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Asian control Conference

作者： Ying Feng Min Wu Xin Chen Luefeng Chen Sheng Du Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9781728102634

Continuous casting is an important process in iron and steel production. In continuous casting process, in order to improve the control precision of mould level under steady-state working condition, and to suppress large fluctuation under non-steady-state working condition, a fuzzy PID controller is designed based on working condition identification. First, a mechanism model of mould level is established. After analyzing the characteristics of the model, the continuous casting process is divided into different working conditions. Then, fuzzy rules are designed to regulate the parameters of PID. Finally, results in industrial site show both of the control precision of mould level under steady-state working condition and the anti-interference ability under non-steady-state working condition are improved, indicating that the proposed method is effective.

关键词： Employee welfare Casting Process control Steel Steady-state Slabs Level control

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Analysis and circuit implementation of a new fourth-order multi-wing chaotic system based on memristors

Analysis and circuit implementation of a new fourth-order mu...

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Chinese Automation Congress (CAC)

作者： Lei Jia Xiaowei Jiang Xianhe Zhang Ming Chi Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Geodetection Technology Ministry of Education School of Automation China University of Geosciences Wuhan P. R. China School of Electrical Engineering and Automation Hubei Normal University Huangshi P. R. China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan P. R. China

ISBN: (纸本)9781665426480

In this paper, a new fourth-orders memristor chaotic system is obtained by introducing a smooth memristor model as the feedback term based on the modified three-orders chaotic system. The system can generate double-wing, four-wing chaos or hyperchaos for different parameters and initial conditions. Through the analysis of Lyapunov exponent and other dynamics, we can see that the system has complex chaotic, hyperchaotic, and continuous chaotic. Other dynamical behaviors such as multi-stability and extreme multi-stability are found by comparing phase and bifurcation diagrams, and equilibrium point calculations. Finally, the chaotic behavior is successfully verified by circuit simulation.

关键词： Chaos Automation Circuit simulation Buildings Memristors Bifurcation Encryption

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Youla Parameterization Based control Performance Degradation Online Recovery of Single Inverter control systems in Microgrids: a PnP Approach

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IFAC-PapersOnLine 2020年第2期53卷 12080-12085页

作者： Y. Liu C. Hu H. Lu S.X. Ding L. Li X. Peng Y. Wang Institute for Automatic Control and Complex Systems University of Duisburg-Essen Bismarkstr. 81 BB 47057 Duisburg Germany College of Electrical and Control Engineering North China University of Technology 100144 Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing China Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology200237 Shanghai China

In an inverter control system of smart microgrids, the control performance degradation due to load fluctuations, unbalanced loads and other factors, is one of the considerable factors affecting the output power quality. In this paper, a plug-and-play (PnP) technology based on Youla parameterization is proposed to achieve system performance recovery without modifying the existing controller. By ‘plugging-in’ a residual generator and a compensator, a dynamic feed-back of residual signals is embedded into the original inverter control system. In order to realize PnP, an online parameter estimation scheme of the compensator is developed. Finally, an inverter control system is applied to show the effectiveness of the proposed approach.

关键词： Youla parameterization performance degradation online recovery power quality microgrids

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Design of audio to image cross-modal learning and generation based on single-layer CoPt spin-orbit torque devices

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Journal of Magnetism and Magnetic Materials 2025年 629卷

作者： Qian, Likun Yang, Liu Zuo, Chao Tao, Ying Li, Wendi Jin, Fang Li, Huihui Dong, Kaifeng School of Future Technology 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 Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Wuhan Second Ship Design and Research Institute Wuhan430064 China Beijing Superstring Academy of Memory Technology Beijing100176 China

