检索结果-内蒙古大学图书馆

Construction of Multilayer Porous Scaffold Based on Magnetically Guided Assembly of Microfiber

Journal of systems Science & complexity 2018年第3期31卷 581-595页

作者： LI Xingfu WANG Huaping SHI Qing SUN Tao HUANG Qiang FUKUDA Toshio Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing 100081 China Key Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing 100816 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 China

This paper proposes a novel method of magnetically guided assembly to construct multi- layer porous scaffold for three-dimensional cell culture by apply magnetic microfibers. Microfibers are composed of biocompatible and biodegradable alginate solution with homogeneous magnetic nanopar- ticles, which are continuously spun from a microfluidic device by precise pressure control of the syringe pump. Magnetic nanoparticles enable the control of magnetic field on microfibers. Meanwhile, mag- netized device combining with a round permanent magnet are utilized to guide the distribution of spouted microfibers. The device is composed by pure iron wire arrays and wax, which stimulates pow- erful magnetic flux density and magnetic field gradients for the capture and assembly of microfibers. Thus, magnetic microfibers are spun on desired places of the magnetized device by motion control of the micromanipulation robot, and precise locations are adjusted by magnetic force couple with the assist of glass micropipette. Afterwards, microfibers are spatially organized by periodic magnetic force and crossed layer-by-layer to form micro-pore structure with both length and width of 650μm. Finally, the authors construct a multilayer microfiber-based scaffold with high porosity to provide a satisfactory environment for long-term cell culture. The experimental results demonstrate the effectiveness of the proposed method.

关键词： Magnetically guided assembly magnetic microfiber magnetized device periodic magneticforce multilayer porous scaffold.

来源：评论

学校读者我要写书评

暂无评论

Structure parameter optimized kernel based online prediction with a generalized optimization strategy for nonstationary time series

arXiv

引用

arXiv 2021年

作者： Guo, Jinhua Chen, Hao Zhang, Jingxin Chen, Sheng Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic Systems Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences Fuzhou350002 China Department of Automation Tsinghua University Beijing100084 China School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

In this paper, sparsification techniques aided online prediction algorithms in a reproducing kernel Hilbert space are studied for nonstationary time series. The online prediction algorithms as usual consist of the selection of kernel structure parameters and the kernel weight vector updating. For structure parameters, the kernel dictionary is selected by some sparsification techniques with online selective modeling criteria, and moreover the kernel covariance matrix is intermittently optimized in the light of the covariance matrix adaptation evolution strategy (CMA-ES). Optimizing the real symmetric covariance matrix can not only improve the kernel structure's flexibility by the cross relatedness of the input variables, but also partly alleviate the prediction uncertainty caused by the kernel dictionary selection for nonstationary time series. In order to sufficiently capture the underlying dynamic characteristics in prediction-error time series, a generalized optimization strategy is designed to construct the kernel dictionary sequentially in multiple kernel connection modes. The generalized optimization strategy provides a more self-contained way to construct the entire kernel connections, which enhances the ability to adaptively track the changing dynamic characteristics. Numerical simulations have demonstrated that the proposed approach has superior prediction performance for nonstationary time series. Copyright © 2021, The Authors. All rights reserved.

关键词： Radial basis function networks

来源：评论

学校读者我要写书评

暂无评论

Research and practice of lightweight digital twin speeding up the implementation of flexible manufacturing systems

Research and practice of lightweight digital twin speeding u...

引用

Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Xiaodong Zhang Bin Hu Gang Xiong Xinjie Liu Xisong Dong Dongjia Li School of Information Engineering Yantai institute of Technology Yantai China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Chinese Academy of Sciences Beijing China Yantai University Yantai China School of Artificial Intelligence Yantai Institute of Technology Yantai China

Parallel manufacturing in Industry 5.0 requires digital twin to digitize physical systems, building virtual models to open up channels connecting physical systems, information systems, and social systems, and transforming the physical models of the existing production environment to achieve two-way feedback of virtual and real is the current research direction. This paper proposes the modeling idea of lightweight digital twin, extracts core dimensions and performs digital virtual simulation, so as to quickly realize the complete process of two-way feedback, and realize a set of chess flexible parallel manufacturing production lines as a practice for the design of complete lightweight digital twin.

关键词： Industries Digital twin Conferences Buildings Production Manufacturing Flexible manufacturing systems

来源：评论

学校读者我要写书评

暂无评论

A Unified Framework for Finite-/Fixed-Time Synchronization of Memristor Chaotic systems and Its Application in Image Encryption

Research Square

引用

Research Square 2021年

作者： Wang, Leimin Jiang, Shan Ge, Ming-Feng Hu, Junhao China University of Geosciences China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan430074 China College of Mathematics and Statistics South-Central University for Nationalities Wuhan430074 China

This paper proposes a sliding-mode-based unified control framework to solve the synchronization problem of memristor chaotic systems. Both finite- and fixed-time synchronization of the memristor chaotic systems can be obtained in the uniform framework. According to the Lyapunov stability and finite-time stability theories, we demonstrate that the trajectories of error system reach the presented sliding-mode surface and converge to the origin along the surface in a finite/fixed time. Moreover, an image encryption algorithm is developed based on the presented control framework. Finally, the numerical simulations and the statistical performance analyses are discussed to illustrate the correctness of synchronization results, the effectiveness of the proposed encryption algorithm, and its potential applications in the scope of secure communication. © 2021, CC BY.

