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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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Smart Infrared Temperature Measurement System Based On Elastic Compute Service Platform

Smart Infrared Temperature Measurement System Based On Elast...

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2021 China automation Congress, CAC 2021

作者： Li, Yongbo Yuan, Li Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665426473

In the fight against the novel coronavirus, this paper designs a smart infrared temperature measurement system based on the Elastic Compute Service platform. In the perceptual layer part of the Internet of Things(IoT), the system uses infrared temperature sensors to quickly collect the temperature of the forehead or arm of the human body and Uses the MCU to automatically transmits the measured data to the Elastic Compute Service through the WiFi module. In the network layer part of the Internet of Things,the data written into the database of the Elastic Compute Service through the program deployed on the Elastic Compute Service. In the application layer of the Internet of Things, the remote management terminal monitors the collected body temperature data in real-time and provides quick warnings. Finally, the User can log in to the applet on his mobile phone to quickly and easily obtain personal information. © 2021 IEEE

关键词： Internet of things

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A Co-regularization Facial Emotion Recognition Based on Multi-Task Facial Action Unit Recognition 41

A Co-regularization Facial Emotion Recognition Based on Mult...

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第41届中国控制会议

作者： Chinonso Paschal Udeh Luefeng Chen Sheng Du Min Li Min Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Facial emotion recognition helps feed the growth of the future artificial intelligence with the development of emotion recognition,learning,and analysis of different angles of a human face and head *** worlds recent pandemic gave rise to the rapid installment of facial recognition for fewer applications,while emotion recognition is still within the experimental *** current challenges encountered with facial emotion recognition(FER) are the difference between background *** todays world shows us that humans soon need robotics in the most significant role of human perception,attention,memory,decision-making,and human-robot interaction(HRI) needs *** merging the head pose as a combination towards the FER to boost the robustness in understanding emotions using the convolutional neural networks(CNN).The stochastic gradient descent with a comprehensive model is adopted by applying multi-task learning capable of implicit parallelism,inherent and better global optimizer in finding better network *** executing a multi-task learning model using two independent datasets,the experiment with the FER and head pose learning multi-views co-regularization frameworks were subsequently merged with validation accuracy.

关键词： head pose facial expression convolution neural network deep learning emotion recognition

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An online drilling rate of penetration(ROP) optimization method 41

An online drilling rate of penetration(ROP) optimization met...

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第41届中国控制会议

作者： Tuo Wang Chao Gan Weihua Cao School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Drilling rate of penetration(ROP) optimization is crucial due to its vital role in increasing the drilling efficiency and decreasing the non-productive *** existing methods seldom pay attention to updating model parameter during drilling,which is actually important for ROP optimization under dynamical and uncertain downhole *** this paper,an online drilling ROP optimization method is proposed via three stages(drilling data pre-processing,online ROP modelling and online optimal operational parameters optimization).In the first stage,drilling data is pre-processed by resampling and Savitzky-Golay *** this,support vector regression and moving-window strategy are introduced together to establish an online ROP model in the next ***,particle swarm optimization algorithm is applied in the online ROP optimization framework to obtain the optimal operational parameters in the last *** results indicated the effectiveness of the proposed method.

关键词： Rate of penetration Drilling optimization Online optimization Moving-window strategy

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Speed and Accuracy Tradeoff for LiDAR Data Based Road Boundary Detection

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IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1210-1220页

作者： Guojun Wang Jian Wu Rui He Bin Tian State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the Qingdao Academy of Intelligent Industries ShandongChina

Road boundary detection is essential for autonomous vehicle localization and decision-making,especially under GPS signal loss and lane *** road boundary detection in structural environments,obstacle occlusions and large road curvature are two significant ***,an effective and fast solution for these problems has remained *** solve these problems,a speed and accuracy tradeoff method for LiDAR-based road boundary detection in structured environments is *** proposed method consists of three main stages:1)a multi-feature based method is applied to extract feature points;2)a road-segmentation-line-based method is proposed for classifying left and right feature points;3)an iterative Gaussian Process Regression(GPR)is employed for filtering out false points and extracting boundary *** demonstrate the effectiveness of the proposed method,KITTI datasets is used for comprehensive experiments,and the performance of our approach is tested under different road *** experiments show the roadsegmentation-line-based method can classify left,and right feature points on structured curved roads,and the proposed iterative Gaussian Process Regression can extract road boundary points on varied road shapes and traffic ***,the proposed road boundary detection method can achieve real-time performance with an average of 70.5 ms per frame.

