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Chinese Automation Congress (CAC)

作者： Hui Luo Genping Wu Quan Yin Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781467371902

A large electrolytic capacitor is always used to make dc-link voltage stable in a single-phase to three-phase power converter. However, the large electrolytic capacitor occupies a large volume and has a short lifetime as to the home appliances. And additional PFC circuit is needed to correct the grid current. In order to settle these issues, a converter without electrolytic capacitor is studied in this paper. The q-axis current reference is modified for the high grid power factor operation. And the d-axis current reference is generated to achieve the flux-weakening control and to improve the waveform of the output currents and. Proportional-resonant controllers are adopted to obtain the better current performance. The simulation results verify the validity and feasibility of the proposed method.

关键词： Capacitors

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Laser and Force Sensors Based Human Motion Intent Estimation Algorithm for Walking-aid Robot

Laser and Force Sensors Based Human Motion Intent Estimation...

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IEEE International Conference on Cyber Technology in Automation, control, and intelligent Systems

作者： Qingyang Yan Wenxia Xu Jian Huang Suping Cao Key Laboratory of Ministry of Education for Image Processing and Intelligent Control the School of Automation Huazhong University of Science and Technology

ISBN: (纸本)9781479987313

A human motion intent estimation algorithm based on laser ranger finder and force sensors is designed for a walking-aid robot. By applying the proposed algorithm to the robot, the user can operate the walking-aid robot more fluently, comfortably and safely. A walking-aid or rehabilitation robot normally estimates the user's motion intention by measuring the interactive forces between human and robot. Whereas, the human motion should be represented as a coordination between the arms and the legs movements. This study therefore proposes a human motion intent estimation algorithm by fusing the motion intentions detected by the force sensors and the laser ranger finder, which are used to monitor the movements of arms and legs respectively. A special arrangement of push-pull force sensors is implemented for estimating the human motion intention I from user's operations on the handles. Meanwhile the human motion intention II is extracted by a laser ranger finder observing the user's movement of legs. A multi-sensor fusion algorithm is employed to fuse these two estimates. Experimental results are presented to show the validity of the proposed human motion intent estimation algorithm.

关键词： Human motion force sensors Robot Laser selectors Rehabilitation robotics Arms Arm spiral arm

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Multi-sensor based human motion intention recognition algorithm for walking-aid robot

Multi-sensor based human motion intention recognition algori...

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IEEE International Conference on Robotics and Biomimetics

作者： Wenxia Xu Jian Huang Qingyang Yan Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781467396769

In the coming aging society, it is extremely important to develop devices, which can support and aid the elderly in their daily life. In this paper a multi-sensor based human motion intention recognition algorithm is proposed for walking-aid robot. The mechanism of walking-aid robot was first introduced. Then human intent motion was estimated by force sensors and LRF respectively. A new concept called intentional motion (IM) is proposed to quantitatively describe this moving intention and then estimated by conventional Kalman filter. Based on the two human intent motions estimated by force sensors and LRF, IM can be online inferred by applying Kalman filter method. Finally, the validity of the proposed algorithm is confirmed by the experiments. The experimental results show that the user feels more natural and comfortable when our multi-sensor based human motion intention recognition algorithm is applied.

关键词： Legged locomotion Robot sensing systems Robot kinematics Force sensors Senior citizens

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Small target detection using an optimization-based filter 40

Small target detection using an optimization-based filter

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40th IEEE International Conference on Acoustics, Speech, and Signal processing, ICASSP 2015

作者： Xie, Kai Fu, Keren Zhou, Tao Yang, Jie Wu, Qiang He, Xiangjian Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China School of Computing and Communications University of Technology Sydney Australia

ISBN: (纸本)9781467369978

Small target detection is a critical problem in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some challenges remained, e.g. cloud edges and horizontal lines are likely to cause false alarms. This paper proposes a novel method using an optimization-based filter to detect infrared small target in heavy clutter. First, we design a certain pixel area as active area. Second, a weighted quadratic cost function is performed in the active area. Finally, a filter based on statistics of active area is derived from the cost function. Our method could preserve heterogeneous area, meanwhile, remove target region. Experimental results show our method achieves satisfied performance in heavy clutter. © 2015 IEEE.

