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检索条件"机构=Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan"

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Hierarchical Prediction Model Based on BP Neural Network for Predicting CO/CO2 in Iron Ore Sintering Process

Hierarchical Prediction Model Based on BP Neural Network for...

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第37届中国控制会议

作者： Ben Xu Xin Chen Yang Zhou School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

The sintering process is one of the most energy-consuming processes in steelmaking, its carbon fuel consumption accounts for 8% to 10% in the steel production *** find ways of reducing the energy consumption, it is necessary to predict the carbon efficiency. The value of CO/CO in the carbon emission can reflect the utilization of carbon combustion in sintering process. In this study, the CO/CO is taken to be a measure of carbon efficiency and a hierarchical model is built to predict it. Firstly, the physical and chemical reactions and the carbon flow mechanism in the sintering process are analyzed, and the process parameters that affect the CO/CO are determined. Then, the gray relational analysis method is used to analyze the influence factors to determine the relationship between the parameters, and a hierarchical predictive model for CO/CO is established based on the relationship between the parameters. The hierarchical predictive model is divided into two parts: the predictive models for the thermal state parameters and the predictive model for CO/CO. The inputs of the predictive models for the thermal state parameters are the raw material parameters and the operating parameters, and the inputs of the predictive model for CO/CO are the predicted values of the predictive models for the thermal state parameters. Finally, the simulation results verify the effectiveness of the proposed modeling method. This method can provide a theoretical basis for the optimization and control of carbon efficiency in the sintering process.

关键词： carbon efficiency sintering process back-propagation neural network（BPNN）

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Improved Kriging for Drilling Visualization Based on Quantum Genetic Algorithm

Improved Kriging for Drilling Visualization Based on Quantum...

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第37届中国控制会议

作者： Zheng Zhang Xuzhi Lai Min Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

To realize drilling visualization, an effective interpolation method is essential to construct three-dimensional *** is an effective interpolation method commonly used by geologists. However, the variogram model parameters in traditional Kriging have a certain subjectivity, which will influence the accuracy of interpolation. Quantum Genetic Algorithm（QGA）is introduced to optimize the variogram model parameters selection in this paper. Elevation values of boreholes are used as data sets for simulation. The results show that the proposed improved Kriging has a better prediction accuracy.

关键词： Kriging Quantum Genetic Algorithm Optimization Interpolation

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Finite-time H∞ state estimation for discrete time-delayed stochastic switched genetic regulatory networks with uncertain sojourn probabilities

Finite-time H∞ state estimation for discrete time-delayed s...

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第37届中国控制会议

作者： REN Chuanyu WAN Xiongbo School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper investigates the problem of finite-time H∞ state estimation for discrete-time stochastic switched genetic regulatory networks（GRNs） with time-varying delays and exogenous disturbances. A new discrete time-delayed stochastic switched GRN model with uncertain sojourn probabilities is devised, which is more general than the switched GRNs model with completely known sojourn probabilities. The sufficient conditions which guarantee the stochastic finite-time boundedness of the estimation error dynamics with a prescribed H∞ disturbance attenuation level are derived. By solving several matrix inequalities,the state estimator parameters can be obtained. A numerical example is given to illustrate the effectiveness of our results.

关键词： Genetic regulatory networks（GRNs） Finite-time H∞ state estimation Uncertain sojourn probabilities

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Dense Depth Estimation with Absolute Scale

Dense Depth Estimation with Absolute Scale

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第37届中国控制会议

作者： Xing Jin Zhiwen Yao Jingjing Zhang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Considering the difficulties in estimating depth from single image, in this paper, we propose a method to obtain the absolute scale depth map by combining the convolution neural network and depth filter. We compute relative transformation between consecutive frames by direct tracking features, which are extracted from RGB images and whose depthes are predicted by deep network, and then optimize relative motion by searching for a better feature alignment in epipolar line, and finally update every pixel depth of the reference frame by depth filter. We evaluate the proposed method on the open dataset comparison against the state of the art in depth estimation to evaluate our method.

关键词： Depth Estimation Pose Estimation Depth Filter

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A control Strategy with Zero Residual Vibration for A Planar Single-Link Flexible Manipulator

A Control Strategy with Zero Residual Vibration for A Planar...

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第37届中国控制会议

作者： Qingxin Meng Xuzhi Lai Ze Yan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

The residual vibration（RV） problem of the flexible link manipulators（FLMs） is very difficult to solve due to the low stiffness and the underactuated feature of these *** paper presents a control strategy with zero RV for a planar singlelink flexible manipulator（PSLFM）.The stable control objective of the system is to stabilize the PSLFM at a target equilibrium point with zero ***,the dynamic model of the PSLFM is built by using the assumed mode method（AMM）.Then,we transform the control to the trajectory tracking control.A forward trajectory and a reverse trajectory are obtained by using a bidirectional trajectories planning ***,these two trajectories are connected by using the genetic algorithm（GA）.After doing this,we get a trajectory of the system from the initial equilibrium point to the target equilibrium ***,we design a trajectory tracking controller based on the sliding mode variable structure control method to control the PSLFM track this *** simulation results show that the PSLFM arrives the target equilibrium point with zero RV,which demonstrates the effectiveness of this control strategy.

关键词： Planar single-link flexible manipulator Underactuated systems Zero residual vibration Trajectory tracking control

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Measurement System of Ferromagnetic Film Magnetic Properties Based on Magneto-optical Kerr Effect

Measurement System of Ferromagnetic Film Magnetic Properties...

