Distributed Optimization of High-Order Multi-Agents Based on Activatable Event-Triggering Mechanisms

This paper addresses the distributed optimization problem (DOP) in high-order multi-agent systems(MAS) considering limited communication resources. A decouplable hierarchical algorithm scheme is designed, which decomposes the DOP of high-order agents into the solution of the optimal signal generator and the tracking control problem of actual dynamics, reducing algorithm complexity and enhancing scalability. A novel activatable event-triggering mechanism (ETM) is proposed by combining time triggering mechanisms and dynamic triggering mechanisms. This activatable ETM ensures the existence of positive minimum inter-event time (PMIET) and effectively reduces communication resource consumption while making the agent states converge to the global optimal point of DOP. Based on the hierarchical scheme and the activatable ETM, a novel distributed optimization algorithm for high-order MAS is developed. Theoretical analysis and simulations verify that the proposed algorithm can guarantee that the agent states asymptotically converge to the global optimal solution, and the communication burden is significantly reduced.