Distributed online optimization of high-order multi-agent systems

Distributed online optimization problem for continuous-time multi-agent systems with the form of high-order integrator is studied in this paper. In order to minimize the regret, a distributed online optimization algorithm is developed via consensus idea, PI control idea and gradient descent. Moreover, we show that under the proposed algorithm, the regret bound approaches a constant when the operating time tends to infinity.