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In the operation process of ZB48 dual-channel ultra-high speed cigarette packing unit, the fault downtime of aluminum foil cutting assembly is long, which accounts for 77.4% of the total downtime, and the main phenomenon is caused by the falling of aluminum foil. The cam-like appearance of the aluminum foil paper tightening roll is designed to ensure that the total length of the periphery is equal to that of a piece of aluminum foil paper, and the power transmission mode is optimized to eliminate the phenomenon of falling off the torn pieces of aluminum paper. The results show that the aluminum foil cutting component based on the new improved tensioning roller meets the requirements of the continuous and stable operation of the ultra-high speed packaging unit. Through six months of tracking analysis, the average daily shutdown time of the aluminum foil components is reduced to 5.6 minutes, which reaches the predetermined target.

In this paper, we investigate the globally optimal Kalman filtering problem for uncertain stochastic systems with one-step autocorrelated process noises, cross-correlated noises, random one-step sensor delay and multiple packet dropouts. The multiplicative noises are used to characterize the random disturbances existing in systems. Random one-step sensor delay and multiple packet dropouts are characterized by employing two Bernoulli distributed random variables with known conditional probabilities. By separating the random variables from the non-random terms in the transmission and measurement matrices of the addressed dynamical systems, the process noises and measurement noises in the augmented systems depend on the state and the stochastic uncertain perturbations. The process noises are one-step autocorrelated and cross-correlated with the measurement noises. For this complicated systems, a globally optimal Kalman filtering algorithm is developed in the minimum mean square error (MMSE) sense. Finally, we provide a simulation example to illustrate the performance of the proposed filtering approach.