Abstract
In this article, we study the optimal feedback control problems of knowledge dissemination processes in multilayer complex networks. First, a node-based model is established in multilayer complex networks and two collaborative control strategies are exerted to increase the scope and speed of knowledge dissemination, forming a closed-loop control system. Then, we develop a two-layer optimal control framework. At the upper level, the optimal solution of the control system is solved and sent to the lower layer. At the lower level, a model predictive controller (MPC) receives input information from the upper level and is formulated to decide on the network and then transmits it to its heterogeneous networks which can reduce control resources and computation complexity. Finally, numerical simulations are conducted to confirm the theoretical results.
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