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Chinese control Conference

作者： JunLei Song YanXia Huang ZhiHeng Yang MeiJuan Chen Yong Yang WenQin Mo KaiFeng Dong Fang Jin Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China School of Mathmatics and Physics China University of Geosciences Wuhan P. R. China

Piezoelectric geophones are vibration detectors that convert vibration acceleration signals into electrical signals. High performance piezoelectric materials can improve the sensitivity of piezoelectric geophone and meet the need of high-resolution seismic data acquisition. The comprehensive performance of relaxor piezoelectric single crystal PMN-PT is more superior than PZT, and it is potential to be applied to high sensitivity and small volume geophones. In this paper, the central compressed geophone core model based on PMN-PT was established and theoretically analyzed. Then, a multiphysics simulation model was set up in COMSOL for simulation calculation. Finally, experimental verification was carried out. The results show that using PMN-PT in geophone core design can improve the sensitivity of the model by more than 120% compared with the traditional PZT material. The PMN-PT has the potential to be applied to high sensitivity and small volume geophones.

关键词： Vibrations Sensitivity Acceleration Piezoelectric materials Sensors Earth Force

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Intelligent coordinating control between burn-through point and mixture bunker level in an iron ore sintering process

Intelligent coordinating control between burn-through point ...

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作者： Du, Sheng Wu, Min Chen, Xin Lai, Xuzhi Cao, Weihua School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems No. 388 Lumo Road Hongshan District Wuhan Hubei430074 China

Sintering is a process that involves complex physical and chemical reactions. An intelligent coordinating control strategy is proposed for the strong coupling between the burn-through point (BTP) and the mixture bunker level (MBL). First, an intelligent integrated controller is established for the BTP by fusing the neural network, expert rules, and fuzzy logic. Moreover, an expert controller is designed for the MBL based on expert rules using the analysis of the main factors that affect the MBL. Furthermore, by employing the soft switching control algorithm, an intelligent coordinating controller for the BTP and the MBL is designed. The optimal operation parameters are obtained from the algorithm, which realize the multi-objective control of the sintering process. Finally, a simulation and an experiment of the intelligent coordinating control between the BTP and the MBL are carried out, where the models of the BTP and the MBL are the Takagi-Sugeno (T-S) fuzzy model and the linear model, respectively. And the results show that the proposed approach is feasible and effective.

关键词： Mixtures

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Deep Forest-Based Classification of Hyperspectral Images

Deep Forest-Based Classification of Hyperspectral Images

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Chinese control Conference

作者： Xu Yin Ruilin Wang Xiaobo Liu Yaoming Cai Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China School of Computer Science China University of Geosciences Wuhan P. R. China

The classification of hyperspectral images (HSIs) is a hot topic in the field of remote sensing technology. In recent years, convolutional neural network (CNN) has achieved great success for HSI classification. However, CNN has to do a great effort in parameters tuning which is time-consuming. Furthermore, a large number of samples are required to train CNN, nevertheless, it is expensive to obtain enough training samples from HSIs. In this paper, we propose a novel classification approach based on deep forest. To reduce the dimension of hyperspectral data, principal component analysis (PCA) is performed during the pre-processing. In contrast to the CNN, our method has fewer hyper-parameters and faster training speed. To the best of our knowledge, this is among the first deep forest-based hyperspectral spectral information classification. Extensive experiments are conducted on two real-world HSI datasets to show the proposed method is significantly superior to the state-of-the-art methods.

关键词： Forestry Hyperspectral imaging Training Principal component analysis Vegetation Radio frequency

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An improved tiny SLAM method for simultaneous localization and mapping 5

An improved tiny SLAM method for simultaneous localization a...

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5th International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2017

作者： Li, Dan-Yun Liu, Cong-Jun Liu, Zhen-Tao Feng, Zhi-Yong School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Hubei Key Laboratory of Advanced Technology of Automotive Parts Wuhan University of Technology Wuhan430070 China

TinySLAM algorithm is a simple 2D laser SLAM algorithm. However, in practical applications, it has higher error rate of mapping because of its simple filter. In this paper, an improved TinySLAM algorithm is proposed for simultaneous location and mapping. By adding a simple filter before the Monte Carlo simulation and then fusing the information from the odometer, the error in the positioning process can be reduced. Moreover, the introduced hybrid map cell model that can be compatible with ROS system, improves the response to dynamic obstacles, and reduces the mapping error rate further. Simulation using ROS system and Stage software is performed, from which the results show that the proposal has good effects comparing with TinySLAM, and the error rate is reduced so that the map built is closer to the actual environment.

