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An Improved Switching controller for Boost Converter Based on Hybrid Automata Model

An Improved Switching Controller for Boost Converter Based o...

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Chinese Automation Congress (CAC)

作者： Yi-Juan Ning Hai-Peng Ren Jie Li Shaanxi Key Laboratory of CoTplex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China Department of Electrical Engineering Xi’an University of Technology Xi’an China

Power electronic converters play an important role in the energy conversion. Power electronic converters, exhibiting different system dynamical characteristics according to the onoff state of the switch, are typical switching (nonlinear) systems. The traditional model of power electronic converter is the small signal average model and the converter controller is designed using the linear system theory. This kind of method is effective only within the vicinity of the predefined operating point. When the system parameter varies in a large scale, the converter control performance will degrade. The hybrid system model reflects the essential switching characteristics of the converter, and the controllers designed based on the hybrid model are suitable for converter control when the system states or parameters vary in a large scale. However, the parameter uncertainty is still a problem in conventional switching control method. In this paper, the inductor current compensation control is proposed to deal with the uncertainties of the circuit parameters and working point variation. The effectiveness of the proposed method is verified by both simulation and experiment.

关键词： Switches Voltage control Resistance Inductance Matrix converters

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Assessment and prediction of leakage degree of expansion joints in underground network heating pipe network based on LS-SVM and ARIMA model 13

Assessment and prediction of leakage degree of expansion joi...

引用

13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018

作者： Shang-Bin, Jiao Le, Fan Peng-Yue, Wu Lei, Qiao Yong-Ze, Jin Qian-Kun, Shen Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China Xi'an Thermal Power Research Institute Co. Ltd Xi'an710054 China

ISBN: (纸本)9781538637579

The study shows that the leakage of the expansion joints in the underground heating primary pipe network will lead to the fluctuation of soil temperature and conductivity around the leakage point. Based on the online monitoring of changes of physical quantities around the expansion joint, this paper established the assessment model of temperature and conductivity as the input parameters and the degree of expansion joints leakage as the output parameters, which took the radial basis function as kernel function and made use of PSO algorithm to achieve the optimization of the kernel function parameters. Then, the temperature and conductivity were predicted based on the ARIMA model, and the LS-SVM assessment of expansion joint leakage was realized according to the prediction results. Both simulation and field experiments show that the prediction model based on ARIMA has higher accuracy, which has identified the foundation for on-line prediction and accurate assessment of the expansion joint leakage in the underground heating primary pipe network. © 2018 IEEE.

关键词： Particle swarm optimization (PSO)

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An Early Forest Fire Detection Method Based on Unmanned Aerial Vehicle Vision

An Early Forest Fire Detection Method Based on Unmanned Aeri...

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第30届中国控制与决策会议

作者： Sha Ma Youmin Zhang Jing Xin Yingmin Yi Ding Liu Han Liu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

Traditional forest fire detection methods based on flame are subject to detection delays due to the later appearrance of flame than smoke. When the flame is detected, the fire might have already been spread and out of ***, the objective of this paper is to study new fire detection method based on smoke. First a quadrotor unmanned aerial vehicle(UAV) is adopted to capture the fire video;then the collected video sequence will be processed by a series of preprocessing including filtering and image enhancement;finally a new significance detection algorithm is investigated for early and efficient smoke detection. Experimental results show that the algorithm can detect smoke effectively.

关键词： UAV vision Fire smoke Fire detection Significance detection algorithm

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Horizontal Positioning and Anti-swinging control Tower Crane Using Adaptive Sliding Mode control

Horizontal Positioning and Anti-swinging Control Tower Crane...

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第30届中国控制与决策会议

作者： Wen Wen Bai Hai-Peng Ren Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology

As a non-linear underactuated system, the tower crane should be controlled to transport the load to reference position quickly and smoothly. The actual tower crane is susceptible to the environment interference during operation. Conventional Proportion Integral Derivative（PID） controller cannot deal with this interference. Sliding mode control（SMC） is robust to system uncertainties and external disturbances, but it needs to know the upper bounds of uncertainties and external perturbations, which are usually unknown in practical systems. Adaptive backstepping sliding mode control（ABSMC） is used to adaptively estimate the uncertainties and external disturbances, and the stability of the system is proved based on Lyapunov theory. Compared with SMC, the proposed ABSMC has strong robustness.

关键词： tower crane Proportion Integral Derivative Sliding mode control Adaptive backstepping sliding mode control

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Research on Saturation of PMSM system Regulator for Electric Vehicle

Research on Saturation of PMSM System Regulator for Electric...

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Chinese Automation Congress (CAC)

作者： Shengmin Li Zeling Zhang Dan Zhao Siyu Guo Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing Xi'an China

The saturation phenomenon often happens to the regulator in the start-up procedure of electric vehicles. And the dynamic and static performance of the motor will be worse while this phenomenon lasts longer. In this paper, firstly we will analyze the causes of this phenomenon, and then propose an effective method to solve the regulator saturation. Based on traditional double-loop vector control, this method increased the voltage cut-off negative feedback and combined the state feedback linearization to realize the dynamic decoupling between currents and solve the current regulator saturation problem which happens during start-up procedure. Finally, the feasibility and effectiveness of the proposed method were verified by simulation experiments, and the comprehensive performance of the motor, including speed range, speed tracking performance and dynamic response, was improved.

