A novel edge detection method based on anisotropic mathematical morphology and scale multiplication in nonsubsampled contourlet transform (NSCT) domain is proposed to obtain a superior and robust performance under hea...
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With the widespread use of mobile devices, the location-based service (LBS) applications become increasingly popular, which introduces the new security challenge to protect user's location privacy. On one hand, a ...
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This paper designs a mixed H/Hmodel predictive algorithm for systems with energy-bounded *** formulation of H/Hperformance in previous work is improved by introducing a slack ***,we decouple the formulation of H/Hperf...
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ISBN:
(纸本)9781479900305
This paper designs a mixed H/Hmodel predictive algorithm for systems with energy-bounded *** formulation of H/Hperformance in previous work is improved by introducing a slack ***,we decouple the formulation of H/Hperformance from the formulation of input and state constraints by dilated LMI *** two aspects are combined to develop a less conservative control *** feasibility of the algorithm is able to be proved and stability of the controlled system is *** example shows the effectiveness of the proposed algorithm.
To track the wide range of operating points of fast time-varying processes, a novel multiple model off-line predictive control algorithm is presented. The proposed method is a combination of multiple model strategy an...
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ISBN:
(纸本)9781467355339
To track the wide range of operating points of fast time-varying processes, a novel multiple model off-line predictive control algorithm is presented. The proposed method is a combination of multiple model strategy and predictive control. Firstly, we locally describe the original nonlinear system around an operating point employing linear time varying (LTV) model. Then the offline model predictive control (OMPC) algorithm is adopted to design local controller for LTV model, whose low computation burden makes it be able to control the fast time-varying process. To track the wide range of operating point, the multiple-model strategy is exploited. By estimating the stable region of local OMPC and selecting appropriate middle operating points, the stable switch between controllers can be guaranteed. Finally, a numerical simulation is given to illustrate the implementation and effectiveness of the proposed method.
Improving the computational efficiency for model predictive control (MPC) becomes the focus of recent researches. This paper proposes a fast algorithm to solve the quadratic programming (QP) problem of MPC for systems...
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ISBN:
(纸本)9781467355339
Improving the computational efficiency for model predictive control (MPC) becomes the focus of recent researches. This paper proposes a fast algorithm to solve the quadratic programming (QP) problem of MPC for systems with only input constraints. This algorithm improves the efficiency of the fast gradient approach. Inspired by the multiplexed way, this algorithm searches a better solution of QP problem along the direction of one input channel in every iteration. Meanwhile, in order to further reduce the online computational complexity, the proposed algorithm applies the aggregation strategy to each input channel. Due to the aggregation strategy and the determined optimization direction, the proposed algorithm reduces the number of vector multiplications of each iteration, i.e. with less online computational complexity than previous works. Applying the proposed algorithm, simulations for a system with 3 inputs show that computational efficiency of this algorithm can reach a level of tens of microseconds in Matlab environment.
Many researches on the prediction of the penetration rate of the tunneling boring machine (TBM) have been carried out. The prediction of the penetration rate will contribute to reduce the danger of TBM construction, d...
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ISBN:
(纸本)9781467355339
Many researches on the prediction of the penetration rate of the tunneling boring machine (TBM) have been carried out. The prediction of the penetration rate will contribute to reduce the danger of TBM construction, decrease the cost and provide the support for the construction planning. Most methods for predicting penetration rate rely on the fixed equation relationship between the input parameters and output parameters. In this paper, we build up a dynamic model. We mainly make use of the partial least squares regression algorithm (PLS) and the structure of the fuzzy-neuron network (FNN) to build up the model. All the data should be normalized. We randomly select 120 groups of the data from TBM construction as the training data and 33 groups of data as the testing data. The training and testing results are analyzed by the mean square error and the correlation coefficient. At the same time, we compare the prediction of the PLS-FNN model with the prediction of the FNN model. The simulation result shows that the PLS-FNN model has the good performance for the prediction.
With the quick development of the semantic web technology, RDF data explosion has become a challenging problem. Since RDF data are always from different resources, which may have overlap with each other, they could ha...
With the quick development of the semantic web technology, RDF data explosion has become a challenging problem. Since RDF data are always from different resources, which may have overlap with each other, they could have duplicates. These duplicates may cause ambiguity and even error in reasoning. However, attentions are seldom paid to this problem. In this paper, we study the problem and give a solution, named K-radius sub graph comparison (KSC). The proposed method is based on RDF-Hierarchical Graph Model. KSC combines similar and comparison of 'context' to detect duplicate in RDF data. Experiments on publication datasets show that the proposed method is efficient in duplicate detection of RDF data. And KSC is simpler and less time-costs than other methods of graph comparison.
A saturation allowed scheduled anti-windup design method is proposed in this paper for the linear systems subject to input saturation. We introduced the scheduled controller design method into the anti-windup scheme, ...
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A saturation allowed scheduled anti-windup design method is proposed in this paper for the linear systems subject to input saturation. We introduced the scheduled controller design method into the anti-windup scheme, in which a family of controllers are designed. These controllers are activated depending on the response of the system, rather than only considering the worst noise case off-line. Also, the delayed activation scheme is introduced into the scheduled antiwindup mechanism, i.e., the physical actuator is activated when it really need to, and then the most aggressive controller is activated. In this proposed scheme, since the saturation is allowed and no hard constraint is needed to imposed on the controller input, we can makes fuller utilization of the available actuator capacity. The proposed anti-windup scheme provides the system stability and guaranteed peak-to-peak gain. The control strategy is carried out under the scheme of state feedback and the main results are presented in linear matrix inequality forms. The advantage of the proposed saturated allowed scheduling anti-windup scheme against the traditional saturation avoid method is illustrated through a numerical example.
Many systems use RDF to describe information resources and semantic associations between resources. RDF data plays a very important role in advanced information retrieval. Due to diversity and imprecise of resources, ...
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Many systems use RDF to describe information resources and semantic associations between resources. RDF data plays a very important role in advanced information retrieval. Due to diversity and imprecise of resources, duplicates exist in RDF data. The query and retrieval of RDF data are studied by many researchers. However, researchers seldom study RDF data cleansing. In this paper, we focus on RDF data cleansing. According to the features of RDF data, we propose a new approach. This approach combines similarity and connections among resources. First, we introduce an intermediate model, named RDF-Bipartite Graph model, to represent the RDF data. This model improves from Bipartite Statement-Value Graphs model. Then on the proposed model, we design a Subgraph-Extend method, to find the path connecting two nodes. This method detects the minimum subgraph containing two nodes for connect-path finding. It avoids the connect-weight setting in traditional method. Experiments on publication datasets show that the proposed method is efficient in duplicate detection of RDF data, and has high performance and accuracy.
This paper proposes two hybrid prediction models using for predicting the displacement of landslide, Genetic Algorithm-Radial Basis Function Neural Network (GA-RBFN) and Genetic Algorithm- Back Propagation Neural Netw...
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This paper proposes two hybrid prediction models using for predicting the displacement of landslide, Genetic Algorithm-Radial Basis Function Neural Network (GA-RBFN) and Genetic Algorithm- Back Propagation Neural Network (GA-BPNN). A case study of Yuhuangge landslide in the Three Gorges reservoir in China is used to illustrate the capability and merit of our schemes. In addition, the result shows that GP-BPNN get better accuracy than GA-RBFN in the same measurements.
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