关键词： active area area statistics heavy clutter optimization-based filter small target detection

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Adaptive fuzzy sliding mode control for pneumatic muscle actuator

Adaptive fuzzy sliding mode control for pneumatic muscle act...

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Chinese Automation Congress (CAC)

作者： Jin Qian Jian Huang Songhyok Ri Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei China

In this paper, an adaptive fuzzy sliding mode control approach which combines fuzzy control with the sliding mode control, is applied for the tracking control of pneumatic muscle actuator (PMA). This actuator is widely used in the rehabilitation robots while hard to control due to its strong nonlinearity. The switching-type control term in the sliding mode control law is approximated by a fuzzy system. Based on Lyapunov theory, the stability of the closed-loop PMA system can be guaranteed. Both simulation and experimental studies were carried out to verify the proposed methods. The experiments were conducted on a real PMA system, which was connected with the xPC target system. The results demonstrate the validity of the PMA as well as the effectiveness of the control algorithm even there exist system uncertainties and external bounded disturbances.

关键词： Software Real-time systems Fuzzy control Robots Switches Mathematical model Sliding mode control

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Mid-level parts mined by feature selection for action recognition

Mid-level parts mined by feature selection for action recogn...

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Asian Conference on Pattern Recognition (ACPR)

作者： ShiWei Zhang Nong Sang ChangXin Gao FeiFei Chen Jing Hu Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology China

ISBN: (纸本)9781479961016

This paper develops a method to learn very few discriminative part detectors from training videos directly, for action recognition. We hold the opinion that being discriminative to action classification is of primary importance in selecting part detectors, not just intuitive. For this purpose, part selection based on feature selection is proposed, employing SVM method. Firstly, large number of candidate detectors are trained using k-means and Exemplar-LDA techniques in whitened feature space. Secondly, each candidate part detector is regarded as a visual feature, so that detector selection can be achieved by feature selection. Detectors with larger weight, indicating more discriminative, will be selected. Meanwhile, to keep space-volume structure information, we use the novel method saliency-driven pooling to form feature primitives which are concatenated into mid-level feature vector. Finally, we conduct experiments on three challenging action datasets (KTH, Olympic Sports, HMDB51) and the results outperform the state-of-the-art.

关键词： Detectors Feature extraction Videos Support vector machines Semantics Pattern recognition image recognition

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Reflection invariant local binary patterns for image texture classification

Reflection invariant local binary patterns for image texture...

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Research in Adaptive and Convergent Systems, RACS 2015

作者： Song, Enmin Pan, Ning Hung, Chih-Cheng Li, Xiang Jin, Lianghai School of Computer Science and Technology Huazhong University of Science and Technology Key Laboratory of Education Ministry for Image Processing and Intelligent Control Wuhan430074 China College of Biomedical Engineering South-Central University for Nationalities Wuhan430074 China Sino-US Intelligent Information Processing Lab Anyang Normal University Kennesaw State University MariettaGA30060 United States

ISBN: (纸本)9781450337380

In this study we modified the local binary pattern operator (LBP) to obtain the robust invariant texture patterns for image texture classification. The modified method will be able to calculate patterns which are invariant for translation, scaling, rotation and reflection. Therefore, the modified LBP is called R-LBP. Although many variation of LBP have been proposed, most of them cannot detect and recognize the patterns of reflection. Both clockwise and counter clockwise coding is used in the proposed R-LBP operator in order to derive a minimum code to representing the pattern. Experimental results show that the proposed method is effective in determining the invariant patterns for image texture classification. © 2015 ACM.

