检索结果-内蒙古大学图书馆

Chinese control Conference (CCC)

作者： Jiajun Chu Weihua Cao Chao Gan Yulong Yang 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 Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan P. R. China

Deep-sea unmanned exploration equipment is an important tool for exploring and developing the resources in the ocean, and it can survey the deep-sea environment more visually with the help of visual images. However, the complex and variable environment and the low resolution of the underwater lens lead to the poor resolution of the images acquired by the equipment. In this paper, we propose a residual-dense connected method applied to unmanned deep-sea exploration equipment to improve it's image resolution. The method uses dense connections within the residual structure to improve the model detail information acquisition to ensure accuracy and model stability of model. Secondly, through the study of the model performance, a high precision residual-dense connected model with less computational effort is designed. Finally, the model is trained and tested using environmental images in deep-sea conditions, and it is demonstrated that the method can be applied to deep-sea unmanned exploration equipment for fast, accurate, and stable image super-resolution processing.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Containment control for Multi-Agent Systems under Directed Interaction Topologies with Time-Varying Delays

Containment Control for Multi-Agent Systems under Directed I...

引用

International Conference on control, automation and Systems ( ICCAS)

作者： Xiaojie Peng Yong He 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

This paper is concerned with the containment control problem for multi-agent systems(MASs) with time-varying delays. For the purpose of obtaining less conservative containment control criterion, an augmented Lyapunov-Krasovskii functional(LKF) considering more delay information is constructed firstly. Then by employing the Wirtinger-based integral inequality(WBII) and the extended reciprocally convex matrix inequality(ERCMI) to estimate the derivative of LKF, the delay-dependent term ignored in previous works is reconsidered. Moreover, a delay-product-type(DPT) functional based on the Jensen inequality is established to further reduce the conservatism of the outcomes. As a result, two new criteria are derived to ensure the containment consensus on the communication directed graph, the upper bound of maximum delays and feedback gains. Finally, two numerical simulations are employed to demonstrate the superiority of the theoretical results.

关键词： Upper bound control systems Numerical simulation Delays Topology Linear matrix inequalities Time-varying systems

来源：评论

学校读者我要写书评

暂无评论

Emotion Recognition via Environmental Context and Human Body

Emotion Recognition via Environmental Context and Human Body

引用

Industrial Cyber-Physical Systems (ICPS)

作者： Cheng-Shan Jiang Zhen-Tao Liu 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 Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan P. R. China

To promote the humanized interactive experience of the intelligent device and system, emotional intelligence has become a popular research field in the human-machine interaction. The previous research on emotion recognition based on computer vision has mostly been carried out by analysing facial expression or body posture, and psychological studies show that scene context also contributes some important information on emotion recognition. In addition, most context-aware emotion recognition studies focus on exploring the relevance analysis of environmental semantics, but the influence of feature encoder on semantic information embedding has not been fully discussed. In this paper, we proposed a Global Semantic Feature Enhancement-Dual Stream Densely Connected Network (GSFE-DSDCN) to enhance global semantic information learning from the perspectives of dimension and spatial. Densely connected pattern is introduced to concatenate the shallow and deep layers output, which fuses the semantic information of low-dimensional geometric features and high-dimensional abstract context features together. The Global Multi-Scale Feature Recalibration (GMSFR) module expands the receptive field in spatial, which effectively improves the global semantic features extraction capability of feature encoder. We evaluate the proposed method on the EMOTIC data set, and experimental results are shown to be competitive with the state-of-the-art algorithms.

关键词： Human computer interaction Emotion recognition Computer vision Fuses Biological system modeling Semantics Psychology

来源：评论

学校读者我要写书评

暂无评论

Group Consensus of Multi-agent Systems with Additive Noises and Multiplicative Noises

Group Consensus of Multi-agent Systems with Additive Noises ...

