检索结果-内蒙古大学图书馆

第28届中国控制与决策会议

作者： Lijun Wang Qing Li Ruihua Jiao Yixin Yin Yinan Feng Yichang Liu School of Automation & Electrical Engineering University of Science and Technology Beijing Key Laboratory of Advanced Control of Iron and Steel Process(Ministry of Education) University of Science and Technology Beijing

ISBN: (纸本)9781467397155

To deal with the problem of observing or tracking for discontinuous signal,a kind of second order linear extended state observer(LESO) algorithm is *** ESO estimating the uncertain disturbance,a simple second-order linear ESO with less tunable parameters was designed in the absence of dynamic model,and the method of discrete time realization was *** proposed LESO was applied to the tracking of discontinuous Stribeck Friction in comparison with adaptive state *** results show that the proposed ESO is effective and practical.

关键词： Extended State Observer Adaptive State Observer Stribeck Friction Discontinuous Track

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Interval T-S Fuzzy Model and Its Application to Identification of Nonlinear Interval Dynamic System based on Interval Data

Interval T-S Fuzzy Model and Its Application to Identificati...

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Joint 48th IEEE Conference on Decision and control and 28th Chinese control Conference

作者： Xu Zhengguang Sun Changping IEEE School of Information Engineering University of Science and Technology Beijing Key Laboratory for Advanced Control of Iron and Steel Process(Ministry of Education) University of Science and Technology Beijing

In this paper,a new fuzzy system model structure-Interval T-S Fuzzy Model（ITSFM） is *** from interval regression analysis,the interval arithmetic is incorporated with classical T-S fuzzy model and the parameters in consequent part of the ITSFM model become to be ***,the outputs of the proposed ITSFM are *** addition,we define fuzzy interval set,center membership function and radius membership function for intervals and an arithmetical operation between a constant interval and a general real *** the proposed ITSFM is applied to identification of nonlinear interval dynamic system based on the measured interval *** results are then presented that indicate the validity and applicability of the proposed ITSFM.

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Model Reduction of Two-Dimensional Discrete-time Systems Based on Finite-Frequency Approach

Model Reduction of Two-Dimensional Discrete-time Systems Bas...

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第三十二届中国控制会议

作者： Da-Wei Ding Xiaoli Li School of Automation & Electrical Engineering University of Science and Technology Beijing Key Laboratory of Advanced Control of Iron and Steel Process(Ministry of Education) University of Science and Technology Beijing

ISBN: (纸本)9781479900305

This paper deals with the model reduction problem of two-dimensional(2-D) discrete-time systems described by the Roesser *** from existing fuU-frequency methods,we propose a finite-frequency model reduction method for 2-D Roesser *** the generalized Kalman-Yakubovich-Popov(GKYP) lemma for 2-D systems,sufficient conditions are developed for model reduction of 2-D Roessor systems over low-frequency,and middle-frequency,*** proposed finite-frequency model reduction method can get a better approximation accuracy than the existing full-frequency ones over the finite-frequency *** effectiveness of the proposed method is illustrated by a numerical example.

关键词： Model reduction two-dimensional Roesser systems finite-frequency ranges

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A high-order sliding mode stator flux observer for asynchronous motor based on feedback linearization

A high-order sliding mode stator flux observer for asynchron...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Yuedou Pan Tao Chen School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing China

ISBN: (纸本)9781467376839

This paper proposes a high-order sliding mode stator flux estimation method for asynchronous motor based on feedback linearization. Selecting the rotor flux as the system's output, the coordinate change matrix and the nonlinear state feedback are derived based on the affine nonlinear model of asynchronous motors by using the nonlinear system's differential geometry theory. Then the asynchronous motor system is input-output linearized and the feedback linearization model of asynchronous motors is obtained. On this basis, a high-order sliding mode rotor flux observer for asynchronous motor is designed to estimate rotor flux, and this paper analysis the stability of the designed observer, then we can calculate stator flux by using the rotor flux. The designed observer is applied to Direct Torque control (DTC) of the asynchronous motor and achieves a good control performance. Simulation results verify the effectiveness and feasibility of the proposed method.

关键词： Stators Observers Rotors DC motors Nonlinear systems State feedback

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Mobile robot's electronic compass calibration based on modified Fourier Neural Network

Mobile robot's electronic compass calibration based on modif...

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IEEE Conference on Robotics, Automation and Mechatronics

作者： Gong Kun Deng Fang Ma Tao Gong Kun is with School of Automation Beijing Institute of Technology and Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing China Deng Fang is with School of Automation Beijing Institute of Technology and Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing China Ma Tao is with School of Automation Beijing Institute of Technology and Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing China

In order to improve the precision of the azimuth measured by mobile robot's electronic compass, this paper proposes a new calibration method based on Fourier Neural Network trained by Modified Particle Swarm Optimization (MPSO-FNN). This method makes use of Fourier Neural Network (FNN) to establish the error compensation model of electronic compass's azimuth, and introduces Modified Particle Swarm Optimization (MPSO) algorithm to optimize the weights of neural network. Thus the comparatively accurate error model of azimuth is obtained to compensate the output of electronic compass. This method not only has strong nonlinear approximation capability, but also overcomes the neural networks' shortcomings which are too slow convergence speed, oscillation, and easy to fall into local optimum and sensitive to the initial values. Experimental results demonstrate that after calibrated by this method, the range of azimuth error reduces to -0.35°~0.70° from -3.4°~25.2°, and the average value of absolute error is only 0.30°.

