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2022 Chinese automation Congress, CAC 2022

作者： Hu, Shuaikang Lu, Chengda Wu, Min He, Zhaoqing Song, Haitao Li, Wangnian School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Xi’an Research Institute Co. Ltd. China Coal Technology and Engineering Group Xi’an710077 China

ISBN: (纸本)9781665465335

In this paper, a fuzzy PID (Proportional Integral Derivative) controller is introduced to suppress the stick-slip vibration present in the drilling process. First, the dynamical model of stick-slip vibration is composed of the multi-DOF (Degree-Of-Freedom) drill-string model and the Karnopp model describing the interaction of the drill bit with the rock. Then, stability analysis is made for the initial PID parameters of our controller. To suppress the stick-slip vibration and at the same time mitigate the effects of the stratigraphic environment variation on the control performance, the fuzzy adaptive algorithm is chosen as the method of optimization controller parameters. From the experimental results, it is clear that our controller has good control performance in the complex and changing stratigraphic environment. © 2022 IEEE.

关键词： controllers

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Preassigned-Time Stabilization of Memristive Chaotic Circuit via Switching control

Preassigned-Time Stabilization of Memristive Chaotic Circuit...

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Neuromorphic Computing (ICNC), International Conference on

作者： Qiming Wang Leimin Wang Wenzhao Qin School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Department of Mathematics and Information Engineering Dongchang College of Liaocheng University Liaocheng China

ISBN: (数字)9798331508661

ISBN: (纸本)9798331508678

In this paper, we propose a 3D memristive chaotic circuit, in which both its dynamical behaviors and the preassigned-time stability are analyzed. First, we design a chaotic circuit utilizing the KNOWM memristor model, and confirm the presence of chaos through phase portrait. Subsequently, we develop a switching controller, which successfully achieves the preassigned-time stability of the memristive chaotic circuit. Ultimately, the validity of our theoretical findings is substantiated through rigorous numerical simulations.

关键词： Three-dimensional displays Memristors Switches control systems Stability analysis Circuit stability Numerical models Integrated circuit modeling Numerical stability Switching circuits

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Stability analysis of systems with two additive time-varying delay components via the zero-valued equations 48

Stability analysis of systems with two additive time-varying...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Liu, Meng He, Yong Jiang, Lin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Liverpool Department of Electrical Engineering & Electronics LiverpoolL69 3GJ United Kingdom

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

In the case of introducing the double integral state into the augmented vector, the time-varying delay square terms in the derivative of the Lyapunov-Krasovskii functional (LKF) usually needs to be treated with some negative-determination lemmas in the existing literatures, which are only sufficient conditions and are conservative to some extent. In this work, by introducing some new augmented variables, some zero-valued equations are proposed to avoid the appearance of these time-varying delay square terms, which have great potential to reduce the conservatism. Then, a stability result in terms of linear matrix inequalities is derived via the presented zero-valued equations. Finally, a representative example is provided to testify the usefulness and meliority of the raised stability criterion. © 2022 IEEE.

关键词： Additives

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Improving Disturbance-Rejection Performance Using Combination of Sliding-Mode control and Equivalent-Input-Disturbance Approach 48

Improving Disturbance-Rejection Performance Using Combinatio...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Wang, Zewen She, Jinhua Sato, Daiki School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China Kanagawa Yokohama226-8503 Japan Tokyo University of Technology School of Engineering Tokyo Hachioji192-0982 Japan

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

This paper combines the equivalent-input-disturbance (EID) approach with the sliding-mode control (SMC) approach that improves disturbance-rejection performance. A novel equivalent-input-disturbance (NEID) approach is presented, which considers the disturbance estimation in the state observer. A sliding surface is designed based on the internal model principle, which is called internal-model sliding-mode control (IMSMC). A stability condition is devised for the SMC-EID-based control system. The parameters are designed based on the stability condition. Simulation results show the validity of the NEID approach. © 2022 IEEE.

关键词： Sliding mode control

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A new result for H∞ performance analysis of sampled-data systems via looped-functionals

A new result for H∞ performance analysis of sampled-data sy...

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第41届中国控制会议

作者： Du Xiong Wen-Hu Chen Yong-He Lao Yu-Long Fan Chuan-Ke Zhang 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 is concerned with H performance analysis of aperiodic sampled-data systems by employing the input delay ***,a novel augmented looped-functional（ALF） is presented under the double-side looped-functional technique,which considers coupled relationships among state vectors more fully than the current ***,by using the BesselLegendre inequality to estimate the derivative of the ALF,a stability criterion is derived in the form of linear matrix ***,a numerical example demonstrates the effectiveness and the advantages of the proposed criterion by comparing it with the existing ones.

关键词： Aperiodic sampled-data systems Stability analysis Input delay approach H_∞ performance Bessel-Legendre inequality

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Surface Defect Detection of Sanitary Ceramic Product Utilizing High-resolution Image on Two Different Scales

Surface Defect Detection of Sanitary Ceramic Product Utilizi...

