This paper is concerned with the dissipativity analysis of singular systems with time-varying delays. Firstly, an improved augmented Lyapunov-Krasovsii functional(ALKF) is constructed based on the state decomposition ...
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This paper is concerned with the dissipativity analysis of singular systems with time-varying delays. Firstly, an improved augmented Lyapunov-Krasovsii functional(ALKF) is constructed based on the state decomposition method. Then, the derivative of the ALKF is estimated by applying the auxiliary function integral inequality and the extended reciprocally convex inequality. As a result, an improved dissipativity criterion with less conservativeness is established. Finally, numerical examples are given to show the superiority of the proposed method.
In this paper, the master-slave synchronization issue of chaotic Lur’ e systems with time-varying-delay feedback control is investigated. Firstly, the synchronization problem of chaotic system is transformed into the...
In this paper, the master-slave synchronization issue of chaotic Lur’ e systems with time-varying-delay feedback control is investigated. Firstly, the synchronization problem of chaotic system is transformed into the stability problem of chaotic synchronization error system, which is studied based on Lyapunov-Krasovskii functional (LKF) method. Secondly, a novel augmented LKF with more cross terms that related to time-varying delay is proposed. Based on the application of the relaxation integral inequality and the reciprocally convex matrix inequality, an improved synchronization criterion is derived by using the cubic function negative-determination lemma. Finally, a numerical simulation example demonstrates the effectiveness and advantages of the proposed methods.
In drilling processes, non-stationary phases corresponding to shifts between operating conditions and changes in downhole formations typically lead to false alarms. Extracting these frequent event patterns is critical...
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In drilling processes, non-stationary phases corresponding to shifts between operating conditions and changes in downhole formations typically lead to false alarms. Extracting these frequent event patterns is critical to build drilling process monitoring and fault diagnosis models. This study aims to extract the frequent event patterns associated with non-stationary phases in drilling time series. In this way, diversified information related to signal changes under normal conditions can be obtained, which is beneficial for suppressing false alarms and improving fault detection performance. The main contributions of this study are twofold: 1) a non-stationary phase detection method is proposed to extract drilling frequent event patterns based on t -distributed stochastic neighbor embedding and relative unconstrained least-squares importance fitting; 2) an event sequence generation method is proposed to express drilling frequent event patterns with a group of symbols. The effectiveness of the proposed method is demonstrated by data from a real drilling project.
With the continuous deepening of international anti-terrorism movement,the anti-terrorism has entered a new stage,and it is facing new *** of the new challenges is to extract useful and valuable information from massi...
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ISBN:
(数字)9781728158556
ISBN:
(纸本)9781728158563
With the continuous deepening of international anti-terrorism movement,the anti-terrorism has entered a new stage,and it is facing new *** of the new challenges is to extract useful and valuable information from massive data *** anti-terrorism system model based on local shallow information is imperfect,which is not conducive to obtaining accurate prediction *** shortcomings of existing research are the lack of comprehensive analysis and deeper mining of *** order to improve the efficiency and accuracy of the present anti-terrorism system,we propose an effective method for risk assessment and prediction based on machine learning by using Global Terrorism Database(GTD).There are four basic steps:first,we reduce the data dimension through correlation calculation and Singular Value Decomposition(SVD),then,the function is established to rank the harmfulness of terrorist attacks;second,the cascaded network with attention mechanism is used to predict suspects;third,k-means is used to cluster the regions of terrorist attacks,and then we establish a generalized linear regression model to predict the situation of terrorist *** verify the feasibility of the model by comparing with the real *** experimental results show that the proposed method can analyze and predict the information related to terrorist attacks comprehensively and accurately.
This paper presents an adaptive equivalent-input-disturbance(AEID)approach that contains a new adjustable gain to improve disturbance-rejection performance.A linear matrix inequality is derived to design the parameter...
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This paper presents an adaptive equivalent-input-disturbance(AEID)approach that contains a new adjustable gain to improve disturbance-rejection performance.A linear matrix inequality is derived to design the parameters of a control *** adaptive law for the adjustable gain is presented based on the combination of the root locus method and Lyapunov stability theory to guarantee the stability of the AEID-based *** adjustable gain is limited in an allowable range and the information for adjusting is obtained from the state of the *** results show that the method is effective and robust.A comparison with the conventional EID approach demonstrates the validity and superiority of the method.
Graph Structure Learning (GSL) has recently garnered considerable attention due to its ability to optimize both the parameters of Graph Neural Networks (GNNs) and the computation graph structure simultaneously. Despit...
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Delegated-Proof-of-Stake (DPoS) blockchains, such as EOSIO, Steem and TRON, are governed by a committee of block producers elected via a coin-based voting system. We recently witnessed the first de facto blockchain ta...
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Autonomous tracking control is one of the fundamental challenges in the field of robotic autonomous navigation,especially for future intelligent *** this paper,an improved pure pursuit control method is proposed for t...
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Autonomous tracking control is one of the fundamental challenges in the field of robotic autonomous navigation,especially for future intelligent *** this paper,an improved pure pursuit control method is proposed for the path tracking control problem of a four-wheel independent steering *** on the analysis of the four-wheel independent steering model,the kinematic model and the steering geometry model of the robot are *** the path tracking control is realized by considering the correlation between the look-ahead distance and the velocity,as well as the lateral error between the robot and the reference *** experimental results demonstrate that the improved pure pursuit control method has the advantages of small steady-state error,fast response and strong robustness,which can effectively improve the accuracy of path tracking.
In this paper, the outlier-resistant distributed filtering problem based on amplify-and-forward relays is studied for discrete time-varying nonlinear multi-rate systems with multiple measurement delays over sensor net...
In this paper, the outlier-resistant distributed filtering problem based on amplify-and-forward relays is studied for discrete time-varying nonlinear multi-rate systems with multiple measurement delays over sensor networks, where the augmenting method is utilized to transform the multi-rate system into a single rate system. An amplify-and-forward (AF) relay is set between the sensor and the filter to extend the transmission distance of the signal and ensure the communication transmission quality. The outlier-resistant distributed filter is constructed by introducing a saturation function to limit the innovations, then the upper bound on the filtering error covariance is obtained and the filter gain is designed to minimize such obtained upper bound. Finally, a numerical example is used to show the effectiveness of the outlier-resistant distributed filtering algorithm based on AF relays.
The distributed sensing, decision-making, and cooperative control of multi-agent systems has been thoroughly investigated in the fields such as sensor networks, social networks, distributed computing, and robotics in ...
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