive Control Applied to an Autonomous Underwater Vehicle
IEEE Journal of Oceanic Engineering ( IF 4.1 ) Pub Date : 2020-07-01 , DOI: 10.1109/joe.2019.2919860
Rafael Meireles Saback , Andre Gustavo Scolari Conceicao , Tito Luis Maia Santos , Jan Albiez , Marco Reis

This paper presents an experimental analysis of a nonlinear model predictive controller combined with an integral sliding mode control component and an explicit dead-time compensator applied to the closed-loop control of FlatFish, an autonomous underwater vehicle (AUV). The proposed strategy is composed of three control instances that can be integrated to deal with constraints, disturbances, and dead time. The integral sliding mode control instance is considered to attenuate unmeasured disturbance effects, the filtered Smith predictor component is used to compensate for the dead-time effect, and the model predictive control layer aims at systematically optimizing closed-loop performance with constraint satisfaction. The discussion highlights that any of these control layers can be either included or removed from the control chain, which depends on the challenges presented by the AUV problem. The benchmark for such evaluation is the original control chain of FlatFish, which is based on a P cascade controller. Experimental tests were performed with FlatFish in a saltwater tank located in Bremen, Germany, and showed the superior performance of the proposed system. The experimental results show that the proposed control chain may be effectively used to provide improved tracking performance as expected from theoretical analysis.

中文翻译:

应用于自主水下航行器的非线性模型预测控制

本文介绍了非线性模型预测控制器与积分滑模控制组件和显式死区时间补偿器相结合的实验分析,该控制器应用于自动水下航行器 (AUV) FlatFish 的闭环控制。所提出的策略由三个控制实例组成,可以集成这些实例来处理约束、干扰和死区时间。积分滑模控制实例被认为可以衰减未测量的扰动效应,滤波后的史密斯预测器组件用于补偿死区时间效应,模型预测控制层旨在系统地优化闭环性能并满足约束条件。讨论强调了这些控制层中的任何一个都可以包含在控制链中或从控制链中删除,这取决于 AUV 问题带来的挑战。这种评估的基准是FlatFish的原始控制链,它基于P级联控制器。在位于德国不来梅的盐水箱中使用 FlatFish 进行了实验测试,并显示了所提议系统的卓越性能。实验结果表明,所提出的控制链可以有效地用于提供如理论分析所预期的改进的跟踪性能。
更新日期:2020-07-01
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