Wind energy has emerged as an increasingly viable renewable energy source, driven by rising fossil fuel costs, energy security concerns, and environmental considerations. In 2022, wind energy production grew by 9% com...
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We study the geometric knapsack problem in which we are given a set of d-dimensional objects (each with associated profits) and the goal is to find the maximum profit subset that can be packed non-overlappingly into a...
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In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utili...
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In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.
The purpose of this research paper is to explore different approaches to maximize power point tracking (MPPT) in photovoltaic (PV) systems. In this work, we evaluate and compare incremental conductance (InC) and fuzzy...
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As more and more devices in Cyber-Physical Systems(CPS)are connected to the Internet,physical components such as programmable logic controller(PLC),sensors,and actuators are facing greater risks of network attacks,and...
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As more and more devices in Cyber-Physical Systems(CPS)are connected to the Internet,physical components such as programmable logic controller(PLC),sensors,and actuators are facing greater risks of network attacks,and fast and accurate attack detection techniques are *** key problem in distinguishing between normal and abnormal sequences is to model sequential changes in a large and diverse field of time *** address this issue,we propose an anomaly detection method based on distributed deep *** method uses a bilateral filtering algorithm for sequential sequences to remove noise in the time series,which can maintain the edge of discrete *** use a distributed linear deep learning model to establish a sequential prediction model and adjust the threshold for anomaly detection based on the prediction error of the validation *** method can not only detect abnormal attacks but also locate the sensors that cause *** conducted experiments on the Secure Water Treatment(SWAT)and Water Distribution(WADI)public *** experimental results show that our method is superior to the baseline method in identifying the types of attacks and detecting efficiency.
Dear editor, Vehicle control is one of the key steps of intelligent driving [1]. Algorithms based on receding horizon optimization(RHO) can predict future trajectories and handle multiobjective constraint conditions; ...
Dear editor, Vehicle control is one of the key steps of intelligent driving [1]. Algorithms based on receding horizon optimization(RHO) can predict future trajectories and handle multiobjective constraint conditions; therefore, RHO-based methods have attracted considerable attention in the field of vehicle control. Although existing methods use RHO to design controllers, they do not simultaneously meet the multiobjective optimal control performance requirements on tracking, fuel economy, and ride comfort.
Cloud computing is one of the most attractive and cost-saving models,which provides online services to *** computing allows the user to access data directly from any *** nowadays,cloud security is one of the biggest i...
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Cloud computing is one of the most attractive and cost-saving models,which provides online services to *** computing allows the user to access data directly from any *** nowadays,cloud security is one of the biggest issues that *** types of malware are wreaking havoc on the *** on the cloud server are happening from both internal and external *** paper has developed a tool to prevent the cloud server from spamming *** an attacker attempts to use different spamming techniques on a cloud server,the attacker will be intercepted through two effective techniques:Cloudflare and K-nearest neighbors(KNN)*** will block those IP addresses that the attacker will use and prevent spamming ***,the KNN classifiers will determine which area the spammer belongs *** the end of the article,various prevention techniques for securing cloud servers will be discussed,a comparison will be made with different papers,a conclusion will be drawn based on different results.
With the continuous change of artificial intelligence technology, the study of path planning for mobile robots is no longer limited to traditional path algorithms. Reinforcement learning, as an artificial intelligence...
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CT image reconstruction is a challenging inverse problem of estimating image intensities from sensor signals. While deep learning-based methods hold promise, they are typically classified into fully-supervised, self-s...
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Wind energy has emerged as an increasingly viable renewable energy source, driven by rising fossil fuel costs, energy security concerns, and environmental considerations. In 2022, wind energy production grew by 9% com...
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ISBN:
(数字)9798350349351
ISBN:
(纸本)9798350349368
Wind energy has emerged as an increasingly viable renewable energy source, driven by rising fossil fuel costs, energy security concerns, and environmental considerations. In 2022, wind energy production grew by 9% compared to 2021, maintaining an annual rate exceeding 12% since 2012. This study focuses on the application of Field Oriented Control (FOC), a prevalent control strategy in wind power generation systems, to a permanent magnet synchronous generator (PMSG) in a variable speed wind turbine configuration. The research methodology involved implementing FOC and conducting robustness analyses through PMSG parameter variations. The primary objectives were to maximize wind energy capture efficiency while ensuring sustained control performance. MATLAB/Simulink was employed to simulate and evaluate the various components of the wind turbine system (WTS), facilitating comprehensive analysis of the results.
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