Uncertainty and disturbance rejections of complex dynamical networks via truncated predictive control

摘要

This study investigates the combined problems of uncertainty and disturbance rejections and syn- chronization of a class of complex dynamical networks with input delay. Specifically, a new uncertainty and disturbance estimator (UDE)-based truncated predictive control approach is used to simultaneously compensate the effects of unknown bounded disturbance and known input delay. The proposed approach relies on the conventional state prediction model to estimate the current state for the feedback by using the delayed state information and the estimation error is treated as an additional disturbance. Then, the effects of uncertainty and disturbance in the system model are robustly canceled with an appropriate filter based on the UDE approach. In addition, a set of sufficient conditions that guarantees the synchro- nization of the concerned system, the input delay compensation and the asymptotic disturbance rejection is derived with the aid of Lyapunov stability theory. In numerical examples, the proposed control method shows the better state estimation and robust synchronization performance by suppressing the effects of uncertainty and disturbance without any prior knowledge about them. (c) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.