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Network Parameter Generation for One-Shot Object Detection

Network Parameter Generation for One-Shot Object Detection

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IEEE International Conference on Unmanned systems (ICUS)

作者： Kang Wang Jiajia Zhao Yang Wang Shuigeng Zhou Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University Shanghai China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineer Institute Beijing China School of Information Engineering Nanchang University China

ISBN: (纸本)9781728137933

Recent object detection models have achieved satisfactory performance by deep learning with large-scale annotated datasets. However, these models often perform poorly when the training examples are not sufficient enough, especially for one-shot object detection where there is only one training example of each target class. In this paper, we propose a network parameter generation framework for effective one-shot object detection. By leveraging the semantic relationship between the source-domain and the target-domain (new classes), our framework can generate network parameters for the new classes directly. Furthermore, we develop two implementation schemes for this framework: weighting-based parameter generation and regression-based parameter generation. These two schemes use different information to construct the relationship and transfer knowledge from the source-domain to the target-domain. Experiments on the PASCAL-OSCD benchmark show that our methods can significantly boost the performance of one-shot object detection.

关键词： Object detection Detectors Head Training Feature extraction Task analysis Training data

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Distributed dimensionality reduction of industrial data based on clustering

Distributed dimensionality reduction of industrial data base...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Yongyan Zhang Guo Xie Wenqing Wang Xiaofan Wang Fucai Qian Xulong Du Jinhua Du Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing China

Large amounts of data are produced in system operation, and how to extract effective information from these data has become an important research topic in the industrial application. Dimensionality reduction is a way to refine the data. Because of the low efficiency of the existing methods, these methods can't discover the internal structure of the data. Regarding these problems, a distributed method of dimensionality reduction based on clustering is proposed, which includes the following steps:(1) Clustering the data into some small classes according to the similarity between the data variables; (2) reducing the dimension of data in a small class after being clustered respectively; (3) merging the data after being reduced dimension; (4) classifying the data after being merged by support vector machine (SVM). The data in the simulation is the test data, and the results show that the methods proposed in this paper are better than the existing dimensionality reduction methods.

关键词： Dimensionality reduction Support vector machines Clustering algorithms Distributed databases Data mining Principal component analysis Classification algorithms

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Effects of control Parameters on Oxygen Distribution in Czochralski Crystal Growth Process

Effects of Control Parameters on Oxygen Distribution in Czoc...

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Chinese Automation Congress

作者： Jun-Chao Ren Ding Liu Yin Wan Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi‘an University of Technology Xi'an China

The application of a quadrupole magnetic field structure with low power consumption and high field strength is very effective in solving the problem of non-uniformity of oxygen concentration distribution in the process of industrial drawing single crystal silicon by MCZ method. In this paper, a 3D model is used to simulate the crystal growth process under the action of quadrupole magnetic field for accurately describe the effect of control parameters on the oxygen concentration distribution at the crystal-melt interface. The results show that the radial oxygen concentration gradient at the crystal-melt interface is positively correlated increases with the radial temperature gradient when the magnetic induction strength is increased, while the positive correlation decreases with the increase of the crucible rotation speed or the crystal rotation speed within the appropriate range. Moreover, the uniformity of the radial oxygen concentration distribution at the crystal-melt interface can be improved by about 19.11% when the crystal rotation speed is higher and the crucible rotation speed is lower, which is more favorable for improving the quality of the silicon single crystal.

关键词： Quadrupole magnetic field Czochralski silicon single crystals Numerical simulation Crystal-melt interface Oxygen concentration distribution

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Research on Grounding Fault Detection Method of united adjustment power source system Based on VMD and Comprehensive Energy Relative Entropy

Research on Grounding Fault Detection Method of united adjus...

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Chinese Automation Congress (CAC)

作者： Shangbin Jiao Yunpeng Yang Jingwen Guo Sen Li Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi‘an University of Technology Xi'an China

The paper present a ground fault detection method of united adjustment power source system based on variational mode decomposition (VMD) and comprehensive energy relative entropy. First, the analysis of the system revealed the fault feature extraction is more difficult and the line selection is inaccurate. Secondly, we summarize the fault characteristics of different operation modes. Different operation modes select line by the same selection line method. The proposed method can accurately extract feature in the weak zero sequence current of each feeder, and distinguish the bus fault and feeder fault for each mode of operation. The simulation results show that the proposed method is also suitable for the traditional small current grounding system, and distribution networks with different voltage levels and grounding modes. The results of laboratory simulation experiments show that the method is reliable and practical.

关键词： Entropy Fans Grounding Feature extraction Transient analysis Power generation Generators

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Fast S-transform for fault line selection in distribution network system

Fast S-transform for fault line selection in distribution ne...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Jiao Shang-bin Yang Yun-peng Shi Yan-jin Shi Wen-wen Guo Jing-wen Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China

The current of the distribution networks under 66kV is widely operating in small current grounding mode. The problem of extracting the fault feature in each line would be quite difficult due to the short duration of the transient zero sequence current with the non-stationary and non-linear characteristics when the single-phase-to-ground fault occurs in the system. Therefore, a novel method of single-phase-to-ground fault line selection for small current based on Fast S-transform (FST) is developed in this paper. Firstly, FST is presented to transform the transient electric current signal in each feeder, after that the one-dimension modulus and phase angle value can been obtained. Then, the feeder with the largest energy value calculated by the modulus obtained above is selected as the alternative possible fault line. Finally, line failure or bus failure can been determined by evaluating the difference of the phase angle between the fault line and the comparison line that has been selected from the non-alternative feeders before. The results of the simulative and experimental circuits reveal that the proposed method using FST can avoid the influence of neural point grounding type. Additionally, the method of line selection is quite accurate and real-time.

关键词： Transient analysis Circuit faults Grounding Time-frequency analysis Feature extraction Fourier transforms

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