In order to avoid the linear inversion method falling into local minima and slow convergence speed of the global optimization inversion method, the article proposed the simplex-simulated annealing algorithm for transi...
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In order to avoid the linear inversion method falling into local minima and slow convergence speed of the global optimization inversion method, the article proposed the simplex-simulated annealing algorithm for transient electromagnetic inversion research which combines advantages of the simplex method and the simulated annealing algorithm. The simplex method is used to obtain local minimum value which is relatively close to the actual value, then the simulated annealing algorithm is used to obtain the global optimal solution which can better reflect structural characteristics of the real stratigraphic *** the comparison of the noise inversion results and noise free inversion results about K-type, H-type, KH-type and HKH-type stratigraphic models, it can be proved that the simplex-simulated annealing algorithm can suppress some noise. The comparison of the simulated annealing method and the simplex-simulated annealing algorithm shows that the simplex-simulated annealing algorithm has the characteristics of global searching ability and fast convergence speed.
This paper focuses on an accelerating method for partitioning the loops in the structure of the adaptive dynamic programming（ADP）. ADP contains critic-actor structure which involves the iterations of the value funct...
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This paper focuses on an accelerating method for partitioning the loops in the structure of the adaptive dynamic programming（ADP）. ADP contains critic-actor structure which involves the iterations of the value function. When the system needs to be stable, the value function generally needs to iterate thousands of times, the high computation burden which hinders the iterations will be generated. In order to reduce the computation burden, we introduce a hyperparallelepiped based loop partitioning（H-LP） method which splits the iterations of the value function and reduces the communication traffic calculated by the data footprint. The experiment results show that the computation performance will be enhanced when the H-LP method is introduced. The proposed method has an important practical significance.
This paper presents a position control strategy based on the iterative method for a planar *** control objective of the system is to move the end-point from any initial equilibrium point to a target equilibrium *** pr...
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This paper presents a position control strategy based on the iterative method for a planar *** control objective of the system is to move the end-point from any initial equilibrium point to a target equilibrium *** presented method is based on the iterative steering,where a converging control law is applied *** order to compute such a control law,the dynamic equations of the system are transformed via partial feedback linearization and nilpotent ***,the simulation results demonstrate that the position control objective is realized by using this control strategy.
This paper suggests a novel technique for the tool parameter measurement based on machine vision. Tool images are captured by using a machine vision system and the outer contour image of the cutter is obtained by usin...
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This paper suggests a novel technique for the tool parameter measurement based on machine vision. Tool images are captured by using a machine vision system and the outer contour image of the cutter is obtained by using the machine vision technology. The HALCON image processing library is used as the development platform to build the tool parameters test system. Several algorithms including image segmentation, edge extraction and fitting ellipse determination is used for image processing. The tool parameters such as external diameter and contour angle of tool edge can be obtained after rebuilding the contour of tool edge. The proposed scheme is shown to be reliable and effective for the automated tool parameter measurement.
This paper investigates the problem of the strictly(Q,S,R)-γ-dissipativity analysis for Markovian jump neural networks with a time-varying *** employing an appropriate Lyapunov-Krasovskii functional and using the ext...
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This paper investigates the problem of the strictly(Q,S,R)-γ-dissipativity analysis for Markovian jump neural networks with a time-varying *** employing an appropriate Lyapunov-Krasovskii functional and using the extended relaxed integral inequality to estimate its derivative,a delay-dependent and mode-dependent condition that guarantee the considered Markovian jump neural networks strictly(Q,S,R)-γ-dissipative is ***,a numerical example is provided to illustrate the effectiveness of the proposed method.
Facial expression recognition(FER) plays an important role in human-machine interaction. An assistant robot having a close interaction with human being should be able to recognize human facial expression. FER is a non...