Despite remarkable achievements in neural network applications using spin–orbit torque (SOT) devices, current research predominantly focuses on unimodal classification tasks, while cross-modal learning tasks often suffer from suboptimal generation quality. To address this limitation, we employ generative adversarial networks (GANs) based on CoPt-SOT to achieve cross-modal learning and generation from speech to handwritten digit images. Initially, we explore the field-free switching characteristics of single-layer CoPt devices, developing spin-based implementations of Scaled Rectified Linear Unit (SReLu), Sigmoid, and Tanh neuronal functions. Simultaneously, we leverage the nonvolatile multistate characteristics of CoPt devices to realize excitatory-inhibitory synaptic plasticity. Subsequently, for the first time, we construct half-spin and full-spin GAN networks using these spin-based neurons and synapses, enabling cross-modal learning and generation between speech and image domains. Finally, we evaluate the performance of these networks through handwritten digit recognition tasks, achieving impressive recognition accuracies of 93.78 % and 88.61 % for half-spin and full-spin implementations, respectively. Notably, this work overcomes the existing bottleneck in SOT device applications, which have been largely confined to unimodal classification tasks, and demonstrates significant potential for expanding the scope of SOT-based technologies. © 2025 Elsevier B.V.

关键词： Generative adversarial networks

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Multiscale Infrared and Visible Image Fusion Based on Phase Congruency and Saliency

Multiscale Infrared and Visible Image Fusion Based on Phase ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Jun Chen Kangle Wu Linbo Luo Xiaoqiang Chen Yue Gu Xin Tian School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Mechanical Engineering and Electronic Information China University of Geosciences Electronic Information School Wuhan University

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

In this paper, in order to enhance the infrared target in infrared image and retain the edge and detail information in visible image, we propose a multi-scale decomposition fusion method based on phase congruency and saliency. In this method, the Laplacian pyramid is first used to decompose the source image into detail layers and base layers. Secondly, we use a method based on phase congruency for the fusion of detail layers. Thirdly, for the base layer, we decompose it into saliency map and residual map. The “max absolute” rule and “averag” rule are adopted for the fusion of saliency map and residual map, then the fused saliency map and residual map are added to attain the fused base image. Finally, we use the inverse transform of Laplacian pyramid to reconstruct the fused image. The experimental results show that the proposed method have better fusion effect than other methods. What's outstanding is that the infrared targets in the fused image are enhanced and abundant edges are preserved.

关键词： Image fusion Image edge detection Laplace equations Image reconstruction Discrete wavelet transforms Target recognition Fuses

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Logic-based switching finite-time stabilization with applications in mechanical systems

arXiv

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arXiv 2020年

作者： Zheng, Shiqi Wang, Shihao Chen, Xiang Xie, Yuanlong The School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China The School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China

This paper investigates the finite time stabilization problem for a class of nonlinear systems with unknown control directions and unstructured uncertainties. The unstructured uncertainties indicate that not only the parameters but also the structure of the system nonlinearities are uncertain. A new adaptive control method is proposed for the considered system. Logic-based switching rule is utilized to tune the controller parameters online to stabilize the system in finite time. Different from the existing adaptive controllers for structured/parametric uncertainties, a new switching barrier Lyapunov method and supervisory functions are introduced to overcome the obstacles caused by unstructured uncertainties and unknown control directions. Both simulations and experiments are conducted on mechatronic systems to verify the effectiveness of the proposed methods. © 2020, CC BY.

关键词： Lyapunov methods

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An intelligent control Scheme for Burn-Through Point to Carbon Efficiency optimization in Iron Ore Sintering Process

An Intelligent Control Scheme for Burn-Through Point to Carb...

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第37届中国控制会议

作者： Sheng Du Min Wu Jinhua She School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

The sintering process is an important step of preparing raw material for iron and steel smelting. It is a series of complex physico-chemical changes with high energy consumption, high pollution and large CO emissions. How to reduce carbon consumption while ensuring the quality and yield of sinter ore are the problems to be solved urgently. In this paper,An intelligent control scheme for burn-through point(BTP) to carbon efficiency optimization in iron ore sintering process is presented. The comprehensive coke ratio is employed as a measure of carbon efficiency;and the BTP, a measure of the stability of the sintering process. First, a model is established to predict the comprehensive coke ratio using a back propagation neural network, and the carbon efficiency is optimized using the particle swarm optimization algorithm. This yields an optimal strand velocity. Then, the control of the BTP is taken into consideration using an expert-fuzzy control strategy. This yields another strand velocity. Finally, these two kinds of strand velocity are integrated using the fuzzy satisfaction method to produce a control input for the strand velocity. It not only improves the carbon efficiency, but also ensures the stable running of the sintering process. Part of the strategy was tested in an actual plant, and the results show the effectiveness of the scheme.

