This article studies the robust model predictive control of heterogeneous multi-agent systems with polytopic uncertainties and time delay. Moreover, some constraints on the amplitude of the control inputs are considered for each agent. The proposed distributed controllers are designed as state feedback. The goal is to design the feedback gains such that the multiagent system achieves consensus in the presence of time-delay and model uncertainties. For this purpose, an optimization problem is proposed, and by using the constrained robust model predictive control and the appropriate Lyapunov–Krasovskii functional, sufficient conditions are obtained to solve the optimization problem through solving the linear matrix inequalities. In this regard, a theorem is presented, and it is proved that the consensus errors converge to zero. Finally, the effectiveness of the proposed method is illustrated using numerical simulations.

本文研究了具有多主题不确定性和时滞的异构多主体系统的鲁棒模型预测控制。而且，对于每个代理，考虑了对控制输入的幅度的一些约束。提出的分布式控制器被设计为状态反馈。目的是设计反馈增益，以使Multiagent系统在存在时间延迟和模型不确定性的情况下达成共识。为此，提出了一个优化问题，并通过使用约束鲁棒模型预测控制和适当的Lyapunov–Krasovskii函数，通过求解线性矩阵不等式获得了充分的条件来解决优化问题。在这方面，提出了一个定理，并证明了共识误差收敛到零。最后，