关键词： Mapping

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Distributed dynamic modeling and monitoring for large-scale industrial processes under closed-loop control

arXiv

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arXiv 2018年

作者： Li, Wenqing Zhao, Chunhui Huang, Biao State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Chemical and Materials Engineering University of Alberta EdmontonABT6G-2V4 Canada

For large-scale industrial processes under closed-loop control, process dynamics directly resulting from control action are typical characteristics and may show different behaviors between real faults and normal changes of operating conditions. However, conventional distributed monitoring approaches do not consider the closed-loop control mechanism and only explore static characteristics, which thus are incapable of distinguishing between real process faults and nominal changes of operating conditions, leading to unnecessary alarms. In this regard, this paper proposes a distributed monitoring method for closed-loop industrial processes by concurrently exploring static and dynamic characteristics. First, the large-scale closed-loop process is decomposed into several subsystems by developing a sparse slow feature analysis (SSFA) algorithm which capture changes of both static and dynamic information. Second, distributed models are developed to separately capture static and dynamic characteristics from the local and global aspects. Based on the distributed monitoring system, a two-level monitoring strategy is proposed to check different influences on process characteristics resulting from changes of the operating conditions and control action, and thus the two changes can be well distinguished from each other. Case studies are conducted based on both benchmark data and real industrial process data to illustrate the effectiveness of the proposed method. Copyright © 2018, The Authors. All rights reserved.

关键词： Process monitoring

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Sinter Product Rate Forecasting Based on T-S Fuzzy Model 36

Sinter Product Rate Forecasting Based on T-S Fuzzy Model

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第36届中国控制会议

作者： Qi Lei GaiWen Zhao Xin Chen Min Wu School of Information Science and Engineering Central South University School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Through the analysis of sintering process and the relationship between sintering thermal state and sinter product rate, this paper determines the key factors influencing the sinter product rate, and proposes a method of sinter product rate forecasting based on T-S fuzzy model. Based on the extraction of the characteristic parameters of the thermal state of sintering process, the input of the model is determined. Then, the antecedent and the consequent parameters of the forecasting model are identified by the fuzzy c-means(FCM) clustering algorithm and the recursive least squares method(RLS). Finally, the T-S fuzzy model for sinter product rate forecasting is obtained. The proposed forecasting method is of value through the analysis of the forecast ing results. The forecasting results are also compared with the support vector machine(SVM) and the back propagation neural network(BPNN) methods. The results show that the proposed T-S fuzzy model can effectively improve the precision of the sinter product rate forecasting.

关键词： Sinter Product Rate Forecasting T-S Fuzzy Model Fuzzy c-means Recursive Least Squares(RLS)

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Research on Image Denoising Method Based on Wavelet Transform

Research on Image Denoising Method Based on Wavelet Transfor...

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Chinese control Conference

作者： JunLei Song MeiJuan Chen Chang Jiang YanXia Huang Qi Liu Yuan Meng WenQin Mo KaiFeng Dong Fang Jin China University of Geosciences Wuhan Hubei CN School of Automation China University of Geosciences Wuhan P. R. China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China

