Dear editor,Solving linear matrix equations is a basic and important problem in many fields such as the computation of generalized inverses of matrices and(generalized) Sylvester equations. Also, the linear algebraic ...
Dear editor,Solving linear matrix equations is a basic and important problem in many fields such as the computation of generalized inverses of matrices and(generalized) Sylvester equations. Also, the linear algebraic equation is a fundamental problem, which is a special form of linear matrix equations.
Faults on distribution networks due to abnormal weather events can lead to disruption and can cause high socio-economic losses. In line with the rising frequency of such events, the paper proposes an algorithm for the...
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reconfigurable intelligent surfaces are devices that can significantly improve the quality of wireless communication by interacting with electromagnetic waves. RISs may in principle make the wireless environment contr...
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Electrical tree degradation is one of the main causes of insulation failure in high-frequency *** tree degradation is studied on pure epoxy resin(EP)and MgO/EP composites at frequencies ranging from 50 Hz to 130 *** r...
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Electrical tree degradation is one of the main causes of insulation failure in high-frequency *** tree degradation is studied on pure epoxy resin(EP)and MgO/EP composites at frequencies ranging from 50 Hz to 130 *** results show that the tree initiation voltage of EP decreases,while the growth rate and the expansion coefficient increase with ***,the bubble phenomenon at high frequencies in EP composites is *** with trap distribution character-istics within the material,the intrinsic mechanism of epoxy composites to inhibit the growth of the electrical tree at different frequencies is *** can be concluded that more deep traps and blocking effect are introduced by doping nano-MgO into EP bulks,which can improve the electrical tree resistance performance of EP composites in a wide frequency range.
In this paper,a comparative study for kernel-PCA based linear parameter varying(LPV)model approximation of sufficiently nonlinear and reasonably practical systems is carried *** matrix inequalities(LMIs)to be solved i...
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In this paper,a comparative study for kernel-PCA based linear parameter varying(LPV)model approximation of sufficiently nonlinear and reasonably practical systems is carried *** matrix inequalities(LMIs)to be solved in LPV controller design process increase exponentially with the increase in a number of scheduling *** kernel functions are used to obtain the approximate LPV model of highly coupled nonlinear *** error to norm ratio of original and approximate LPV models is introduced as a measure of accuracy of the approximate LPV *** examples conclude the effectiveness of kernel-PCA for LPV model approximation as with the identification of accurate approximate LPV model,computation complexity involved in LPV controller design is decreased exponentially.
For continuous-time switched linear autonomous systems,this work addresses the stabilization problem under safety-critical *** an origin-symmetric region that any state trajectory should be stayed,we seek to design a ...
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For continuous-time switched linear autonomous systems,this work addresses the stabilization problem under safety-critical *** an origin-symmetric region that any state trajectory should be stayed,we seek to design a switching law to achieve both stability and *** main approach is to characterize,both theoretically and algorithmically,the safe initial set that any initial state within the set could stay in the given safety region with a properly designed switching ***,we develop a design procedure that could approximate the safe initial set with the help of the pathwise state feedback switching strategy.A third-order example is presented to validate the effectiveness of the proposed methodology.
Anaerobic digestion is a wastewater treatment method that utilizes bacterial decomposition to convert organic matter into biogas, which provides both environmental and economic benefits. However, controlling biogas pr...
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This paper investigates the problem of traffic signal control in large-scale road networks. A deep reinforcement learning model based on graph meta-learning using local subgraphs is proposed to control the traffic sig...
This paper investigates the problem of traffic signal control in large-scale road networks. A deep reinforcement learning model based on graph meta-learning using local subgraphs is proposed to control the traffic signal. The entire traffic network is represented as a graph by defining traffic lights as nodes and treating connections between intersections as edges. A graph neural network is used to enhance cooperation and communications between agents since information about neighbors is aggregated. To overcome the challenges in large-scale road networks, the proposed model employs a graph neural network on local subgraphs to reduce the difficulty of training in large-scale road networks. The model trained in small-scale traffic networks is transferred to a large-scale traffic network. Agent knowledge acquired from local subgraphs during the training of a small-scale road network confers advantages to the training of large-scale road networks under the resemblance between the structures of local subgraphs in small-and large-scale road networks. Furthermore, meta-learning is used to facilitate the model's rapid adaptability to unseen large-scale road networks. The advantage of the double Q-learning network is taken to reduce overestimation. In experiments, real-world road networks and synthetic road networks comprising more than 1000 intersections are given to evaluate the effectiveness of the proposed model.
Cyber-physical systems(CPSs)have emerged as an essential area of research in the last decade,providing a new paradigm for the integration of computational and physical units in modern control *** state estimation(RSE)...
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Cyber-physical systems(CPSs)have emerged as an essential area of research in the last decade,providing a new paradigm for the integration of computational and physical units in modern control *** state estimation(RSE)is an indispensable functional module of ***,it has been demonstrated that malicious agents can manipulate data packets transmitted through unreliable channels of RSE,leading to severe estimation performance *** paper aims to present an overview of recent advances in cyber-attacks and defensive countermeasures,with a specific focus on integrity attacks against ***,two representative frameworks for the synthesis of optimal deception attacks with various performance metrics and stealthiness constraints are discussed,which provide a deeper insight into the vulnerabilities of ***,a detailed review of typical attack detection and resilient estimation algorithms is included,illustrating the latest defensive measures safeguarding RSE from ***,some prevalent attacks impairing the confidentiality and data availability of RSE are examined from both attackers'and defenders'***,several challenges and open problems are presented to inspire further exploration and future research in this field.
Definition of weak Pareto improvement is given for noncooperative systems with vector-valued payoff functions. The region where a system trajectory is Pareto improving is characerized. Some necessary and sufficient co...
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