Formation Control of an Underactuated Autonomous Undersea Vehicle Based on Distributed Model Predictive Control
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摘要: 分布式模型预测控制(DMPC)相较于集中式模型预测控制具有更低的计算量、更强的容错性和鲁棒性, 被广泛应用于多智能体编队控制。文中提出了一种基于DMPC的欠驱动自主水下航行器(AUV)编队控制方法, 基于局部邻居信息为各AUV控制器构建预测控制的代价函数和约束条件, 通过优化算法求解一定时域内的最优控制输入。同时, 针对编队系统可能存在的障碍物避碰问题和通信时延问题, 分别设计了基于距离和相对视线差的避障方法, 以及在接收到所有邻居信息后再求解的等待机制。仿真结果表明, 采用文中方法, 多航行器编队能够在障碍及通信时延条件下保持队形稳定。Abstract: Compared with centralized model predictive control, distributed model predictive control(DMPC) is characterized by lower computational complexity and stronger fault tolerance and robustness, and it is widely used in multiagent formation control. In this study, an underactuated autonomous undersea vehicle(AUV) formation control method based on DMPC is proposed. Based on local neighbor information, the cost function and constraints of predictive control are constructed for each AUV controller, and the optimal control input in a certain time domain is solved by using an optimization algorithm. To solve the obstacle avoidance problem and communication delay problem that may exist in the formation system, obstacle avoidance methods based on distance and relative line of sight, as well as a waiting mechanism for problem solving after receiving all neighbor information, are designed. The simulation results demonstrate that, by using the method proposed in this study, the multi-AUV formation can remain stable under the conditions of obstacles and communication delays.
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表 1 障碍物信息
Table 1. Obstacle information
位置信息${\text{/m}}$ ${R/{\rm{m}} }$ ${d}_{{\rm{safe}}}$${\text{/m}}$ (110, 15) 20 30 -
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