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第37届中国控制会议

作者： Xueying Fu Wenqin Mo Shun Yuan Liming Xu Junlei Song Kaifeng Dong Fang Jin School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

A new measuring system for magnetic properties of the ferromagnetic thin film has developed based on magneto-optical Kerr effect（MOKE）. This system can realize both polar MOKE and longitudinal MOKE measurements through the optimization of optical path and electromagnet’s poles. The signal processing software on Lab VIEW has been also designed to acquire the Kerr signal and plot the hysteresis loop. The MOKE measurements have been performed to investigate the magnetic properties of ferromagnetic films such as Co Fe Si B, permalloy and Ni Fe/Ag/Ni Fe multilayer. The experimental results proved that the system has a high angular accuracy of 0.0008°.

关键词： Magneto-optical Kerr effect Kerr rotation angle Ferromagnetic film LabVIEW

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On Self-adjusting Fuzzy controller Based on Feedforward Compensation Decoupling

On Self-adjusting Fuzzy Controller Based on Feedforward Comp...

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第37届中国控制会议

作者： Zhenjiang Feng Yongbo Li Zhenzhu Liu Xinmei Wang Kaiyuan Fu Juanjuan Wang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Aiming at the multivariable coupling characteristics and the complexity of its control inside the concrete curing box,this paper firstly analyzes the coupling relationship between temperature and humidity in the curing box, and uses the decoupling strategy of the feedforward compensation algorithm. The simulation results show that the decoupling effect is good. Then, based on the principle of the self-adjusting function on the transient performance of the system, a self-adjusting factor fuzzy controller is designed, which combines the decoupling method and the self-adjusting function to improve the control effect of the coupling variable of temperature and humidity inside the concrete curing box.

关键词： Temperature and Humidity Coupling Feedforward Compensation Algorithm Self-adjusting Function

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Synchronous Detector for GMI Magnetic Sensor Based on Lock-in Amplifier

Synchronous Detector for GMI Magnetic Sensor Based on Lock-i...

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第37届中国控制会议

作者： Jinchao Wang Fang Jin Lei Zhu Zhi Zhao Hengchang Rao Junlei Song Kaifeng Dong Wenqin Mo School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

A new concept of a synchronous detector for Giant Magneto-Impedance（GMI） sensors is presented. This concept combines a lock-in amplifier, with outstanding capabilities, high speed and a feedback approach that ensures the amplitude detection with easily adjustable gain. The synchronous detector is capable of measuring high-frequency and very low amplitude signals without the use of diode-based active rectifiers or analog switches. In comparison with most of the commercially available diode-based peak detectors, the linearity of the synchronous detector is generally better, especially for low level amplitudes. The synchronous detector has been used for the amplitude measurement of single frequency sine signal and for the demodulation of amplitude-modulated signal. It has also been successfully integrated in a GMI sensor prototype. Magnetic field measurements in open-and closed-loop of this sensor have been conducted. The measured sensitivity was about 1.02 V/Oe in open-loop while it was 0.12 V/Oe in close-loop. The above research provides technical accumulation for the design of sensor nodes based on GMI sensor wireless sensor networks.

关键词： magnetic sensor Giant Magneto-impedance synchronous detector amplitude demodulation

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RBF Neural Network Based-PID control for Weight on Bit During Drilling Operation

RBF Neural Network Based-PID Control for Weight on Bit Durin...

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第37届中国控制会议

作者： Sike Ma Min Wu Luefeng Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Deep drilling is a costly project and efficiency is of paramount importance. The weight on bit is one of the main operating parameters that influences the drilling efficiency and it was controlled by manual before. But after people saw the giant potential of an auto-drilling system in increasing the drilling efficiency, more and more studies on the feed back control of weight on bit have emerged. This paper mainly studied weight on bit dynamic under the variational formation based on a lumped parameter model and a self-tuning PID controller for weight on bit control. The parameters of the PID controller are tuned by using gradient descent method and RBF neural network identification.

关键词： Weight on bit auto-drilling system RBF neural network PID

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Unscented Kalman Filter for Nonlinear systems with One-step Randomly Delayed Measurements and Colored Measurement Noises

Unscented Kalman Filter for Nonlinear Systems with One-step ...

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第37届中国控制会议

作者： Xinmei Wang Zhenzhu Liu Leimin Wang Feng Liu Wei Liu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In this paper, a new unscented Kalman filter(Unscented Kalman filter, UKF) for nonlinear system with both one-step randomly delayed measurements and colored measurement noises is proposed. Firstly, the first-order Markov sequence model is used to whiten colored noise, at the same time, an independent and identically distributed Bernoulli variable is used to model the delay of measurement data transmission, then the model of nonlinear one-step randomly time delay system with colored noise whitening is established. Secondly, filter recursion formula of UKF under the above model is proposed through unscented transformation(Unscented transformation, UT) to calculate the posterior mean and covariance of the nonlinear state based on the Bayesian filter framework. The proposed new UKF method can effectively deal with the issue that traditional UKF is failure under the condition of one-step randomly delayed measurements and colored measurement noises. The efficiency and superiority of the proposed method are illustrated in a numerical example for a target tracking problem.

关键词： State Estimation Unscented Kalman Filtering One-step Randomly Delayed Measurements Colored Measurement Noises

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