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Facial expression recognition(FER) plays an important role in human-machine interaction. An assistant robot having a close interaction with human being should be able to recognize human facial expression. FER is a non-trivial problem because each individual has his own way to reveal his emotion and the facial expressions of two different persons may not be totally identical. Hence,facial expression recognition is still a challenging problem in computer vision. In this work, we propose a simple solution for facial expression recognition that uses a combination of Convolutional Neural Network and specific image pre-processing *** experiments employed to evaluate our technique were carried out using two largely used public databases(CK+, JAFFE).A study of the impact of each image pre-processing operation in the accuracy rate is presented. The proposed method: achieves competitive results when compared with other facial expression recognition methods-97.85% of accuracy in the CK+ database-it is fast to train,and it allows for real time facial expression recognition with standard computers.
During the drilling process, accurate prediction of drilling efficiency and safety plays a key role in timely adjustment of drilling process state. In general, surface parameters rate of penetration（ROP） and mud pit...
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During the drilling process, accurate prediction of drilling efficiency and safety plays a key role in timely adjustment of drilling process state. In general, surface parameters rate of penetration（ROP） and mud pit volume（MPV） are often used as important parameters to judge drilling safety and efficiency due to the bad bottom hole environment and unreliable detection devices. However, most drilling systems are underground, the structure is complex and exists many disturbances, so the state of drilling process is difficult to accurately predict. In this paper, an online support vector regression（OSVR） model is proposed to predict the ROP and MPV. First, the parameters of the model are determined by simple drilling process analysis. Then, the fast fourier transform filtering method is used to filter the high frequency disturbances of the data. Finally, the prediction model is established by support vector regression（SVR） method and the model is continuously updated by the model update method. The simulation results of industrial data show that the proposed model has a good prediction effect.
Cyber-physical System(CPS) have a high requirement on real-time property, and it is difficult to improve the sampling efficiency base on traditional sampling theory. In this paper, the compression sensing(CS) theory i...
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Cyber-physical System(CPS) have a high requirement on real-time property, and it is difficult to improve the sampling efficiency base on traditional sampling theory. In this paper, the compression sensing(CS) theory is applied to the sampling compression process of CPS system. The CS theory was used to the sampling compression method of CPS system. The Bernoulli circulant matrix, which is easy to be realized and stored, and its construction algorithm were designed to simplify the realization of CS theory in CPS. It is concluded that for random data set, the compression ratio increases from 14.06 % to 42.18 % and the reconstruction error decreases from 27.65 to 1.28 with increasing repetition times. Note that the sampling time are around tens of microseconds and the reconstruction time are around several milliseconds, which indicates a high real-time performance for CPS. In addition, for image data set, the compression ratios are about 42.90 % which indicates a high compression ratio and huge storage resources saving. More importantly, the sampling time and reconstruction time are only several microseconds and several seconds respectively, which indicates a high real-time performance for CPS.
As slide steering technology has lower maintenance costs, it is widely used in geological drilling industry. In order to adjust the hole trajectory, this technology changes the drilling direction by controlling tool f...
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As slide steering technology has lower maintenance costs, it is widely used in geological drilling industry. In order to adjust the hole trajectory, this technology changes the drilling direction by controlling tool face angle of downhole power drill tool. However, due to the existence of the untwist angle, it is difficult to precisely control the angle, which will directly affect the quality of hole trajectory. So untwist angle prediction is the prerequisite of hole trajectory control. This paper introduces a common method for calculating untwist angle for generating the training set. And then factors that influence untwist angle will be analyzed. Meanwhile, based on the analysis and calculation results, support vector regression is introduced in the prediction algorithm to provide a new way for untwist angle prediction.
A demand analysis method based on TAKAGI-SUGENO（T-S） fuzzy model for drinking service is proposed to provide corresponding services according to users’ emotions and intentions in human-robot interaction,in which T-...
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A demand analysis method based on TAKAGI-SUGENO（T-S） fuzzy model for drinking service is proposed to provide corresponding services according to users’ emotions and intentions in human-robot interaction,in which T-S fuzzy model is used to establish the relationship among human intention and human ***,the transformation of input and output is ***,fuzzy rules are formulated,and then fuzzy inference is applied to get user’s demand corresponding to emotion and *** proposal considers peoples fuzziness in inferring humans intention,which could help the robots to provide satisfied drinking service to *** validate the proposal,drinking service experiments are performed in a laboratory scenario using a humans-robots interaction system,from which the experimental results demonstrate the feasibility of the proposal.
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