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The fault detection and estimation problems for the physical layer network in the cyber-physical systems with unknown external disturbances are investigated in this study. Both bias fault and loss of efficiency scenarios are considered for the actuators. Based on the adaptive threshold method and sliding mode observer approach, a distributed fault detection observer (DFDO) is constructed for each physical layer node to detect the occurrence of actuator faults. Then a relative global estimation error system is defined for the distributed fault estimation observer (DFEO). Compared with the existing results, the proposed DFEO can provide the estimation for not only the actuator bias faults but also the actuators' efficiency factors under the impact of exogenous disturbance with two gain dynamic update processes. Finally, the feasibility and effectiveness of the given DFDO and the DFEO are examined by Lyapunov stability method and the simulation results.
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http://dx.doi.org/10.1016/j.isatra.2019.12.002 | DOI Listing |
This study aims to tackle the tracking control problem of multiple unmanned surface vessels (USVs). It considers the impact of connectivity-hybrid cyber-attacks in the networked level, and wave-induced disturbances, as well as severe and nonsevere unified modeling rudder angle faults in the physical level. To do this, the study establishes USV models, taking into account actuator fault and cyber-attack modeling.
View Article and Find Full Text PDFIEEE Trans Neural Netw Learn Syst
September 2025
Class incremental learning (CIL) offers a promising framework for continuous fault diagnosis (CFD), allowing networks to accumulate knowledge from streaming industrial data and recognize new fault classes. However, current CIL methods assume a balanced data stream, which does not align with the long-tail distribution of fault classes in real industrial scenarios. To fill this gap, this article investigates the impact of long-tail bias in the data stream on the CIL training process through the experimental analysis.
View Article and Find Full Text PDFFront Public Health
September 2025
Western Switzerland Center for Indoor Air Quality and Radon (croqAIR), Transform Institute, School of Engineering and Architecture of Fribourg, HES-SO University of Applied Sciences and Arts Western Switzerland, Fribourg, Switzerland.
Since the 1980s, radon has been recognized as a public health concern in Switzerland and internationally. In an effort to more accurately estimate the number of lung cancer cases attributable to radon exposure, Swiss health authorities initiated the creation of radon measurements into a centralized national database. As of 2025, this database comprises approximately 300,000 measurements from 150,000 buildings across the country.
View Article and Find Full Text PDFISA Trans
August 2025
School of Automation, Shenyang Aerospace University, Shenyang, Liaoning Province 110136, China. Electronic address:
When a failure occurs in bearings, vibration signals are characterized by strong non-stationarity and nonlinearity. Therefore, it is difficult to sufficiently dig fault features. 1D local binary pattern (1D-LBP) has the advantageous feature to effectively extract local information of signals.
View Article and Find Full Text PDFSci Robot
September 2025
Google DeepMind, London, UK.
Modern robotic manufacturing requires collision-free coordination of multiple robots to complete numerous tasks in shared, obstacle-rich workspaces. Although individual tasks may be simple in isolation, automated joint task allocation, scheduling, and motion planning under spatiotemporal constraints remain computationally intractable for classical methods at real-world scales. Existing multiarm systems deployed in industry rely on human intuition and experience to design feasible trajectories manually in a labor-intensive process.
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