关键词： 3D-LiDAR autonomous vehicle object detection point cloud road boundary

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A zeroth-order algorithm for distributed optimization with stochastic stripe observations

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Science China(Information Sciences) 2023年第9期66卷 297-298页

作者： Yinghui WANG Xianlin ZENG Wenxiao ZHAO Yiguang HONG School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Department of Control Science and Engineering Tongji University

Recent years have seen a rising interest in distributed optimization problems because of their widespread applications in power grids, multi-robot control, and regression *** the last few decades, many distributed algorithms have been developed for tackling distributed optimization problems. In these algorithms, agents over the network only have access to their own local functions and exchange information with their neighbors.

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Dynamic constrained multi-objective evolutionary algorithms with a novel selection strategy for constrained optimization 18

Dynamic constrained multi-objective evolutionary algorithms ...

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2018 Genetic and Evolutionary Computation Conference, GECCO 2018

作者： Jiao, Ruwang Li, Changhe Zeng, Sanyou Jiang, Yuhong China University of Geosciences Wuhan China China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9781450357647

The recently proposed dynamic constrained multi-objective evolutionary algorithm (DCMOEA) is effective to handle constrained optimization problems (COPs). However, one drawback of DCMOEA is it mainly searches the global optimum from infeasible regions, which may result in the bias against feasible solutions. Then the useful information about the optimal direction of feasible regions is not fully used. To overcome this defect, this paper proposes a novel selection strategy based on DCMOEA framework, called NSDCMOEA to solve COPs. The performance of NSDCMOEA is evaluated using a set of benchmark suites. Experimental results validate that the proposed method is better than or very competitive to five state-of-the-art algorithms. © 2018 Copyright held by the owner/author(s).

关键词： Constrained optimization

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A repetitive-control method based on sliding-mode control for nonlinear systems with external disturbances 41

A repetitive-control method based on sliding-mode control fo...

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第41届中国控制会议

作者： Yibing Wang Min Wu Manli Zhang Luefeng Chen Jinhua She School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Engineering Tokyo University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper presents a two-dimensional(2 D) repetitive-control method based on sliding-mode control for a nonlinear system with external *** a sliding-mode controller has a powerful ability to handle nonlinearity and external disturbances during the sliding motion,the reference-tracking and disturbance-suppression problems of the original nonlinear system are decomposed into two subproblems:reference tracking for a linear system and disturbance suppression for a nonlinear modified-repetitive control system(MRCS) with external *** the first one,a repetitive controller constructed with two positive time-delay loops is employed to increase the flexibility of the system design and guarantee high accuracy reference tracking.A continuous-discrete 2 D model of the linear MRCS is established to describe continuous control and discrete learning by using the 2 D property of repetitive control.A sufficient stability condition,in which three parameters are used to adjust control and learning,is given to guarantee the stability of the linear *** design of the system is transformed into parameter *** optimization algorithm is used to yield the optimal *** the other,a sliding-mode controller is developed to eliminate the effect of both nonlinearity and external disturbances on the system.A linear-matrix-inequality(LMI)-based sufficient stability condition is derived to guarantee the stability of the sliding *** condition is used to design the sliding-mode controller,which has a simple structure and does not require any specific information of nonlinearity and external ***,a numerical example and a comparison demonstrate the validity and advantage of the presented method.

关键词： Repetitive control sliding-mode control two-dimensional model

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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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From Parallel Plants to Smart Plants:intelligent control and Management for Plant Growth

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IEEE/CAA Journal of Automatica Sinica 2017年第2期4卷 161-166页

作者： Mengzhen Kang Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences (SKL-MCCSCASIA) Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology IEEE State Key Laboratory of Management and Control for Complex Systems (SKL-MCCS) Institute of AutomationChinese Academy of Sciences (CASIA) School of Computer and Control Engineering University of Chinese Academy of Sciences Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology

Precision management of agricultural systems, aiming at optimizing profitability, productivity and sustainability, comprises a set of technologies including sensors, information systems, and informed management, etc. Expert systems are expected to aid farmers in plant management or environment control, but they are mostly based on the offline and static information, deviated from the actual situation. Parallel management, achieved by virtual/artificial agricultural system, computational experiment and parallel execution, provides a generic framework of solution for online decision support. In this paper, we present the three steps toward the parallel management of plant: growth description U+0028 the crop model U+0029, prediction, and prescription. This approach can update the expert system by adding learning ability and the adaption of knowledge database according to the descriptive and predictive model. The possibilities of passing the knowledge of experienced farmers to younger generation, as well as the application to the parallel breeding of plant through such system, are discussed. © 2017 Chinese Association of automation.

关键词： Agriculture Artificial intelligence Decision support systems Expert systems Sustainable development

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