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Game-Based Target Enclosing Control of Autonomous Surface Vehicles Against Actuator Faults

delete2026-07-13
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PRE
AI
H
Hongye Zhang
Y
Yong Chen
DOI:10.1109/tits.2026.3703591delete
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Abstract

Abstract

En 中文
Autonomous surface vehicles (ASVs), as vital vehicles in port traffic management, necessitate robust control research for their complex operations. This article investigates the target enclosing control of ASVs suffering from actuator faults and environment disturbances, with a focus on ensuring reliable traffic monitoring tasks. Fault tolerant control (FTC) based on a two-level differential game is proposed to encircle the target. First, the cooperative target enclosing problems of ASVs with actuator faults are proposed and auxiliary control laws are developed to achieve the maritime traffic monitoring tasks. Unlike the traditional kinetic controller design method, the two-level games are established in this paper to design the controllers. On the one hand, the total disturbances consisting of actuator faults and environmental disturbances is considered as one player, constituting a zero-sum differential game with the kinetic controller. On the other hand, based on the topology graph, the whole ASV system constructs a graphical game, in which each vehicle is a player to find the control policies achieving the global Nash equilibrium (GNE). Moreover, the two-level game problem is solved by adaptive dynamic programming, which leads to the distributed kinetic FTC laws. The control policies enable the target enclosing task, the fault-tolerant task and the Nash equilibrium (NE) task. Finally, the result analysis proves the effectiveness of the algorithm.
Keywords:
Autonomous surface vehicle
traffic monitoring
graphical game
zero-sum differential game
actuator faults

Journal

IEEE Transactions on Intelligent Transportation Systems cover
IEEE Transactions on Intelligent Transportation Systems
IF:
8.4
Papers:
9.5K
Citations:
6.3W

Organization

U
university of electronic science and technology of china
Scholars:
1.1W
Papers: 4.3K
Citations: 4
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