In the process of image acquisition and transmission, the image always generates noise due to internal and external interference. Noise reduces the quality of the image, and makes it difficult for subsequent image processing. Therefore, image denoising is very important in image processing. Wavelet denoising can effectively filter out noise and retain high-frequency information of the image, this method has the characteristics of fast operation speed and has become an important branch of image denoising. Threshold functions commonly used in wavelet threshold denoising include hard threshold function and soft threshold function. The hard threshold function is not continuous as a whole. Although the soft threshold function has good continuity, there is always a constant deviation between the processed coefficient and the original coefficient when the wavelet coefficient is large. In response to these deficiencies, this paper establishes a new improved threshold function based on traditional soft and hard threshold functions. By processing the thresholds of wavelet coefficients, a reasonable balance between smoothing and edge oscillations can be achieved after image denoising. The improved threshold function not only overcomes the shortcomings of the soft and hard threshold functions, but also provides more flexibility in the processing of image noise. Through MATLAB simulation, the denoising effects of the soft, hard threshold functions and the threshold function constructed in this paper are compared in terms of signal-to-noise ratio (SNR) and root mean square error (MSE). The MATLAB simulation results show that compared with the traditional threshold function, the improved threshold function has a higher signal-to-noise ratio (SNR = 26.27709) and a smaller mean square error (MSE = 153.4579), and it has a good noise reduction effect.

关键词： Wavelet coefficients Noise reduction Image denoising Correlation Signal to noise ratio

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Stability and Neimark-Sacker bifurcation analysis for single gene discrete system with delay

Stability and Neimark-Sacker bifurcation analysis for single...

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第37届中国控制会议

作者： Feng Liu Qicheng Mei Fenglan Sun Xinmei Wang Hua O Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Research Center of System Theory and Application Chongqing University of Posts and Telecommunications Department of Mechanical Engineering Boston University

The network structure and functional properties of gene regulatory system and their relationships are an important research field in systems *** this paper,a new improved model is proposed based on the study of gene expression *** model takes into account the effect of protein concentration on the gene expression,so as to obtain a new bifurcation point and improve the performance of the *** validity of the model is verified by theoretical analysis and data simulation.

关键词： Stability Neimark-Sacker bifurcation single gene discrete system delay

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Development of A Customizable Real-time Monitoring System for Networked control systems

Development of A Customizable Real-time Monitoring System fo...

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Chinese control Conference

作者： Haoran Tan Zhiwu Huang Min Wu School of Information Science and Engineering Central South University Changsha P. R. China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan P. R. China

The design and implementation of a monitoring system for networked control systems (NCSs) are introduced in this paper. The monitoring system is developed in the .NET framework using C# according to the C/S architecture which allows the user to monitor network nodes without geographical limitations. The widgets used to display come from the National Instruments (NI) suit and are integrated in the system by reconstructing it. The user is able to design a monitoring interface freely by creating and customizing widgets dynamically. During the monitoring, the display value of the widget is synchronized with parameters and signals of NCSs through receiving data asynchronously from network notes. In particular, all elements of the matrix widely used in NCSs are supported for monitoring. The functionality and feasibility of the designed monitoring system are demonstrated via a networked control experiment. In addition, the saved data can be used in data driven control and model identification.

关键词： Monitoring Graphical user interfaces control systems Communication channels Mice Protocols Real-time systems

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Aeromagnetic compensation of Rotor UAV Based on Least Squares

Aeromagnetic compensation of Rotor UAV Based on Least Square...

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第37届中国控制会议

作者： Han Li Jian Ge Haobin Dong Xiangyu Qiu Wang Luo Huan Liu Zhiwen Yuan Jun Zhu Haiyang Zhang School of Automation China University of Geosciences School of Automation China University of Geosciences Wuhan Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Institute of Geophysics & Geomatics China University of GeosciencesWuhan

Aeromagnetic survey is widely used in geophysical exploration because of large exploration range and little limitations on geographical environment. Aiming at the problem using manned aircraft in aeromagnetic survey, an aeromagnetic system of rotor unmanned aerial vehicle(UAV) based on Overhauser sensor is established. It can carry out high-precision geomagnetic measurement with small magnetic interference and omidirection. Firstly, the magnetic interference of rotor UAV is analyzed and the mathematical model is established for software compensation. Next, aeromagnetic magnetometer based on Overhauser sensor is developed. Finally, the least squares is used to estimate the coefficients. The necessity and superiority of allowing for the eddy-current magnetic field is verified by comparing the fitting results. Moreover, the flight test was carried out and the results showed that the improvement ratio was 6.86. The compensation effect of magnetic interference is verified and magnetic anomaly signal is extracted successfully.

关键词： aeromagnetic compensation Overhauser sensor rotor unmanned aerial vehicle

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