关键词： Local binary pattern

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Design of chinese natural language in fuzzy boundary determination algorithm based on big data

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Journal of Information Hiding and Multimedia Signal processing 2017年第2期8卷 423-434页

作者： Zhang, Fu Quan Mao, Zi Jing Ding, Gang Yi Xu, Lin School of Software Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China Via Room A9#301 Juyuan JiyuanFuzhou350008 China Department of Electrical Engineering University of Texas at San Antonio One UTSA Circle San AntonioTX78249 United States Via Arrow Oaks 126 San AntonioTX78249 United States Beijing Institute of Technology Via Room 611 Software Building 5 South Zhongguancun Street Haidian Beijing100081 China Innovative Information Industry Research Institute Fujian Normail University Fuzhou350300 China Via Fuqing Brunch of Fujian Normal University Campus County 1# Longjiang Road FuqingFuzhou350300 China

In this study, we proposed a new method to determine the fuzzy boundary of natural language based on big data. According to the principle of natural language recognition, the acoustic characteristics of the analysis, natural language acoustic model and statistical model is established, Viterbi decoding algorithm has been applied for natural language decoding, and take this as the basis, we implemented deep learning methods for natural language feature extraction, and used the support vector machine method for classification, according to the characteristics of natural language significant division, in accordance with the constraints, combined with large data analysis method, to determine the natural language fuzzy boundary. Experimental results indicate that using the proposed method, compared with existing methods the recall and accuracy rate have been improved. © 2017 ISSN.

关键词： Big data

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Cell resistance slope combined with LVQ neural network for prediction of anode effect 6

Cell resistance slope combined with LVQ neural network for p...

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6th International Conference on intelligent control and Information processing, ICICIP 2015

作者： Zhou, Kaibo Lin, Zhikai Yu, Dengzhi Cao, Bin Wang, Ziqian Guo, Sihai School of Automation Huazhong University of Science and Technology Key Laboratory of Ministry of Education Image Processing and Intelligent Control Wuhan430074 China Guiyang Aluminum Magnesium Design and Research Institute Guiyang550004 China School of Automation Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9781479917174

It is an important part in aluminum electrolysis production to control the anode effect (AE). Since there are some shortcomings in traditional methods of anode effect prediction in aluminum electrolysis, this paper combined two methods, the slope of cell resistance and learning vector quantization (LVQ) neural network, to predict anode effect. First of all, the first prediction of anode effect will be conducted based on the slope of cell resistance. Afterwards, the inaccurate data are supposed to be re-predicted. The second prediction consists of two steps, one is to estimate the power spectrum from the signal of cell resistance by means of periodogram, the other is to re-predict the anode effect with the LVQ neural network, since the energy of frequency bands are served as the input feature variables of neural network, so as to raise the accuracy of prediction. It turned out that the success rate of ten-minute in advance prediction for anode effect can be above 85%, though just cell resistance signal is studied. © 2015 IEEE.

关键词： Forecasting

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3D model generating method based on multi-views deblurring images

3D model generating method based on multi-views deblurring i...

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International Conference on Optoelectronics and Microelectronics (ICOM)

作者： Yu Shi Hanyu Hong Jie Song Xia Hua Laboratory of Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan P.R.China

The image of moving target which captured though image acquisition system in mobile platform is contaminated by blur and noise, then it make the 3D(3 dimension) model of target difficult to reconstruct. A new method of 3D Model generating is proposed for this question. Firstly, detect SURF characteristic points of deblurred images and match it. Obtain the camera parameter matrix through solve Kruppa equation according to character points which is matched. Then, estimate the points of partly deblurred images and get the blur kernel of the other images with camera model which obtained in the previous step. Finally, according to the camera parameter matrix make space transformation for the pixels of images. A serials experiment validate high-efficiency of the proposed method.

关键词： Solid modeling Three-dimensional displays Cameras Feature extraction Kernel Mathematical model image restoration

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