An Event-Triggered Predictive Control for Weight Control System

In this paper, we deal with the weight control of cigarette production process, and we establish a system model with uncertainties and give an event-triggered predictive control algorithm. First, according to the actual situation in the production process, the corresponding relationship between the weight of the cigarette and the height of the leveling disc is established. The uneven distribution and uncertainty of the cut tobacco are taken into account in the model simultaneously. Secondly, a model predictive controller is designed, which can effectively reduce the weight error caused by detection lag, uneven distribution, and random density of cut tobacco. A prediction model and cost function for predicting the future weight of cigarettes are established, and the optimal control sequence is solved when the cost function is the smallest. Finally, considering the limited computing and communication resources of the controller, an event-triggered mechanism is introduced to effectively reduce the computing cost of the controller. Simulation results demonstrate the effectiveness of the proposed event-triggered predictive control method in the cigarette weight control system.