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第40届中国控制会议

作者： Haitao Jian Shiqi Zheng Chenghao Zhao Haiming Li Shihao Wang 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

This paper focuses on the control problem of a class of random teleoperation systems. To overcome the difficulties caused by the random environment, a new adaptive sliding mode control method for random teleoperation system is *** with the previous work, the model in this paper is built by random differential equations. In addition, different time-varying delays are introduced between the two communication channels. Furthermore, a new design scheme for random teleoperation system with varying-time delay is proposed. Radial Basis Function neural network（RBFNN） is introduced to deal with the unknown nonlinearities of the system. Using this method, good position tracking performance and stability can be obtained.

关键词： Adaptive control Sliding mode Teleoperation Random Lagrangian system Time-varying delay

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Fault Detection Based on Canonical Correlation Analysis with Rank Constrained Optimization

Fault Detection Based on Canonical Correlation Analysis with...

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第40届中国控制会议

作者： Yuhan Zhang Xianchao Xiu Ying Yang Wanquan Liu State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of EngineeringPeking University School of Intelligent Systems Engineering Sun Yat-sen University

Canonical correlation analysis（CCA） has attracted increasing attention in the field of fault detection because it provides an effective way to explore the relationship between the input and output *** paper develops a novel rank constrained CCA（RCCCA） framework,which is the first approach that takes the rank prior information into ***,the rank constrained optimization is able to capture the global structures of variables,and thus improve the performance of fault *** order to solve RCCCA,an alternating minimization algorithm is designed,which aims to preserve the maximum correlation with the low-rank learning.A fault detection residual is then generated,and the test statistic is constructed to determine whether a fault *** RCCCA-based fault detection is finally tested on a numerical example and the Tennessee Eastman benchmark *** results indicate the efficiency and feasibility of the proposed method.

关键词： Fault detection canonical correlation analysis rank constrained optimization alternating minimization algorithm Tennessee Eastman process

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A New Dynamic Event-Triggered Mechanism Based Model Predictive Control for systems with Polytopic Uncertainties

A New Dynamic Event-Triggered Mechanism Based Model Predicti...

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第40届中国控制会议

作者： Fan Wei Xiongbo Wan 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

This paper investigates the problem of model predictive control（MPC） for systems with polytopic uncertainties under the event-triggered communication mechanism. To save network resources, a new dynamic event-triggered mechanism（DETM） is proposed, which contains an adaptive internal dynamic variable（IDV） and a time-varying parameter. A "min-max"optimization problem is put forward to dealing with the MPC problem for systems with polytopic uncertainties. With the aid of a Lyapunov-like function dependent on the IDV of the DETM, an auxiliary optimization problem is devised with constraints in terms of linear matrix inequalities. By solving such an auxiliary optimization problem, sub-optimal feedback gains are obtained which ensure the input-to-state practical stability of the closed-loop system. A numerical example is provided to demonstrate the effectiveness of the devised MPC algorithm.

关键词： Model predictive control dynamic event-triggered mechanism networked systems input-to-state practical stability

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Performance Improvement of TFRC Congestion Control Algorithm in Wireless Network Streaming Media Transmission

Performance Improvement of TFRC Congestion Control Algorithm...

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第40届中国控制会议

作者： Kang Li Yan Yuan Yitao Chen Zhicheng Zhao 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

This paper studies a rate-based TCP-Friendly Rate Control（TFRC） mechanism, which is widely used in multimedia real-time services, and analyzes its basic workflow, throughput model and calculation of key parameters. In order to meet the demand of real-time service for network transmission, the bandwidth-delay product（BDP） is applied to the congestion control of TFRC as the network congestion warning signal, and the improved TFRC algorithm is proposed. The simulation results show that this method can achieve good results in the network transmission of real-time services, and its friendliness and smoothness are improved to a certain extent.

关键词： Real-time multimedia application TFRC Bottleneck bandwidth and round-trip time（BBR） Wireless network

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Detection Method for Overbreak and Underbreak of Tunnel Based on Three-Dimensional Laser Point Clouds

Detection Method for Overbreak and Underbreak of Tunnel Base...

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第32届中国过程控制会议(CPCC2021)

作者： Zhuoxuan Jiang Jianqi An Zhilin Tang Xin Chen Min Wu 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

During the construction of the tunnel excavation with the method of drilling and blasting,overbreak and underbreak occur ***,overbreak and underbreak affect the cost,efficiency,and safety of tunnel *** paper presents a detection method for overbreak and underbreak of tunnels based on three-dimensional laser point ***,this paper obtains point cloud data of a tunnel by a 3 D laser scanner,preprocesses the point cloud data based on Gaussian filter,and extracts midlines of the tunnel based on random sampling consistency(RANSAC) to obtain attitude and trend information of the ***,cross-sections of the tunnel are extracted according to the midline of the ***,the position and value of the overbreak and underbreak are got according to comparing the projections of the cross-sections of the tunnel with a planned extent of the ***,this method was applied to an evaluation of overbreak and underbreak of a tunnel,and the results show that the method in this paper detects overbreak and underbreak easily,quickly,and accurately.

关键词： Overbreak and underbreak three-dimensional laser point cloud

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Electroencephalogram Emotion Recognition Using Variational Modal Decomposition Based Dispersion Entropy Feature Extraction

Electroencephalogram Emotion Recognition Using Variational M...

