Recently, multirobot systems(MRSs) have found extensive applications across various domains, including industrial manufacturing, collaborative formation of unmanned equipment, emergency disaster relief, and war scenar...
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Recently, multirobot systems(MRSs) have found extensive applications across various domains, including industrial manufacturing, collaborative formation of unmanned equipment, emergency disaster relief, and war scenarios [1]. These advancements are largely supported by the development of consistency control theory. However, traditional dynamicsfree models may cause instability in complex robotic systems. Lagrangian dynamics offers a better approach for modeling these systems, as it facilitates controller design and optimization analysis. Despite this, challenges persist with unknown parameters and nonlinear friction within the systems.
With the continuous progress of big data, Internet of Things, artificial intelligence and other technologies, we are living in an era of information explosion. A large amount of data is constantly recorded, and this d...
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Alumina-forming austenitic(AFA) steel, a promising candidate for use in high-temperature components of ultrasupercritical power plants, has high creep strengths and outstanding high-temperature corrosion resistance. T...
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Alumina-forming austenitic(AFA) steel, a promising candidate for use in high-temperature components of ultrasupercritical power plants, has high creep strengths and outstanding high-temperature corrosion resistance. The effects of microstructural evolution on the mechanical properties of Fe-20Ni-14Cr-3Al alumina-forming austenitic(3Al-AFA) steel with micro-cold deformation were investigated by multiple characterization methods, and the micro-cold deformation process was analyzed by conducting compression experiments. Tensile properties and hardness were also examined. The results show that the reduction of deformation has significant influences on the increase in the density of dislocation, the reduction of grain size, and the distribution of precipitates, which play an essential role in the enhancement of mechanical properties. As the reduction of deformation increases, the density of dislocations rises, the fragmentation of grains results in a reduction of grain size, and the distribution of precipitates at the grain boundaries gradually increases, which causes a rise in strength and a decrease in elongation. Since the elastic deformation range expands with an increase in deformation before the strain reaches 5 %of the CR0 sample in the compression test, the variation in the average grain aspect ratio between a reduction of 2% and 6 % is relatively small. It contributes more to hardness and strength when the grain aspect ratio is high.
This paper addresses the dynamic target tracking and circumnavigation problem for multiple Wheeled Mobile Robots (WMRs) while considering both kinematic and dynamic models, and proposes a fixed-time circumnavigation c...
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This paper addresses the dynamic target tracking and circumnavigation problem for multiple Wheeled Mobile Robots (WMRs) while considering both kinematic and dynamic models, and proposes a fixed-time circumnavigation controller. The control system consists of two parts: Firstly, it formulates an error model of relative velocity between the target and WMRs, transforming the cooperative circumnavigation problem into a tracking problem. A dynamic feedback linearization method is employed to generate suitable linear and angular velocity. Secondly, based on the dynamic model, the error vector is redefined to represent relative position and orientation between the trajectory generated by the kinematic controller and the WMRs. A torque control law is designed using backstepping and fixed-time stability theory to track this trajectory, ultimately achieving circumferential velocity, circumferential radius, and relative angular spacing tracking during circumnavigation control. Additionally, the integration of an adaptive term into the controller, aimed at estimating unknown parameters, facilitates the attainment of effective control performance even when confronted with parameter uncertainties. Furthermore, Lyapunov tools are utilized for fixed-time stability analysis. Finally, the efficacy of the designed controller is validated via numerical simulations. IEEE
Due to the probability characteristics of quantum mechanism, the combination of quantum mechanism and intelligent algorithm has received wide attention. Quantum dynamics theory uses the Schr?dinger equation as a quant...
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Due to the probability characteristics of quantum mechanism, the combination of quantum mechanism and intelligent algorithm has received wide attention. Quantum dynamics theory uses the Schr?dinger equation as a quantum dynamics equation. Through three approximation of the objective function, quantum dynamics framework(QDF) is obtained which describes basic iterative operations of optimization algorithms. Based on QDF, this paper proposes a potential barrier estimation(PBE) method which originates from quantum mechanism. With the proposed method, the particle can accept inferior solutions during the sampling process according to a probability which is subject to the quantum tunneling effect, to improve the global search capacity of optimization *** effectiveness of the proposed method in the ability of escaping local minima was thoroughly investigated through double well function(DWF), and experiments on two benchmark functions sets show that this method significantly improves the optimization performance of high dimensional complex functions. The PBE method is quantized and easily transplanted to other algorithms to achieve high performance in the future.
Industrial cyber-physical systems closely integrate physical processes with cyberspace, enabling real-time exchange of various information about system dynamics, sensor outputs, and control decisions. The connection b...
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Industrial cyber-physical systems closely integrate physical processes with cyberspace, enabling real-time exchange of various information about system dynamics, sensor outputs, and control decisions. The connection between cyberspace and physical processes results in the exposure of industrial production information to unprecedented security risks. It is imperative to develop suitable strategies to ensure cyber security while meeting basic performance *** the perspective of control engineering, this review presents the most up-to-date results for privacy-preserving filtering,control, and optimization in industrial cyber-physical systems. Fashionable privacy-preserving strategies and mainstream evaluation metrics are first presented in a systematic manner for performance evaluation and engineering *** discussion discloses the impact of typical filtering algorithms on filtering performance, specifically for privacy-preserving Kalman filtering. Then, the latest development of industrial control is systematically investigated from consensus control of multi-agent systems, platoon control of autonomous vehicles as well as hierarchical control of power systems. The focus thereafter is on the latest privacy-preserving optimization algorithms in the framework of consensus and their applications in distributed economic dispatch issues and energy management of networked power systems. In the end, several topics for potential future research are highlighted.
As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of *** connection between industrial control networks and the external internet is becoming increa...
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As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of *** connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security *** paper proposes a model for the industrial control *** includes a malware containment strategy that integrates intrusion detection,quarantine,and ***,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment *** addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction ***,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is *** otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control *** earlier the immunization of key nodes,the *** the time exceeds the threshold,immunizing key nodes is almost *** analysis provides a better way to contain the malware in the industrial control network.
As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention...
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As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.
In the past decade, thanks to the powerfulness of deep-learning techniques, we have witnessed a whole new era of automated code generation. To sort out developments, we have conducted a comprehensive review of solutio...
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In the past decade, thanks to the powerfulness of deep-learning techniques, we have witnessed a whole new era of automated code generation. To sort out developments, we have conducted a comprehensive review of solutions to deep learning-based code generation. In this survey, we generally formalize the pipeline and procedure of code generation and categorize existing solutions according to taxonomy from perspectives of architecture, model-agnostic enhancing strategy, metrics, and tasks. In addition, we outline the challenges faced by current dominant large models and list several plausible directions for future research. We hope that this survey may provide handy guidance to understanding, utilizing, and developing deep learning-based code-generation techniques for researchers and practitioners.
Recognition and detection of traffic signs in autonomous driving is a challenging task. With the advancement of deep learning technology., methods based on convolutional neural networks have made significant progress....
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