引用

Chinese automation Congress (CAC)

作者： Haoxiang Qin Chuanjian Li Xiaofeng Zong 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

In this paper, we study the group consensus problem of multi-agent systems with additive noises and multiplicative noises. The multi-agent systems are composed of two sub networks affected by additive noises and multiplicative noises, respectively. A consensus protocol is designed to guarantee the group consensus. Based on this protocol, the mean square weak consensus condition and mean square strong consensus condition are obtained by algebraic graph theory and stochastic stability theory. Finally, the numerical simulations show the effectiveness of the group consensus protocol in this paper.

关键词： Additive noise Differential equations Numerical simulation Stability analysis Consensus protocol Thermal stability Numerical stability

来源：评论

学校读者我要写书评

暂无评论

Exponential Stability Analysis for Delayed Neural Networks via A Cubic Function Negative-Determination Lemma

Exponential Stability Analysis for Delayed Neural Networks v...

引用

Chinese control Conference (CCC)

作者： Wen-Xuan Zhao Yun-Fan Liu Yu-Long Fan Chuan-Ke Zhang 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 Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan P. R. China

This paper concerns with the exponential stability of delayed neural networks via Lyapunov-Krasovskii functional (LKF) method. Initially, an improved augmented delay-product-type LKF containing an additional double integral state is established, which introduces more delayed states and has less conservatism. In the LKF's derivative, the function has high order of delay due to the existence of exponent. Thus, in order to obtain tractable linear matrix inequalities, three state vectors are used to reduce the order of the function to cubic. Secondly, to achieve the negative-definiteness requirement, a negative-determination lemma for cubic functions with less conservatism is employed. Then, a less conservative delay-dependent stability criterion for neural networks with time-varying delays is established. Finally, the validity of the proposed delay-dependent stability criterion is illustrated by two numerical examples.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Deep transfer learning-based decoder calibration for intracortical brain-machine interfaces

引用

Computers in Biology and Medicine 2025年第Pt A期192卷 110231-110231页

作者： Li, Xiao Dong, Xianxin Wang, Jun Mao, Haodong Tu, Xikai Li, Wei He, Jiping Li, Qiang Zhang, Peng Hubei Key Laboratory of Modern Manufacturing Quantity Engineering School of Mechanical Engineering Hubei University of Technology Wuhan430068 China Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Hubei Wuhan China MoE Key Laboratory for Biomedical Photonics Collaborative Innovation Center for Biomedical Engineering School of Engineering Sciences Huazhong University of Science and Technology Hubei Wuhan China The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan China Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

Intracortical brain-machine interfaces (iBMIs) aim to establish a communication path between the brain and external devices. However, in the daily use of iBMIs, the non-stationarity of recorded neural signals necessitates frequent recalibration of the iBMI decoder to maintain decoding performance, which requires collecting and labeling a large amount of new data. To address this challenge and minimize the time needed for decoder recalibration, we proposed an active learning domain adversarial neural network (AL-DANN). This model leveraged a substantial volume of historical data alongside a small amount of current data (four samples per category) to calibrate the decoder. By incorporating domain adversarial and active learning strategies, the model effectively transferred knowledge from historical data to new data, reducing the demand for new samples. We validated the proposed method using neural signals recorded from three monkeys performing different movements in a classification task or a regression task. The results showed that the AL-DANN outperformed existing state-of-the-art methods. Impressively, it required only four new samples per category for decoder recalibration, leading to a recalibration time reduction of over 80 %. To our knowledge, this is the first study to incorporate deep transfer learning into iBMI decoder calibration, highlighting the significant potential of applying deep learning technologies in iBMIs. © 2025

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

control Strategy of Electrolytic Capacitor-Less Multi-port Converter for Suppressing the Influences of Low-Frequency DC-Link Current Ripple

Control Strategy of Electrolytic Capacitor-Less Multi-port C...

