This paper revisits the problem of bumpless transfer control(BTC) for discrete-time nondeterministic switched linear systems. The general case of asynchronous switching is considered for the first time in the field of...
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This paper revisits the problem of bumpless transfer control(BTC) for discrete-time nondeterministic switched linear systems. The general case of asynchronous switching is considered for the first time in the field of BTC for switched systems. A new approach called interpolated bumpless transfer control(IBTC) is proposed, where the bumpless transfer controllers are formulated with the combination of the two adjacent modedependent controller gains, and are interpolated for finite steps once the switching is detected. In contrast with the existing approaches, IBTC does not necessarily run through the full interval of subsystems, as well as possesses the time-varying controller gains(with more flexibility and less conservatism) achieved from a control synthesis allowing for the stability and other performance of the whole switched system. Sufficient conditions ensuring stability and H_(∞) performance of the underlying system by IBTC are developed, and numerical examples verify the theoretical findings.
High penetration of renewable energy sources(RESs)induces sharply-fluctuating feeder power,leading to volt-age deviation in active distribution *** prevent voltage violations,multi-terminal soft open points(M-sOPs)hav...
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High penetration of renewable energy sources(RESs)induces sharply-fluctuating feeder power,leading to volt-age deviation in active distribution *** prevent voltage violations,multi-terminal soft open points(M-sOPs)have been integrated into the distribution systems to enhance voltage con-trol ***,the M-SOP voltage control recalculated in real time cannot adapt to the rapid fluctuations of photovol-taic(PV)power,fundamentally limiting the voltage controllabili-ty of *** address this issue,a full-model-free adaptive graph deep deterministic policy gradient(FAG-DDPG)model is proposed for M-SOP voltage ***,the attention-based adaptive graph convolutional network(AGCN)is lever-aged to extract the complex correlation features of nodal infor-mation to improve the policy learning ***,the AGCN-based surrogate model is trained to replace the power flow cal-culation to achieve model-free ***,the deep deterministic policy gradient(DDPG)algorithm allows FAG-DDPG model to learn an optimal control strategy of M-SOP by continuous interactions with the AGCN-based surrogate *** tests have been performed on modified IEEE 33-node,123-node,and a real 76-node distribution systems,which demonstrate the effectiveness and generalization ability of the proposed FAG-DDPGmodel.
Deep learning for defect detection has become a critical imperative in contemporary electronics manufacturing. We propose an inpainting-based anomaly detection system to identify defects without labeled defects. An im...
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The significance of precise energy usage forecasts has been highlighted by the increasing need for sustainability and energy efficiency across a range of *** order to improve the precision and openness of energy consu...
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The significance of precise energy usage forecasts has been highlighted by the increasing need for sustainability and energy efficiency across a range of *** order to improve the precision and openness of energy consumption projections,this study investigates the combination of machine learning(ML)methods with Shapley additive explanations(SHAP)*** study evaluates three distinct models:the first is a Linear Regressor,the second is a Support Vector Regressor,and the third is a Decision Tree Regressor,which was scaled up to a Random Forest Regressor/Additions made were the third one which was Regressor which was extended to a Random Forest *** models were deployed with the use of Shareable,Plot-interpretable Explainable Artificial Intelligence techniques,to improve trust in the *** findings suggest that our developedmodels are superior to the conventional models discussed in prior studies;with high Mean Absolute Error(MAE)and Root Mean Squared Error(RMSE)values being close to *** detail,the Random Forest Regressor shows the MAE of 0.001 for predicting the house prices whereas the SVR gives 0.21 of MAE and 0.24 *** outcomes reflect the possibility of optimizing the use of the promoted advanced AI models with the use of Explainable AI for more accurate prediction of energy consumption and at the same time for the models’decision-making procedures’*** addition to increasing prediction accuracy,this strategy gives stakeholders comprehensible insights,which facilitates improved decision-making and fosters confidence in AI-powered energy *** outcomes show how well ML and SHAP work together to enhance prediction performance and guarantee transparency in energy usage projections.
optimization algorithms play a crucial role in solving complex problems in various domains. Single-objective optimization algorithms aim to discover the most optimal solution for a particular objective function, commo...
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The United Nations approved the Sustainable Development Goals in 2015 to help countries around the world work toward a more sustainable future. The SDG7 goal is to ensure that everyone has access to cheap, dependable,...
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Presence of heterogenous huge data leads towards the ‘big data’ era. Recently, tweeter usage increased with unprecedented rate. Presence of social media like tweeter has broken the boundaries and touches the mountai...
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The sensor data points that exhibit unexpected behaviour that considerably deviates from the norm are considered anomalies in the time-series sensor data. We can model univariate time series data using a number of tra...
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Renal irregularities are serious medicinal condition that is becoming more common and killing more people each year. In its early stages, renal irregularities are curable, but it can progress irreversibly and result i...
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A combination of their ability to adapt to a broad spectrum of applications and their ability for self-organization, mobile ad hoc networks, or MANETs, have attracted much interest. However, the fundamental characteri...
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