An iterative coordination control strategy based on multi-agent systems (MAS) is suggested to handle the problem of voltage fluctuation during peak load periods and peak solar generation times in complex LV distributi...
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With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair compar...
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With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.
In the operating rooms and the intensive care unit, it is crucial to manage the patient's hemodynamic status, which includes factors like cardiac output and mean arterial pressure. Anesthesiologists confront a dif...
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The leader-following asymptotic consensus problem for general discrete-time linear multi-agent systems over jointly con-nected switching networks was solved about a decade ***,the leader-following exponential consensu...
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The leader-following asymptotic consensus problem for general discrete-time linear multi-agent systems over jointly con-nected switching networks was solved about a decade ***,the leader-following exponential consensus was further established using the so-called Krasovskii-LaSalle theorem for a class of discrete-time linear switched *** this method involves some advanced concepts such as the weak zero-state detectability of some limiting *** this paper,we offer a simpler solution to the leader-following exponential consensus problem for general discrete-time linear multi-agent systems over jointly connected switching *** converting the solvability of the problem to the establishment of the exponential stability for a class of discrete-time linear switched systems,we first show that this class of linear switched systems is uniformly completely ***,we further conclude that the uniform complete observability for this class of linear switched systems implies the exponential stability for the same class of linear switched systems,thus leading to the solution of the leader-following exponential consensus ***,our approach also gives rise to an explicit characterization of the exponential convergence rate of the leader-following consensus problem.
Distributed Nash equilibrium seeking of aggregative games is investigated and a continuous-time algorithm is *** algorithm is designed by virtue of projected gradient play dynamics and aggregation tracking dynamics,an...
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Distributed Nash equilibrium seeking of aggregative games is investigated and a continuous-time algorithm is *** algorithm is designed by virtue of projected gradient play dynamics and aggregation tracking dynamics,and is applicable to games with constrained strategy sets and weight-balanced communication *** key feature of our method is that the proposed projected dynamics achieves exponential convergence,whereas such convergence results are only obtained for non-projected dynamics in existing works on distributed optimization and equilibrium *** examples illustrate the effectiveness of our methods.
Industrial controlsystems (ICSs) are becoming increasingly interconnected as the rapid convergence of information technology (IT) and operation technology (OT) networks, and meanwhile massive attack surfaces have bee...
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This letter is a brief summary of a series of IEEE TIV's decentralized and hybrid workshops (DHWs) on Federated Intelligence for Intelligent Vehicles. The discussed results are: 1) Different scales of large models...
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This letter is a brief summary of a series of IEEE TIV's decentralized and hybrid workshops (DHWs) on Federated Intelligence for Intelligent Vehicles. The discussed results are: 1) Different scales of large models (LMs) can be federated and deployed on IVs, and three types of federated collaboration between large and small models can be adopted for IVs. 2) Federated fine-tuning of LMs is beneficial for IVs data security. 3) The sustainability of IVs can be improved through optimizing existing models and continuous learning using federated intelligence. 4) LM-enhanced knowledge can make IVs smarter. IEEE
This paper shows that the torpedo-type Autonomous Underwater Vehicle (AUV) exhibits the non-minimum phase behavior in the depth control operation for a certain range of forward velocity. Contributions in this paper ar...
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This paper addresses the asymptotic control problem of uncertain multi-input and multi-output(MIMO)nonlinear *** considered MIMO systems contain unknown virtual control coefficients(UVCCs)and state *** Lyapunov functi...
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This paper addresses the asymptotic control problem of uncertain multi-input and multi-output(MIMO)nonlinear *** considered MIMO systems contain unknown virtual control coefficients(UVCCs)and state *** Lyapunov function by associating with the lower bounds of UVCCs is presented to counteract the adverse effect deriving from *** state constraints are ensured by utilising the barrier Lyapunov ***,the asymptotic tracking controller is recursively constructed by combining the backstepping technique with fuzzy logic *** remarkable character of the designed controller is that the asymptotic tracking performance can be achieved by introducing some smooth functions into adaptive backstepping *** contrast to the existing results,the conditions on the UVCCs are ***,the new control design is illustrated by a practical example.
Information and communication technologies enable the transformation of traditional energy systems into cyber-physical energy systems(CPESs),but such systems have also become popular targets of ***,available methods f...
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Information and communication technologies enable the transformation of traditional energy systems into cyber-physical energy systems(CPESs),but such systems have also become popular targets of ***,available methods for evaluating the impacts of cyberattacks suffer from limited resilience,efficacy,and practical *** mitigate their potentially disastrous consequences,this study suggests a two-stage,discrepancy-based optimization approach that considers both preparatory actions and response measures,integrating concepts from social *** proposed Kullback-Leibler divergence-based,distributionally robust optimization(KDR)method has a hierarchical,two-stage objective function that incorporates the operating costs of both system infrastructures(e.g.,energy resources,reserve capacity)and real-time response measures(e.g.,load shedding,demand-side management,electric vehicle charging station management).By incorporating social computing principles,the optimization framework can also capture the social behavior and interactions of energy consumers in response to *** preparatory stage entails day-ahead operational decisions,leveraging insights from social computing to model and predict the behaviors of individuals and communities affected by potential *** mitigation stage generates responses designed to contain the consequences of the attack by directing and optimizing energy use from the demand side,taking into account the social context and preferences of energy consumers,to ensure resilient,economically efficient CPES *** method can determine optimal schemes in both stages,accounting for the social dimensions of the *** original disaster mitigation model uses an abstract formulation to develop a risk-neutral model that characterizes cyberattacks through KDR,incorporating social computing techniques to enhance the understanding and response to cyber *** approach can mitigate the impacts more
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