Abstract
In this paper, the distributed online optimisation problem is considered in an unknown dynamic environment. Compared with the existing results, an unknown dynamic environment causes the problem to be more challenging. An online optimisation algorithm is designed based on distributed mirror descent and distributed average tracking technology. The analysis of dynamic regret is presented and a bounded regret is obtained. Some simulations are given to verify the validity of the designed algorithm.
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