This study aimed to design chaos-based synchronized dynamic keys and develop an improved chaos-based advanced encryption standard (AES) algorithm with the proposed synchronized random keys. First, based on sliding mode control (SMC) technology, a rippling control scheme was introduced to guarantee the synchronization between master–slave discrete chaotic systems. Under the synchronization, the same dynamic random chaos signals could be simultaneously obtained at the transmitter and receiver in communication systems. Then, a novel modified AES cryptosystem with dynamic random keys based on chaos synchronization was presented. In a traditional AES cryptosystem, a static key is used, and it must be exchanged in advance and confirmed to be safely kept. However, in the proposed design, by introducing the synchronization technology of chaotic systems, the static key becomes dynamic and random, and it does not need to be kept or transmitted in open channels. Consequently, the disadvantage of key storage could be eliminated and the security of encryption could be improved. Finally, the developed chaos-based AES (CAES) algorithm has been applied to construct a novel image encryption algorithm. The statistical analysis, histogram, information entropy, and correlation indexes have been calculated and analyzed through simulation experiments in order to demonstrate the capability and improvement of this presented CAES cryptosystem.

This paper is concerned with a novel secure data transmission design based on adaptive synchronization of master and slave unified chaotic systems. First, by introducing an augmented error state, an adaptive continuous sliding mode control (SMC) is derived to guarantee the synchronization of unified chaotic systems. Then, the secret message embedded in the master chaotic system can be transmitted from transmitter to receiver. Different from previous works using discontinuous SMC, the undesired chattering phenomenon can be fully eliminated, and it becomes possible to precisely recover the embedded secret message at the receiver. Last, an example is given to illustrate the success of secure data transmission with the continuous SMC developed in this paper.

This study is concerned with robust synchronization for master–slave chaotic systems with matched/mismatched disturbances and uncertainty in the control input. A robust sliding mode control (SMC) is presented to achieve chaos synchronization even under the influence of matched/mismatched disturbances and uncertainty of inputs. A proportional-integral (PI) switching surface is introduced to make the controlled error dynamics in the sliding manifold easy to analyze. Furthermore, by using the proposed SMC scheme even subjected to input uncertainty, we can force the trajectories of the error dynamics to enter the sliding manifold and fully synchronize the master–slave systems in spite of matched uncertainties and input nonlinearity. As for the mismatched disturbances, the bounds of synchronization errors can be well estimated by introducing the limit of the Riemann sum, which is not well addressed in previous works. Simulation experiments including matched and mismatched cases are presented to illustrate the robustness and synchronization performance with the proposed SMC synchronization controller.

In an industrial mass production pattern, quality prediction is one of the important processes when guarding quality. The products are extracted periodically or quantitatively for inspection in order to observe the relationship between process variation and engineering specification. When these irregularities are not instantly detected by lot sampling inspection, lot defectives are produced, and the defective cost increases. Failure to identify defects during sampling inspection leads to product returns or harm to business reputation. Press casting is a common mass production method in the metal industry. After the metal is molten at a high temperature, high pressure is injected into the mold, and then it is solidified and formed in the mold. Thus, pressure stability inside the mold is one of the key factors that influences quality. The melting point of aluminum alloy is normally around 650 °C, but there was no sensor that could withstand this high temperature. To combat this, we developed a high temperature resistant sensor and installed it into pressure casting mold grounded on the principles of fluid mechanics and experts’ suggestions in order to realize the impact of pressure change on the mold. To our limited knowledge, it was a seminal study on predicting mold’s casting quality via in-mold pressure data. We propose a press casting quality prediction method based on machine learning. By collecting the in-mold pressure data in real time. Savitzky-Golay Filter is used for data smoothing, and first-order difference is taken to extract the time interval of an actual injection of molten metal in-to the mold. We extract the key data that influence the quality and employ XGBoost to establish a classifier. In the experiment we prove that the method achieves good accuracy of quality prediction and recall of defectives for in-mold pressure. Via this model, we not only can save large amount of time and costs, but also can carry out maintenance warnings in advance, notify professionals to stop produce defective products, reduce the shipping risk and maintain reputation so as to strengthen its competitive edge.

In this paper, a robust control design of chaos suppression is considered for generalized four-dimensional (4D) Lorenz–Stenflo systems subjected to matched/mismatched uncertainties and input nonlinearity. It is implemented by using rippling sliding mode control (SMC). A proportional-integral (PI) type scalar switching surface is designed such that the controlled dynamics in the sliding manifold becomes easy to analyze. Furthermore, only by using single rippling SMC even with input nonlinearity can we ensure the existence of the sliding mode for the controlled dynamics and suppress the chaotic behavior in a manner of rippling. Under the proposed control scheme, the chaos behavior in uncertain generalized 4D Lorenz–Stenflo systems subjected to mismatched uncertainties can be robustly suppressed to predictable bounds, which is not addressed in the literature. The numerical simulation results including matched/mismatched uncertainties and nonlinear inputs are presented to verify the robustness and validity of the rippling sliding mode controller.