Composite Finite-Time Resilient Control for Cyber-Physical Systems Subject to Actuator Attacks.

Cyber-physical systems (CPSs) seamlessly integrate communication, computing, and control, thus exhibiting tight coupling of their cyber space with the physical world and human intervention. Forming the basis of future smart services, they play an important role in the era of Industry 4.0. However, CPSs also suffer from increasing cyber attacks due to their connections to the Internet. This article investigates resilient control for a class of CPSs subject to actuator attacks, which intentionally manipulate control commands from controllers to actuators. In our study, the supertwisting sliding-mode algorithm is adopted to construct a finite-time converging extended state observer (ESO) for estimating the state and uncertainty of the system in the presence of actuator attacks. Then, for the attacked system, a finite-time converging resilient controller is designed based on the proposed ESO. It integrates global fast terminal sliding-mode and prescribed performance control. Finally, an industrial CPS, permanent magnet synchronous motor control system, is investigated to demonstrate the effectiveness of the composite resilient control strategy presented in this article.

Spatiotemporally mapping of the relationship between NO2 pollution and urbanization for a megacity in Southwest China during 2005-2016.

Nitrogen dioxide (NO2) significantly contributes to air pollution. Long-term NO2 exposure is harmful to human health. The NO2 pollution in China has surpassed developed countries and attracts international attention. To understand the spatial and temporal distributions of NO2 across Chengdu in Southwest China, a random forest (RF) model was developed based on NO2 environmental monitoring data, the Ozone Monitoring Instrument (OMI) satellite retrievals, and geographic covariates. The RF model showed good performance with a cross validation R2 of 0.77, and a root mean square error (RMSE) of 11.0 µg/m3. The ground-level NO2 concentrations of Chengdu for 2005-2016 were predicted using the developed model with the multiyear population weighted NO2 concentration being 41.7 ±â€¯11.7 µg/m3. The predicted NO2 concentrations exhibited a clear seasonal variation trend with winter being the highest and summer being the lowest. Furthermore, higher NO2 concentrations in the downtown areas were observed than that in the rural areas indicating the former being attributed to more anthropogenic sources. The population weighted NO2 concentrations with deseasonlization were relatively high during 2011-2013. The NO2 concentration increased at a rate of 0.81 µg/m3/year before 2011 (43.4 ±â€¯11.2 µg/m3) and decreased at a rate of -1.03 µg/m3/year after 2013 (44.8 ±â€¯12.8 µg/m3).