Truncated predictive control for delayed cyber–physical systems under deception attacks

In this work, the state tracking, input delay prediction, uncertainty and disturbance rejection problems are studied for the delayed cyber–physical systems under uncertainties, nonlinearities and external disturbances in which the addressed model is described by the fuzzy technique. More specifically, such an input-delayed system is linearized through an interval type-2 fuzzy technique accompanied by a parallel distribution compensation method. Further, the presence of constant input delays in the examined system is proficiently compensated with the assistance of a truncated predictor feedback approach. In parallel, the impacts of external disturbances and uncertainties that are occurred in the system are estimated by means of uncertainty and disturbance estimator method in an efficacious way. With the help of this estimated information, an uncertainty and disturbance estimator-based truncated predictive tracking control protocol is formulated to acquire the state tracking results of the underlying system in the presence of external disturbances and uncertainties. Remarkably, in this study, the interval type-2 fuzzy is blended with the designed reference system. Furthermore, the secure tracking control law is designed for the considered system under the random deception attacks. To address the deception attacks, the Bernoulli stochastic distribution is considered in this study. Moreover, the constraints are expressed for computing the truncated predictive feedback control gain matrices. Conclusively, the numerical simulation analysis is carried out to demonstrate the usefulness of the devised approach.