This paper investigates the linear quadratic Gaussian(LQG) control problem over a packet-dropping network connecting the local sensor and the remote controller. A linear predictive compensator is proposed for countera...
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ISBN:
(纸本)9781479947249
This paper investigates the linear quadratic Gaussian(LQG) control problem over a packet-dropping network connecting the local sensor and the remote controller. A linear predictive compensator is proposed for counteracting the stochastic packet loss. The control command executes to the plant is rst expressed as the random sequence which relies on the packet arrival sequence. The information set of the system is then divided into several subsets and corresponding prediction error covariances of each subset are also obtained. By this means, the quantitative relationship between the performance index of LQG control and the prediction steps is established. Numerical example shows that there exists nite steps of prediction for minimizing the performance index.
For some big cities where congestion occurs frequently,this paper proposes a novel predictive congestion control algorithm,focusing on imposing hard constraints on links for avoiding *** the urban traffic network is o...
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ISBN:
(纸本)9781538629185
For some big cities where congestion occurs frequently,this paper proposes a novel predictive congestion control algorithm,focusing on imposing hard constraints on links for avoiding *** the urban traffic network is often optimized with some micro-integrated global performance indexes,which equalize the effect of congestion and the emergency of congestion may be ***,for cities with heavy congestion,more attentions should be directly paid to congestion avoidance which may be particularly sensitive for urban traffic managers and individual *** use the universal standard of length of the queue to describe the congestion status of the *** simplifying the macroscopic urban traffic S model,we approximately get a linear relationship between signals and queue lengths such that we can predict the future congestion status of the *** on this,we transform the traditional optimization into formulating the urban traffic congestion control as a constraint satisfaction problem(CSP) where congestion avoidance conditions are imposed on the links and the problem can be characterized by finding the feasible solution for a group of linear *** the problem is non-feasible,we further develop a hierarchical strategy to guarantee the most important links without *** results show that the control approach significantly decreases the number of congested links compared to other controllers.
In recent years, more and more plug-in hybrid electric vehicles(PHEVs) have been put to use in smart grid. In this paper, we consider a dynamic aggregator-PHEV system, where the aggregator convinces the PHEVs to use...
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ISBN:
(纸本)9781479947249
In recent years, more and more plug-in hybrid electric vehicles(PHEVs) have been put to use in smart grid. In this paper, we consider a dynamic aggregator-PHEV system, where the aggregator convinces the PHEVs to use electricity rather than gas by setting an appropriate charging price dynamically. We propose a payoff-maximizing algorithm for the aggregator to decide not only the charging price but also the electricity amount purchased from real-time power market based on Lyapunov optimization. Furthermore, we transform the power purchase problem into the energy allocation problem among all the *** proposed algorithm operates in real time and does not require any prior knowledge of the statistical information of the system. Theoretically, we demonstrate the proposed algorithm can guarantee system stability and achieve a result that is away from the optimum by O(1/V), where V is a control parameter. The effectiveness and robustness of the algorithm is validated through simulation results.
This paper establishes the prediction model of low cycle fatigue damage of steam turbine rotor using the rich data from finite element analysis. In order to monitor the damage, a multiple regression analysis of input ...
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ISBN:
(纸本)9781479947249
This paper establishes the prediction model of low cycle fatigue damage of steam turbine rotor using the rich data from finite element analysis. In order to monitor the damage, a multiple regression analysis of input data/output data with high correlation is made via dynamic PLS. The variation of the process parameters is extracted and it restrains the multiple dependency of the several parameters in different time series. Finally, a simulation of rolling process of a domestic 300 MW turbine unit validates the effectiveness and accuracy of the prediction model based on dynamic PLS.
Prediction of the future traffic states of the overall city arterial networks provides the process of urban traffic evolution for researchers,which can serve as reference information for the city traffic ***,the compl...
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ISBN:
(纸本)9781509009107
Prediction of the future traffic states of the overall city arterial networks provides the process of urban traffic evolution for researchers,which can serve as reference information for the city traffic ***,the complexity and heterogeneity of urban traffic system and the big data challenge have proven to be substantial difficulties.A probabilistic tree modeling framework for estimating the overall traffic states is proposed in this ***,we extract several typical traffic states covering the overall ***,the state predicting algorithm based on dynamic Variable-order Markov Model and Genetic Algorithm is developed,where different date attributes were evaluated ***,the prediction model using probability tree with multiple prediction steps is *** results using traffic speed data in Shanghai demonstrate the high accuracy and efficiency of the proposed method.
