In this study, the authors consider distributed computation of the Stein equations with set constraints, where each agent or node knows a few rows or columns of coefficient matrices. By formulating an equivalent distr...
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In this study, the authors consider distributed computation of the Stein equations with set constraints, where each agent or node knows a few rows or columns of coefficient matrices. By formulating an equivalent distributedoptimisation problem, they propose a projection-based algorithm to seek least-squares solutions to the constrained Stein equation over a multi-agent system network. Then, they rigorously prove the convergence of the proposed algorithm to a least-squares solution for any initial condition, and moreover, provide a simplified distributed algorithm with an exponential convergence rate for the case without constraints.
A distributedoptimisation problem is investigated for disturbed continuous-time multi-agent systems with discrete-time communication and gradient measurement. First, a distributedoptimisation algorithm with time-tri...
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A distributedoptimisation problem is investigated for disturbed continuous-time multi-agent systems with discrete-time communication and gradient measurement. First, a distributedoptimisation algorithm with time-triggered communication and gradient measurement is proposed. Then an event-triggered communication strategy and an event-triggered gradient measurement strategy are developed, and a distributedoptimisation algorithm combining these two event-triggered strategies is designed, in which the two event-triggered strategies are free of Zeno behaviour. Moreover, the exponential convergence of system can be guaranteed by using the internal model design to reject the external disturbance. Finally, an example illustrates the effectiveness of the proposed algorithms.
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