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第34届中国控制与决策会议

作者： Xing-ao Wang Jianqi An Yisheng Mei 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

Surface defect detection of sanitary ceramic products is an important part of the production *** deep learning method is the mainstream research direction in the field of defect *** there are many small defects on the surface of sanitary ceramic products,it is an effective means to use a high-resolution camera to obtain *** detection speed of high-resolution pictures and the interference of background are the difficult problems in ***,this paper designs a two-scale detection framework to detect and locate defects of sanitary ceramics utilizing high-resolution *** two-scale detection framework speeds up the detection of high-resolution images and weakens the interference of the background by dividing the defect detection task into two parts,a workpiece region recognition task on large scale and a defect detection task on small *** experiments show that the two-scale detection method has a better detection speed and accuracy rate compared with the single-scale method,which proves the superiority of the proposed method.

关键词： Defect detection Two-scale detection Deep learning

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Stability and bifurcation control of fractional-order coupled Hindmarsh-Rose neural networks

Stability and bifurcation control of fractional-order couple...

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第42届中国控制会议

作者： Feng Liu Feifan Zhou Wei Wang Gang Cai Hua O Wang Xiuqin Yang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mechanical Engineering Boston University School of Education Minzu University of China

This article investigates a fractional-order coupled Hindmarsh-Rose neural networks ***,the existence and stability of an equilibrium point in the system are ***,the periodic bifurcation behavior of the system on a twoparameter plane is studied,and numerical simulations show the existence of both non-chaotic and chaotic plus periodic bifurcation behavior on the two-parameter ***,a feedback controller was designed to stabilize the bifurcation point of the delayed system and increase the stable range of the system.

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Fault diagnosis of drilling process based on multi-scale decomposition and decision fusion

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IFAC-PapersOnLine 2023年第2期56卷 8079-8084页

作者： Aoxue Yang Min Wu Wanke Yu Jie Hu Chengda Lu Yosuke Nakanishi School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China Graduate School of Environment and Energy Engineering Waseda University Tokyo 169-8555 Japan

Data-driven fault diagnosis methods have been widely applied at present. In the drilling process, there usually exists multiple failure modes resulting in the multi-scale of drilling fault data, which would bring challenges for the data-driven methods application in drilling. By considering the characteristics of multi-scale and multivariate, an original scheme based on mode decomposition and decision fusion is proposed for fault diagnosis of drilling process. Firstly, the raw data are decomposed and reconstructed into multiple groups of series. Then, for each group, the diagnosis model is established using the convolutional neural network (CNN), and several diagnostic results are obtained. Finally, all diagnostic results are fused by the Dempster-Shafer (D-S) evidence theory, and the fused result is taken as the final diagnostic result. The actual data based experiments illustrate the effectiveness of proposed method for improving the performance of drilling fault diagnosis.

关键词： Fault diagnosis drilling process multivariate variational mode decomposition decision fusion

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Finite-Time Synchronization of Flux-controlled complex-Valued Memristive Neural Networks

Finite-Time Synchronization of Flux-Controlled Complex-Value...

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Neuromorphic Computing (ICNC), International Conference on

作者： Yonghuan Wang Leimin Wang Genping 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 Wuhan China Wuhan Second Ship Design and Research Institute Wuhan China

In this paper, by using the flux-controlled memristor model, the finite-time synchronization problem of delayed complex-valued memristive neural networks (MCNNs) is studied. Firstly, according to the proposed memristor model, we model the MCNNs as continuous systems on voltage-flux-time $(\wp, \varpi, t)$ domain. Then, we design a class of approaches to realize state synchronization between the drive and response systems, and the corresponding synchronization conditions are achieved. Finally, the effectiveness of results is illustrated with the simulations.

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Large-Scale Hyperspectral Image Clustering Using Contrastive Learning

Large-Scale Hyperspectral Image Clustering Using Contrastive...

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2021 International Conference on Information and Knowledge Management Workshops, CIKMW 2021

作者： Cai, Yaoming Liu, Yan Zhang, Zijia Cai, Zhihua Liu, Xiaobo School of Computer Science China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China

Unsupervised hyperspectral image (HSI) classification is an important but challenging task in the hyperspectral processing community. Despite great success, previous HSI clustering approaches belong to offline clustering which is often performed in a transductive scheme, thus failing to generalize to large-scale and unseen scenes. In this paper, we propose an online and deep clustering model for large-scale HSI clustering, termed spectral-spatial contrastive clustering (SSCC). Specifically, SSCC performs contrastive learning based on a series of semantic-preserving spectral-spatial augmentation to simultaneously maximize the intra-class agreement and inter-class variation, which are implemented by an instance-level contrastive loss and a cluster-level contrastive loss, respectively. The SSCC model is trained in an end-to-end fashion with minibatch, allowing it to efficiently handle large-scale HSIs. We assess the performance of SSCC on real HSI and show that SSCC significantly advances the state-of-the-art results with 8.41% improvement on accuracy. © 2021 CEUR-WS. All rights reserved.

关键词： Spectroscopy

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