引用

Smart Power & Internet Energy Systems (SPIES), International Conference on

作者： Zihong Zhang Zhijian Fang Yuangeng Xia Hanlin Dong Haojiang Yue 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

Multi-port Converter (MPC) gets growing applications due to its advantages of flexible control mode, high power density, bidirectional power delivery capability, etc. However, the inherent instantaneous power difference between each port will generate significant low frequency dc-link current ripple, which degrades the operational stability of the system. To suppress the influence, the mechanism of dc-link current ripple is analyzed. And then, a compound control strategy based on the repetitive controller (RC) plus a PR controller is adopted according to the ripple characteristics for the electrolytic Capacitor-Less Multi-port Converter. The developed current control strategy in this paper can achieve a minimum steady-state error while maintaining a relatively fast transient response. Finally, to validate the proposed strategy, a simulation is also built and tested. The simulation results validate the theoretical analysis.

关键词： Transient response Power system measurements Simulation Power system dynamics Power system stability Frequency conversion Stability analysis

来源：评论

学校读者我要写书评

暂无评论

Stability Analysis of Discrete Networked Systems with Network Induced Delay and Malicious Packet Dropout Based on a Matrix Transformation Method

Stability Analysis of Discrete Networked Systems with Networ...

引用

Chinese control Conference (CCC)

作者： Meng-Ying Zhou Wen-Hu Chen Chuan-Ke Zhang Ya-Xin Hou Ke-You Xie 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 Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan P. R. China

This paper is concerned with the stability of discrete-time networked control systems with network induced delay and malicious packet dropout. Firstly, network induced delay and malicious packet dropout are analyzed, and the data packet dropout is converted into the change rate of time delay. Secondly, the functional of time delay and change rate of time delay is constructed, and some summation terms are generated when calculating the functional forward difference. Moreover, the auxiliary-function-based summation inequality and reciprocally convex matrix inequality are used to estimate the resulting summation terms. Then, a less conservative stability criterion for discrete networked systems with network delay and data packet loss is established. Finally, the validity of the proposed stability criterion is illustrated by a numerical example.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Q -learning based model-free input-output feedback linearization control method ⋆

引用

IFAC-PapersOnLine 2023年第2期56卷 9534-9539页

作者： Yipu Sun Xin Chen Wenpeng He Ziying Zhang Edwardo F. Fukushima Jinhua She 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 School of Engineering Tokyo University of Technology Hachioji Tokyo 192-0982 Japan School of Arts and Communication China University of Geosciences Wuhan 430074 China

Input-output feedback linearization is a nonlinear control method that relies on a precise dynamical model. Combining Q -learning techniques, an input-output feedback linearization correction framework is presented to accomplish model-free feedback linearization of affine nonlinear systems in order to tackle the problem caused by the unknown dynamics model. This framework formulates a model reference tracking control problem that guides the input-output relationship of the nonlinear system into a linear relationship. Due to the two Lie derivative terms present in the feedback linearized controller, the controller is designed as a dual network structure. To overcome the issue of coupling in the dual-network controller, a model-free Q -learning method is presented to solve the unknown controller network weights. The proposed method is experimentally validated on a single-link flexible joint manipulator system, and the resultant linearized system exhibits dynamics similar to the desired linear system in a new tracking task, proving the effectiveness of the proposed method.

关键词： Input-output feedback linearization unknown nonlinear systems Q-learning model-free nonlinear control method

来源：评论

学校读者我要写书评

暂无评论

Stability and Bifurcation control of Fractional-Order Coupled Hindmarsh-Rose Neural Networks

Stability and Bifurcation Control of Fractional-Order Couple...

引用

Chinese control Conference (CCC)

作者： Feng Liu Feifan Zhou Wei Wang Gang Cai Hua O Wang Xiuqin Yang School of Automation China University of Geosciences Wuhan China 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 Wuhan China Department of Mechanical Engineering Boston University Boston USA School of Education Minzu University of China Beijing China

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

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：