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<p>In this paper, a distributed model predictive control method based on Nash optimization is proposed for the problem of cooperative target tracking by Multi-USV system under changes in formation topology caused by factors such as communication link variations and task re-assignment. Firstly, an Adaptive Formation Topology and Role Assignment (AFTRA) algorithm is designed to determine the role of each USV and the inter-USV topological relationships under switching topologies, achieving adaptive topology reconfiguration. Secondly, the formation tracking control problem under switching topologies is modeled as a distributed Nash game. Through potential game analysis, it is proven that this game possesses a pure-strategy Nash equilibrium (PNE). To enable the distributed solution of the aforementioned game equilibrium, a Nash Optimization-based Distributed Model Predictive Control (NDMPC) method is further proposed, which integrates the AFTRA algorithm with distributed iterative optimization to control the multi-USV system for cooperative target tracking. Convergence analysis demonstrates that a Nash equilibrium exists under fixed topology conditions. Moreover, even under topology switching, the system converges to an <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\epsilon \)</EquationSource> <EquationSource Format="MATHML"><math> <mi>ϵ</mi> </math></EquationSource> </InlineEquation>-Nash equilibrium provided that the dwell-time constraint is satisfied. Finally, simulation experiments validate the effectiveness of the proposed approach.</p>

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Nash-optimized DMPC for cooperative target tracking by multi-USV under switching topologies

  • 期刊论文

  • 发表日期：

    2026年3月5日

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  • Yuxi Ma,
  • Ligang Li,
  • Jiucai Jin

摘要

In this paper, a distributed model predictive control method based on Nash optimization is proposed for the problem of cooperative target tracking by Multi-USV system under changes in formation topology caused by factors such as communication link variations and task re-assignment. Firstly, an Adaptive Formation Topology and Role Assignment (AFTRA) algorithm is designed to determine the role of each USV and the inter-USV topological relationships under switching topologies, achieving adaptive topology reconfiguration. Secondly, the formation tracking control problem under switching topologies is modeled as a distributed Nash game. Through potential game analysis, it is proven that this game possesses a pure-strategy Nash equilibrium (PNE). To enable the distributed solution of the aforementioned game equilibrium, a Nash Optimization-based Distributed Model Predictive Control (NDMPC) method is further proposed, which integrates the AFTRA algorithm with distributed iterative optimization to control the multi-USV system for cooperative target tracking. Convergence analysis demonstrates that a Nash equilibrium exists under fixed topology conditions. Moreover, even under topology switching, the system converges to an \(\epsilon \) ϵ -Nash equilibrium provided that the dwell-time constraint is satisfied. Finally, simulation experiments validate the effectiveness of the proposed approach.