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March 26, 2026Asian Journal of Control0 citations

Time‐varying distributed optimization algorithms with nonuniform gradient gain

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ZWZhaoxin WangHCHuabin ChenDGDi Gao

Key Points

  • The central aim is to develop algorithms for solving time-varying distributed optimization problems in multi-agent systems.
  • Developed two time-varying distributed control algorithms: one without an estimator, another with an estimator.
  • Proved consensus among agents in finite time under mild conditions.
  • Minimized sum of time-varying convex cost functions.
  • Both algorithms achieved consensus among agents effectively.
  • Simulations confirmed the theoretical results of optimization controllers.

Abstract

Abstract In this work, two time‐varying distributed control algorithms are investigated for solving the time‐varying distributed optimization problems of continuous‐time multi‐agent systems with a single‐integrator. One algorithm is developed without an estimator, and the other algorithm is designed with an estimator. It can be proved that under some mild conditions, these two algorithms not only achieve consensus within finite time among all agents, but also minimize the sum of time‐varying convex cost functions. Finally, the effectiveness of the theoretical results is verified through the simulations of distributed optimization controllers designed based on multi‐agent networks.

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Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69c4cddcfdc3bde44891aa62https://doi.org/10.1002/asjc.70090
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