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Finite-time optimal feedback control mechanism for knowledge transmission in complex networks via model predictive control

In this paper, the finite-time (FT) optimal feedback control problems of knowledge transmission processes in complex networks via model predictive control (MPC) have been studied. Firstly, we build a knowledge transmission Susceptible–Infected–Hesitation (SIH) model in complex networks. Secondly, in...

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Published in:Chaos, solitons and fractals solitons and fractals, 2022-11, Vol.164, p.112724, Article 112724
Main Authors: Wang, Sixin, Mei, Jun, Xia, Dan, Yang, Zhanying, Hu, Junhao
Format: Article
Language:English
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Summary:In this paper, the finite-time (FT) optimal feedback control problems of knowledge transmission processes in complex networks via model predictive control (MPC) have been studied. Firstly, we build a knowledge transmission Susceptible–Infected–Hesitation (SIH) model in complex networks. Secondly, interventional control strategies are designed to regulate the system parameters to improve the performance of knowledge dissemination, including improving self-learning ability, acquaintance influence, and review rate. With the help of the Lyapunov-based HJB optimal control method, the existence of the optimal solution to the economic optimal problem of the knowledge transmission control model is guaranteed. Then, the optimal control solution is derived by using Pontryagin’s maximum principle. To focus on the performance indicators and state trajectories of the system and enable the controller to modify in real-time according to the state in a fixed time interval as soon as possible, an MPC based on FT feedback is proposed for the first time. Furthermore, under feedback control and initial conditions, the control knowledge dissemination model is FT stable. Numerical simulations are provided to verify the proposed method. •Three interventional controls are designed to formulate a closed-loop knowledge dissemination system and the existence of concave optimal control is proved via the HJB method.•An MPC based on FT feedback is proposed firstly to focus on the performance indicators and state trajectories in a fixed time interval by feedback control mechanism and FT stabilization.•To study a relaxed Lyapunov-based control and Lyapunov MPC method with finite-time convergence for accelerating the knowledge propagation processes, we propose a novel semi-global finite-time stabilization and optimal control scheme.
ISSN:0960-0779
1873-2887
DOI:10.1016/j.chaos.2022.112724