This study explores a new robust consensus control strategy for uncertain multiagent systems and provides an event-based solution to adaptive dynamic programming (ADP) based optimal control. Rather than the control function, the feedback system established symmetrical to the physical system allows the optimal consensus control issue to be handled by the optimal control protocol of an augmented affine system. The feedback system focuses on an auxiliary variable formed in light of the optimality principle and the virtual control input built on a critic neural network (NN). Analysis reveals that the auxiliary variable benefits from decreasing the influence of uncertainty on control performance, while the proposed approach is implemented with fewer communication resources since the critic NN is updated as events occur. Finally, evidence from simulation findings validates the theoretical results.