关键词： Sintering process Carbon efficiency optimization Burn-through point intelligent control

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An IoT Edge Computing System Architecture and its Application

An IoT Edge Computing System Architecture and its Applicatio...

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IEEE International Conference on Networking, Sensing and control

作者： Shichao Chen Qijie Li Hua Zhang Fenghua Zhu Gang Xiong Ying Tang Macau University of Science and Technology The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Macau China Beijing University of Technology The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Beijing Aerospace Smart Manufacturing Technology Development Co. Ltd Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The Engineering Research Center of Intelligent Systems and Technology Institute of Automation and Cloud Computing Center Chinese Academy of Sciences Beijing China Rowan University Glassboro NJ USA Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China

ISBN: (数字)9781728168555

ISBN: (纸本)9781728168562

As the number of devices connected to the Internet of things (IoT) surges, the amount of data explodes. Therefore it not only increases the bandwidth load of data transmission but also aggravates the computing and storage load of a cloud platform. At the same time, the traditional computing paradigm centered on cloud computing cannot meet the real-time requirements in many application scenarios. The emergence of edge computing can solve the problems of realtime data processing and network bandwidth occupation in the current IoT scene. In this paper, according to the characteristics of IoT, such as fragmented data, heterogeneous network, and limited energy consumption, the architecture of an IoT edge computing system is constructed to suit better an IoT scene. In addition, the application of edge computing key technologies such as virtualization, edge intelligence, computing offload, collaborative scheduling and micro-services in resource-constrained IoT scenarios is analyzed in detail. Finally, the functions and application of energy consumption monitoring and optimization to a central air-conditioning system are analyzed and summarized, which is a typical application of edge computing in the context of the IoT.

关键词： Energy consumption Processor scheduling Computer architecture Internet of Things optimization Monitoring Edge computing

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A Collision-Free Person-Following Approach Based on Path Planning

A Collision-Free Person-Following Approach Based on Path Pla...

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IEEE International Conference on Mechatronics and Automation

作者： Lei Pang Zhiqiang Cao Junzhi Yu Weimin Zhang Xuechao Chen State Key Laboratory of Management and Control for Complex Systems Institute of Automation School of Artificial Intelligence University of Chinese Academy of Sciences BIC-ESAT College of Engineering Peking University Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

Person following is a crucial capability for mobile robots in tasks of human assistance and cooperation. In this paper, a person-following approach based on path planning is proposed for mobile robots, which takes person following and obstacle avoidance into account in a unified framework. The proposed approach is comprised of a sensing module and a planning module. The sensing module with a camera and a 3D LiDAR is employed to locate the target person and perceive obstacles. For the planning module, the combination of global planner and local planner effectively outputs collision-free paths and control commands for a mobile robot to keep following the target person. Experiments were conducted to evaluate the performance of the proposed approach.

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Feature Aggregation Attention Network for Single Image Dehazing

Feature Aggregation Attention Network for Single Image Dehaz...

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IEEE International Conference on Image Processing

作者： Lan Yan Wenbo Zheng Chao Gou Fei-Yue Wang The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Software Engineering Xi’an Jiaotong University Xi’an China School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou China

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

Due to its ill-posed nature, single image dehazing is a challenging problem. In this paper, we propose an end-to-end feature aggregation attention network (FAAN) for single image dehazing. It incorporates the idea of attention mechanism and residual learning and can adaptively aggregate different level features. In particular, in the proposed FANN, we design a novel block structure consisting of feature attention module, smoothed dilated convolution and local residual learning. The local residual learning allows the less useful information to be bypassed through multiple skip connections. The feature attention module is designed to assign more weight to important features. The smoothed dilated convolution is adopted to enlarge the receptive field without the negative influence of gridding artifacts. The experiments on the RESIDE dataset show that the proposed approach acquires state-of-the-art performance in both qualitative and quantitative measures.

关键词： Convolution Atmospheric modeling Kernel Image color analysis Task analysis Training

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