Distributed constraint optimization for discrete-time multiagent systems with event-triggered communication

This paper investigates the distributed optimization problem (DOP) with equality constraint in discrete-time multiagent systems (MASs) in which the global optimization objective is constituted by the summation of local objective functions. Firstly, by employing the Lagrange multiplier method, we convert the convex optimization problem with equality constraint into a consensus problem of MASs. Secondly, to reduce the communication burden, a type of event-triggered control protocol is proposed to enable all agents achieving consensus. Thirdly, by employing the Lyapunov function method and a set of inequality techniques, we establish some sufficient conditions to ensure that all agents converge to consensus and successfully solve the original DOP. Finally, a numerical simulation example is presented to validate the effectiveness of the theoretical analysis.