Multi‐event‐based distributed cooperative predictive control for the multi‐agent system

Abstract In this paper, we provide the detailed distributed cooperative predictive control scheme for the multi‐agent system (MAS) affected by the network delays. Firstly, we restate the distributed cooperative predictive control problem by introducing iterative learning‐based MAS, which can guarantee the cooperative predictive control of the MAS. To alleviate the unfavorable network constrains, the multi‐event‐triggered conditions are formulated via considering the predictive and error data sufficiently. With these preparations, the well‐posed Roesser‐type two‐dimensional (2D) system is achieved equivalently to the distributed iterative learning predictive system. On this basis, we employ 2D predictive system analysis and control theory to realize the predictive control for the equivalent 2D system and then obtain the collaborative predictive control for the MAS under multi‐event‐triggered mechanism. The corresponding stability criteria, controller, and observer gains are provided by the executable matrix constraints and algorithms design. To conclude the paper, the numerical example is proposed to illustrate the effectiveness and practicability of the provided methods and algorithms.