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第40届中国控制会议

作者： Si-Jun Hu Zhen-Tao Liu Xue-Wen Ding 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

Electroencephalogram（EEG） emotion recognition has gained considerable attention due to its ability to reflect people’s inner emotional states objectively and *** extraction is a critical step in EEG emotion recognition because of non-stationarity and irregularity of EEG signals.A feature extraction method using Variational Modal Decomposition（VMD）to extract Dispersion Entropy（DispEn） is proposed in this *** EEG signal is decomposed into several components,and DispEn of each component is extracted in eight emotion-related *** method was tested on DEAP dataset in which the EEG emotional states are accessed in Valence-Arousal emotional *** emotional states（i.e.,HVHA,HVLA,LVHA,LVLA） are classified by Support Vector Machine（SVM）.The experimental results show that the accuracy of emotion recognition is 77.87%,which demonstrates its effectiveness.

关键词： EEG Emotion recognition VMD Dispersion Entropy Feature Extraction SVM

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A dulcimer keys positioning method based on improved Roberts operator

A dulcimer keys positioning method based on improved Roberts...

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2021 China Automation Congress, CAC 2021

作者： Tang, De Zhang, Ziying Chen, Xin Xiao, Zhe Qin, Mengxi School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China School of Arts and Communication China University of Geosciences Wuhan430074 China

ISBN: (纸本)9781665426473

It is important for the dulcimer robot to obtain the spatial coordinates of the dulcimer phonemes. However, the traditional manual positioning method is both inefficient and does not meet the intelligence requirements of modern robot. A visual positioning method based on improved Roberts operator is proposed in this paper on account of solving these problems, which can obtain the 3D coordinates of the dulcimer keys in a short time. First, an improved Roberts edge detection operator is designed, which fully detects the edge information of the target by transforming the scale. Further, this paper proposes a dulcimer keys positioning method by fusing RGB and depth image information. This method has a better positioning effect for dulcimer keys with complex background and small size. The experimental results show that the visual positioning method proposed in this paper can effectively identify and locate the dulcimer keys, and it has better robustness to the lighting environment. © 2021 IEEE

关键词： Binocular vision

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Design of a prediction and optimization system for plate shape in roller quenching process

Design of a prediction and optimization system for plate sha...

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第40届中国控制会议

作者： Wen Zhang Min Wu Cong Chen Sheng Du Luefeng Chen 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

Plate shape is one of the key quality indices of steel plates after *** is of great significance to realize the prediction and optimization of plate shape for obtaining high quality steel *** paper designs a prediction and optimization system for plate shape in roller quenching ***,the roller quenching process is described in detail,the design objectives are analyzed,and the architecture of the system is ***,the system is designed from four parts:the prediction model of plate shape,the comprehensive evaluation model of plate shape,the intelligent optimization model of operating parameters and the case ***,the prediction and optimization system is applied to the industrial *** results of preliminary tests show that the system improves the quality of plate shape.

关键词： Roller quenching process Plate shape prediction intelligent optimization Case matching

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Learning deep multimodal feature representation with asymmetric multi-layer fusion

arXiv

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arXiv 2021年

作者： Wang, Yikai Sun, Fuchun Lu, Ming Yao, Anbang State Key Lab on Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Cognitive Computing Laboratory Intel Labs China

We propose a compact and effective framework to fuse multimodal features at multiple layers in a single network. The framework consists of two innovative fusion schemes. Firstly, unlike existing multimodal methods that necessitate individual encoders for different modalities, we verify that multimodal features can be learnt within a shared single network by merely maintaining modality-specific batch normalization layers in the encoder, which also enables implicit fusion via joint feature representation learning. Secondly, we propose a bidirectional multi-layer fusion scheme, where multimodal features can be exploited progressively. To take advantage of such scheme, we introduce two asymmetric fusion operations including channel shuffle and pixel shift, which learn different fused features with respect to different fusion directions. These two operations are parameter-free and strengthen the multimodal feature interactions across channels as well as enhance the spatial feature discrimination within channels. We conduct extensive experiments on semantic segmentation and image translation tasks, based on three publicly available datasets covering diverse modalities. Results indicate that our proposed framework is general, compact and is superior to state-of-the-art fusion frameworks. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal encoding

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Multi-condition recognition method based on LSTM＿GRU for heating processes

Multi-condition recognition method based on LSTM＿GRU for he...

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第40届中国控制会议

作者： Qingyi Zhu Weihua Cao Wenshuo Song 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

Aiming at the multi-condition problem of Continuous Annealing Processes(CAP), this paper proposes a new method based on Long Short-Term Memory(LSTM) and Gated Recurrent Unit(GRU) models to identify multiple conditions in ***, this work analyzes the parameters in CAP, selects the key variables that affect the working conditions, and then selects a piece of data in the CAP work process as the training data set to train the constructed LSTMRU neural network. This method realizes the recognition of different working conditions in CAP, which saves training time, simplifies internal *** with the traditional method, this method avoids the recognition error caused by personal experience factors, and the model accuracy has greatly improved.

关键词： Working condition recognition LSTMGRU Metallurgy Process industry CAP

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