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<p>When communication between agents in a distributed optimization problem for a multi-agent system is disconnected, the system must adapt its communication topology to ensure that all agents can still converge to the desired optimal point. This paper proposes a distributed optimization control approach that addresses this challenge, while also accounting for communication delays among agents. To this end, a distributed optimization controller is designed in conjunction with an active topology switching law. A stability condition is derived in the form of linear matrix inequalities, which considers both the optimization parameters and an upper bound on the communication delays. This upper bound is also incorporated into the switching topology mechanism. When agents become disconnected, the proposed switching law activates to reconfigure the topology so that all agents can still reach consensus on the optimal solution. When reconfiguring the network under this switching topology law, any communication links that have failed or been disconnected are ignored and not used in the new topology. Finally, numerical examples, including comparative simulations for different systems, are provided to illustrate the efficiency and superiority of the theoretical results.</p>

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Distributed optimization-based control with active topology switching for networked systems subject to communication delays

  • 期刊论文

  • 发表日期：

    2026年3月31日

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  • Farshad Rahimi,
  • Reza Mahboobi Esfanjani

摘要

When communication between agents in a distributed optimization problem for a multi-agent system is disconnected, the system must adapt its communication topology to ensure that all agents can still converge to the desired optimal point. This paper proposes a distributed optimization control approach that addresses this challenge, while also accounting for communication delays among agents. To this end, a distributed optimization controller is designed in conjunction with an active topology switching law. A stability condition is derived in the form of linear matrix inequalities, which considers both the optimization parameters and an upper bound on the communication delays. This upper bound is also incorporated into the switching topology mechanism. When agents become disconnected, the proposed switching law activates to reconfigure the topology so that all agents can still reach consensus on the optimal solution. When reconfiguring the network under this switching topology law, any communication links that have failed or been disconnected are ignored and not used in the new topology. Finally, numerical examples, including comparative simulations for different systems, are provided to illustrate the efficiency and superiority of the theoretical results.