The ability to reconstruct complex networks plays an important role in our understanding of how nodes interact with each other and how information ows coordinate node's dynamic behaviors. Many similarity-based met...
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ISBN:
(纸本)9781509009107
The ability to reconstruct complex networks plays an important role in our understanding of how nodes interact with each other and how information ows coordinate node's dynamic behaviors. Many similarity-based methods usually prefer steadystate data to time-series and perform poorly with the latter, such as pearson correlation and mutual information. Meanwhile,these similarity-based methods result in networks of non-directional structure. Moreover, various methods have been proposed based on linear dynamic models. One of the most representative methods is graphical granger causality. In this paper,we consider the problem of discovering network structure from time-series and introduce a novel method for reconstructing nonlinear causal interactions among nodes in complex networks, termed as grouped sparse nonlinear graphical granger causality, which is particularly t for directionality and nonlinearity of real network systems. The performance of our proposed method is evaluated on synthetic datasets and the benchmark datasets of Dream3 Challenge4. Both the result of them demonstrate that our proposed method outperforms other methods.
Directional sensors,such as cameras,are limited in their sensing angles,but are able to switch to different directions and cover the area of interest *** directional sensor networks,how to prolong the network lifetime...
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ISBN:
(纸本)9789881563842
Directional sensors,such as cameras,are limited in their sensing angles,but are able to switch to different directions and cover the area of interest *** directional sensor networks,how to prolong the network lifetime while satisfying certain coverage requirements is a fundamental problem since the sensors are powered by *** this paper,we propose scheduling schemes for directional sensor networks to maximize the network lifetime and satisfy the coverage requirements,which are designed to cover the point of interest as well as a specified ratio of *** the position of the point of interest may change time to time,dynamic coverage constraints are considered in this *** and distributed scheduling algorithms are developed,*** results show that both algorithms can prolong the network lifetime significantly by balancing the energy consumption of the whole network.
We propose an approach to improving the detection results of a generic offline trained detector on frames from a specific video. For two consecutive frames of a video with the object, deformable part model(DPM) dete...
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ISBN:
(纸本)9781467355339
We propose an approach to improving the detection results of a generic offline trained detector on frames from a specific video. For two consecutive frames of a video with the object, deformable part model(DPM) detection is perform to get the original detections. Then respectively obtain the image patches corresponding to the detected root box and part boxes. Thirdly, extract scale invariant feature transform features(SIFT) from those image patches and match the sift features by KD-Tree. Finally, get the SIFTPM detection result of from the matches between image patches of continuous frames. We focus on methods with high precision detection results since it is necessitated in real application. Extensive experiments with state-of-the-art detector demonstrate the efficacy of our approach..
In this paper,we study the consensus problem of multiple Euler-Lagrange systems subject to limited communication resources and parametric ***,an event-triggered communication scheme is proposed to achieve the leaderle...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
In this paper,we study the consensus problem of multiple Euler-Lagrange systems subject to limited communication resources and parametric ***,an event-triggered communication scheme is proposed to achieve the leaderless consensus *** the proposed event-triggered mechanism,the state of each subsystem is transmitted at event instants which are aperiodic and asynchronous with respect to other ***,we consider the time-delay effects in *** consensus analysis of the proposed scheme is based on the small-gain *** simulation results on a network of robot manipulators are given to illustrate the effectiveness of the proposed control scheme.
Based on saliency and grayscale morphological reconstruction, a new detection algorithm for infrared dim and small targets is proposed in this paper. The saliency of the original image to obtain the region of interest...
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ISBN:
(纸本)9781467374439
Based on saliency and grayscale morphological reconstruction, a new detection algorithm for infrared dim and small targets is proposed in this paper. The saliency of the original image to obtain the region of interest(ROI) is analyzed, then the spatial domain characteristic of dim and small targets is introduced into the marker image. Grayscale morphological reconstruction is based on the marker image and the mask image(the original image). Because saliency efficiently concentrates the gradient difference of the targets, detection probability is improved also with little false alarms. As the role of recognition, spatial domain characteristic of target reduces false alarm probability with the same detection probability, and background can be well estimated by grayscale morphological reconstruction, after subtraction, dim and small targets are detected. Experiments of real data prove the better detection performance, especially higher signal-to-noise ratio(SNR).
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