Adaptive event-triggered-based efficient model predictive control for nonlinear systems subject to cyber attacks and...

In this paper, a novel event-triggered-based decay aggregation efficient model predictive control (DAEMPC) problem is investigated for nonlinear systems represented by interval type-2 (IT2) T-S fuzzy models subject to cyber attacks and actuator saturation. First, to make full use of communication resources, an adaptive event triggered (AET) strategy is applied to determine the data transmission in the sensor to controller link. A Bernoulli random process is introduced to denote the denial-of-service (DoS) attack, and the polytopic description method is utilized to characterize the actuator saturation. Second, the efficient model predictive controller concerning the decay aggregation approach is designed for the considered nonlinear networked control system (NCS). It involves offline solving feedback control law and designing ellipse feasible sets whose projections are vertical in the x-space, and online optimizing the perturbation variable instead of the whole performance objective function. Different from the previous studies, the presented AET-based DAEMPC algorithm not only compensates for the deficiencies in the communication network, but also enlarges the initial feasible set and reduces the computational burden. Finally, the validity of the presented algorithm is illustrated through the simulation of continuous stirred tank reactor (CSTR).