Cooperative Optimization Hunting Control of Multi-MSV Based on Reinforcement Learning

In this paper, a cooperative hunting optimal control problem is studied for multimarine surface vehicle (MSV) systems based on reinforcement learning (RL). First, in order to enhance the efficiency of cooperative hunting, a novel task allocation method is proposed based on a leader–follower structur...

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Main Authors: Yuanhao Wang, Weiwei Bai, Wenjun Zhang
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Applied Computational Intelligence and Soft Computing
Online Access:http://dx.doi.org/10.1155/acis/1415549
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author Yuanhao Wang
Weiwei Bai
Wenjun Zhang
author_facet Yuanhao Wang
Weiwei Bai
Wenjun Zhang
author_sort Yuanhao Wang
collection DOAJ
description In this paper, a cooperative hunting optimal control problem is studied for multimarine surface vehicle (MSV) systems based on reinforcement learning (RL). First, in order to enhance the efficiency of cooperative hunting, a novel task allocation method is proposed based on a leader–follower structure, where follower and leader MSVs perform the target encircling task and the target tracking task, respectively. Second, on the basis of task allocation, adaptive control design is employed for the follower MSVs to enhance the control performance of target encircling; optimal feedback control design combined with adaptive feedforward control design is considered using the RL algorithm for the leader MSVs to ensure the optimality of target tracking. Finally, the stability of the multi-MSV hunting control system is guaranteed and all signals are uniformly ultimately bounded based on the Lyapunov theory in the closed-loop system. The effectiveness of the proposed scheme is demonstrated through simulation results.
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institution OA Journals
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publishDate 2025-01-01
publisher Wiley
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series Applied Computational Intelligence and Soft Computing
spelling doaj-art-b745e6c6f51c4d72880a4ee3d74293d32025-08-20T02:29:29ZengWileyApplied Computational Intelligence and Soft Computing1687-97322025-01-01202510.1155/acis/1415549Cooperative Optimization Hunting Control of Multi-MSV Based on Reinforcement LearningYuanhao Wang0Weiwei Bai1Wenjun Zhang2Navigation CollegeNavigation CollegeSchool of Maritime Economics and ManagementIn this paper, a cooperative hunting optimal control problem is studied for multimarine surface vehicle (MSV) systems based on reinforcement learning (RL). First, in order to enhance the efficiency of cooperative hunting, a novel task allocation method is proposed based on a leader–follower structure, where follower and leader MSVs perform the target encircling task and the target tracking task, respectively. Second, on the basis of task allocation, adaptive control design is employed for the follower MSVs to enhance the control performance of target encircling; optimal feedback control design combined with adaptive feedforward control design is considered using the RL algorithm for the leader MSVs to ensure the optimality of target tracking. Finally, the stability of the multi-MSV hunting control system is guaranteed and all signals are uniformly ultimately bounded based on the Lyapunov theory in the closed-loop system. The effectiveness of the proposed scheme is demonstrated through simulation results.http://dx.doi.org/10.1155/acis/1415549
spellingShingle Yuanhao Wang
Weiwei Bai
Wenjun Zhang
Cooperative Optimization Hunting Control of Multi-MSV Based on Reinforcement Learning
Applied Computational Intelligence and Soft Computing
title Cooperative Optimization Hunting Control of Multi-MSV Based on Reinforcement Learning
title_full Cooperative Optimization Hunting Control of Multi-MSV Based on Reinforcement Learning
title_fullStr Cooperative Optimization Hunting Control of Multi-MSV Based on Reinforcement Learning
title_full_unstemmed Cooperative Optimization Hunting Control of Multi-MSV Based on Reinforcement Learning
title_short Cooperative Optimization Hunting Control of Multi-MSV Based on Reinforcement Learning
title_sort cooperative optimization hunting control of multi msv based on reinforcement learning
url http://dx.doi.org/10.1155/acis/1415549
work_keys_str_mv AT yuanhaowang cooperativeoptimizationhuntingcontrolofmultimsvbasedonreinforcementlearning
AT weiweibai cooperativeoptimizationhuntingcontrolofmultimsvbasedonreinforcementlearning
AT wenjunzhang cooperativeoptimizationhuntingcontrolofmultimsvbasedonreinforcementlearning