Model Predictive Control-Based Path-Following for Tail-Actuated Robotic Fish
Model Predictive Control-Based Path-Following for Tail-Actuated Robotic Fish
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DOI：
10.1115/1.4043152
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发表时间：
2019-07-01
影响因子：
1.7
通讯作者：
Tan, Xiaobo
中科院分区：
文献类型：
--
作者：
Castano, Maria L.;Tan, Xiaobo
人们对使用自主水下机器人监测淡水和海洋环境越来越感兴趣。特别是，像鱼一样推进和操纵自己的机器人，通常被称为机器鱼，已经成为水生环境的移动传感平台。机器鱼的高度非线性和常欠驱动的动力学特性给这些机器人的控制带来了重大挑战。在这项工作中，我们提出了一种非线性模型预测控制（NMPC）方法来实现尾巴驱动机器鱼的路径跟踪，该方法可以适应非线性动力学和驱动约束，同时最小化控制工作量。考虑到尾部驱动的循环特性，控制设计基于平均动力学模型，其中由尾部跳动产生的水动力使用Lighthill的大振幅细长体理论捕获。提出了一种基于机器人游动和转弯测量数据的高效模型参数识别方法。在尾翼拍频固定的情况下，尾翼振荡的偏置和幅值作为待操作的物理变量，通过非线性映射与控制输入相关联。在求解NMPC问题时，引入了一种控制投影法，以适应控制输入的扇形约束，同时使优化复杂度最小化。仿真和实验结果都证明了该方法的有效性。特别是，通过与其他方法的比较，显示了控制投影方法的优点。
There has been an increasing interest in the use of autonomous underwater robots to monitor freshwater and marine environments. In particular, robots that propel and maneuver themselves like fish, often known as robotic fish, have emerged as mobile sensing platforms for aquatic environments. Highly nonlinear and often under-actuated dynamics of robotic fish present significant challenges in control of these robots. In this work, we propose a nonlinear model predictive control (NMPC) approach to path-following of a tail-actuated robotic fish that accommodates the nonlinear dynamics and actuation constraints while minimizing the control effort. Considering the cyclic nature of tail actuation, the control design is based on an averaged dynamic model, where the hydrodynamic force generated by tail beating is captured using Lighthill's largeamplitude elongated-body theory. A computationally efficient approach is developed to identify the model parameters based on the measured swimming and turning data for the robot. With the tail beat frequency fixed, the bias and amplitude of the tail oscillation are treated as physical variables to be manipulated, which are related to the control inputs via a nonlinear map. A control projection method is introduced to accommodate the sector-shaped constraints of the control inputs while minimizing the optimization complexity in solving the NMPC problem. Both simulation and experimental results support the efficacy of the proposed approach. In particular, the advantages of the control projection method are shown via comparison with alternative approaches.