关键词： Compass Azimuth Biological neural networks Particle swarm optimization Training Accuracy Automation

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FACE LOCATION AND EYE CHARACTER DETECTION BASED ON MONOCULAR VISION GAZE TRACKING SYSTEM

FACE LOCATION AND EYE CHARACTER DETECTION BASED ON MONOCULAR...

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2010 2nd IEEE International Conference on Network Infrasturcture & Digital Content(2010年第二届IEEE网络基础设施与数字内容国际会议 IC-NIDC 2010)

作者： Fenhua Wang Xiao Chen Jiannan Chi Zhiliang Wang Iron and Steel Flow Advanced Control Ministry of Education Key LaboratoryUniversity of Science & Technology Beijing China

In the paper an face location and eye detection method is proposed based on active infrared source system, which is to solve the problems of pupil threshold segmentation according to from coarse and fine strategy. This method use bright pupil and dark pupil difference scheme. Firstly, we collect a lot of dark images to train classifiers make use of Haar features, boosting them to be a strong classifiers to face location;then potential region of pupil is found based on the knowledge about facial structure;Finally, human eyes location can be precise found.

关键词： gaze tracking face location eye location dark and bright pupil image cascade classifiers

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Burden Distribution control Based on Adaptive Genetic Algorithm in Bell-less Blast Furnace

Burden Distribution Control Based on Adaptive Genetic Algori...

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第三十三届中国控制会议

作者： Qiao Zhu Yi-Xin Yin Han-Qing Cheng Xian-Zhong Chen School of Automation & Electrical Engineering University of Science and Technology Beijing Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing

ISBN: (纸本)9781479947249

The proper control of the ratio of ore to coke distribution(ROCD) can achieve energy saving of the blast furnace(BF).In order to achieve the desired ROCD,it is meaningful to search best charging system(especially the burden matrix).This paper deals with the problem of burden distribution control based on the adaptive genetic algorithm and multi-radar ***,the definition of the ratio of ore to coke(ROC) and the desired ROCD are ***,according to the desired ROCD,the concrete steps of searching the best burden matrices are presented based on the adaptive genetic ***,the operators of the adaptive genetic algorithm(especially the mutation operator) are properly adjusted,according to the actual production process of the bell-less ***,three computational experiments demonstrate the effectiveness of the method.

关键词： Bell-less blast furnace Adaptive genetic algorithm Ratio of ore to coke distribution Multi-loop burden matrices.

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Analysis and pattern recognition of blast furnace burden surface based on multi-radar data

Analysis and pattern recognition of blast furnace burden sur...

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International Conference on Intelligent control and Information processing (ICICIP)

作者： Xiang Zhou Xiaoli Li Dexin Liu Yixin Yin Xianzhong Chen Qingwen Hou Key Laboratory of Advanced Control of Iron and Steel Process Ministry of Education University of Science and Technology Beijing Beijing China University of Science and Technology Beijing Beijing Beijing CN

iron making is the first stage and also an important part in steel making process, which will bring the problem of energy efficiency and economic benefits. In this process, the distribution of the blast burden impacts greatly on the production of BF (blast furnace). Therefore, the prediction of furnace burden distribution in furnace throat will play an important role in the control strategy of furnace burden. Based on the data from the multi-radar, the blast burden curve can be formed. Feature extraction and classification based on different curves (i.e. different pattern) can be made by using BP neural networks. The work proposed in this paper will be a guidance for the future research of burden surface based on the data of phased-array radar.

关键词： Turning Blast furnaces Radar imaging Feature extraction Surface treatment

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Application of Fuzzy Neural Network in Burden Surface Clustering

Application of Fuzzy Neural Network in Burden Surface Cluste...

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The 24th Chinese control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Dexin Liu Xiaoli Li Shuting Lu Dawei Ding Xianzhong Chen School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing 100083 China

Blast furnace charging distribution plays an important role in the steel production. The radar data containing the information of present burden surface situation and the cross thermometer data reflecting the trend of burden surface are taken as the training data of fuzzy neural network. The trained network will be used for the future clustering of the data. Considering the demand of energy-saving and consumption-decreasing, the method sets up the basic for the distribution control in the next step. The simulation results show the effectiveness of the proposed method.

关键词： Burden Surface Fuzzy Neural Network and Cluster

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Online Contribution Rate Based Fault Diagnosis for Nonlinear Industrial processes

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Acta Automatica Sinica 2014年第3期40卷 423-430页

作者： Kai-Xiang PENG Kai ZHANG Gang LI Key Laboratory for Advanced Control of Iron and Steel Process School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China Department of Automation Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing 100084 China

Over past decades, kernel principal component analysis (KPCA) appeared quite popularly in data-driven process monitoring area. Enormous work has been done to show its simplicity, feasibility, and effectiveness. However, the introduction of kernel trick makes it impossible to directly employ traditional contribution plots for fault diagnosis. In this paper, on the basis of revisiting and analyzing the existing KPCA-relevant diagnosis approaches, a new contribution rate based method is proposed which can explain the faulty variables clearly. Furthermore, a scheme for online nonlinear diagnosis is established. In the end, a case study on continuous stirred tank reactor (CSTR) benchmark is applied to access the effectiveness of the new methodology, where the comparisons with the traditional linear method are involved as well.

关键词： Kernel principal component analysis (KPCA) nonlinear fault detection contribution rate fault diagnosis

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