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This article considers the design problem of H∞$$ {H}_{\infty } $$ observer‐based fault‐tolerant control under three faulty cases: sensor only, actuator only, and both sensor and actuator faults. To save communication resources, the event trigger mechanism method is used for sensor‐to‐observer and observer‐to‐controller transmissions. In this case, the design method of the new H∞$$ {H}_{\infty } $$ observer is given for obtaining estimating both states and faults which are used to design observer‐based H∞$$ {H}_{\infty } $$ fault‐tolerant controllers. In particular, the virtual observer is designed to suppress the effects of faults on the system. As the virtual observer contains unmeasurable system information, the real observer is built on top of the virtual observer to eliminate the unmeasurable information. Finally, the feasibility of the approach is tested with a numerical example. [ABSTRACT FROM AUTHOR]

Road surface condition (RSC) is an important indicator in road safety studies, enabling transportation departments to employ it for conducting surveys, inspections, cleaning, and maintenance, ultimately contributing to improved performance in road upkeep. However, traditional recognition methods can be easily affected when extreme weather frequently occurs such as winter seasonal changes. To achieve real-time and automatic RSC monitoring, this paper proposes an improved Mask–region-based convolutional neural network (RCNN) based on Swin Transformer-PAFPN and a dynamic head detection network. Meanwhile, transfer learning is used to reduce training time, and data enhancement and multiscale training are applied to achieve better performance. The experimental results show that the proposed model achieves an outstanding mean average precision at 0.5 (mAP@0.5) score of 89.8 under favorable weather conditions characterized by clear visibility, surpassing other popular methods. Notably, the proposed model exhibits lower parameters and GigaFLOPS (GFLOPs) (72.41 and 158.35, respectively) compared to other popular methods, thus demanding fewer computational resources. Furthermore, in challenging weather conditions characterized by poor visibility, such as foggy and nighttime scenarios, the proposed model achieves mAP@0.5 scores of 78.50 and 82.40, respectively. These scores not only outperform those of other popular methods but also underscore the robustness of the proposed model in extreme weather conditions. This exceptional performance demonstrates the proposed model's effectiveness in addressing complex road conditions under various meteorological circumstances, providing reliable technical support for practical traffic monitoring and road maintenance. [ABSTRACT FROM AUTHOR]

This article aims to address the stochastic scaled consensus issue in almost surely and mean square sense of stochastic multiagent systems (SMASs) with compound noises in a Markovian switching setting. At first, based on stochastic approximation technique and nearest‐neighbor interaction rules, the stochastic scaled consensus controller is built for SMASs in presence of multiplicative and additive noise by designing a time‐varying gain. Meanwhile, some consensus criterions of SMASs are addressed if the union of the graph and time‐varying gain fulfill some mild requirements. Furthermore, the scaled consensus means that the agents' state variables tend to a prescribed proportion rather than the common value, so this behavior can be seen as non‐convergent behavior. The difference with most of excellent literatures is that the coexistence of noncooperative behavior and multiplicative noise generates that it is not easy to transform the multiplicative noise term into the form of an error equation, which means that the Lyapunov methods cannot be directly utilized in our article. To cope with this, we first demonstrate the boundedness for each agent's state, and hence the convergence can be achieved. Finally, in order to reveal the efficiency of our proposed protocol, the corresponding example is given in the simulation part. [ABSTRACT FROM AUTHOR]

This article studies the design problem of fault-tolerant and disturbance rejection control for leader-following multi-agent systems with polynomial form fault. First, a novel observer is designed to estimate polynomial form faults and external disturbances in the tracker. Second, a fault-tolerant control protocol is designed for each follower based on the obtained estimates; the designed distributed controller can effectively achieve both the goal of fault-tolerant control and the effect of disturbance rejection. Finally, a simulation result of a practical example is presented to verify the feasibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper is devoted to the research of adaptive command filter tracking control for a class of uncertain nonlinear systems. The coexistence of multiple coupling high‐order terms, uncertain external disturbances, and unknown time‐varying coefficients makes the studied system more general compared with the existing results. By skillfully combining adaptive technology, command filter control, and backstepping method, a new type of adaptive command filter tracking control algorithm is designed. This controller not only solves the problem of complex explosion but also introduces compensation signals to achieve a higher precision tracking effect. Ultimately, the validity of the control algorithm is verified by a numerical simulation and a practical application model simulation. [ABSTRACT FROM AUTHOR]