关键词： Chaotic systems

来源：评论

学校读者我要写书评

暂无评论

Disturbance rejection of two-dimensional repetitive control system based on T-S fuzzy model

Disturbance rejection of two-dimensional repetitive control ...

引用

IEEE Conference on Decision and control

作者： Shengnan Tian Min Wu Manli Zhang Chengda Lu Luefeng Chen Jinhua She School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Engineering Tokyo University of Technology Hachioji Japan

ISBN: (数字)9781728174471

ISBN: (纸本)9781728174488

In this paper, the issue of disturbance rejection of nonlinear repetitive control system (RCS) based on a continuous-discrete two-dimensional (2D) model is studied. Since a RCS involves continuous control and discrete learning, higher tracking performance may be realizable by taking into account these two different actions in system design. This paper construct a fuzzy RCS based on T-S model at first. Then, an improved fuzzy-equivalent-input-disturbance (IFEID)-based 2D RCS is presented to achieve both high tracking precision of periodic input and satisfactory rejection of aperiodic disturbances. Stability conditions of two subsystems are derived by exploiting separation theorem to ease the solution of state-feedback and observer gains. A design algorithm is presented via the concept of parallel distributed compensation. A simulation and a comparison demonstrate the availability and advantage of the IFEID-based 2D RCS approach.

关键词： Two dimensional displays Observers control systems Estimation State feedback Stability analysis Time-frequency analysis

来源：评论

学校读者我要写书评

暂无评论

Research on path planning of robot based on deep reinforcement learning

Research on path planning of robot based on deep reinforceme...

引用

第三十九届中国控制会议

作者： Feng Liu Chang Chen Zhihua Li Zhi-Hong Guan Hua O Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems College of Automation Huazhong University of Science and Technology Department of Mechanical Engineering Boston University

In this paper, to avoid the problem of local optimization and slow convergence in complex environment, a reinforcement learning algorithm is proposed to solve the problem. A robot path planning model is built and its feasibility is verified by simulation. In addition, this paper proposes a deep environment to neural network for robot camera to establish a deep reinforcement learning path planning model, and establishes a deep recursive Q-network（DRQN） and Deep Dueling Q-network（DDQN）respectively. In the comparison of the final simulation results, DRQN needs to consume more computation time, but can achieve better results with higher accuracy.

关键词： Reinforcement learning path planning robots deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

H∞ Consensus control of Multi-agent systems with Round-robin Protocol and Missing Measurements: The Finite-horizon Case

H∞ Consensus Control of Multi-agent Systems with Round-robi...

引用

第31届中国控制与决策会议

作者： Mengmeng Sun Dongyan Chen School of Science Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology

The H consensus control problem is handled for a class of discrete time-varying multi-agent systems with round-robin protocol and missing measurements. The round-robin protocol is considered, which allows only one agent can send its measurement data at each transmission step in order to prevent the data collisions. And the missing measurements phenomenon is described by a sequence of Bernoulli distributed random variables with known probabilities. We focus on designing the controller parameters to guarantee that the closed-loop multi-agent systems with missing measurements satisfy the H consensus performance. On this basis, some sufficient and necessary conditions are obtained by solving coupled backward recursive Riccati difference equations, where the existence and feasibility of the control scheme can be obtained with the help of the completing squares method and the stochastic analysis technique. At last, a numerical example is given to illustrate the effectiveness of the developed controller design scheme.

关键词： Time-varying Multi-agent systems H_∞ Consensus control Round-robin Protocol Missing Measurements Recursive Riccati Difference Equations

来源：评论

学校读者我要写书评

暂无评论

Urban Trip Generation Forecasting Based on Gradient Boosting Algorithm

Urban Trip Generation Forecasting Based on Gradient Boosting...

引用

Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Zhishuai Li Gang Xiong Yu Zhang Meng Zheng Xisong Dong Yisheng Lv State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Municipal Institute of City Planning and Design Beijing China

The four-step transportation model plays an important role in urban planning. The quality of the first phase, i.e. trip generation, determines the performance of the global course. The majority of trip generation forecasting models highly rely on mathematical derivation and have many predictor variables during the prediction, which leads to low accuracy of results and requires laboriously hand-crafted design of input vectors. This paper is the first to introduce the gradient boosting decision tree (GBDT) algorithm for trip generation prediction, and harmonizes such a powerful machine learning method with traditional urban planning requirements to achieve better prediction performance. Unlike the commonly used linear regression method, GBDT can automatically perform feature selection and model the non-linear relationships between input and output variables. Experimental results on real-world residential travel census in Beijing prove that the GBDT model significantly outperforms the baseline and can forecast the trip generation more accurately.

关键词： Machine learning algorithms Urban planning Transportation Predictive models Prediction algorithms Feature extraction Boosting

来源：评论

学校读者我要写书评

暂无评论

Improved potential field method path planning based on genetic algorithm

Improved potential field method path planning based on genet...

引用

第三十九届中国控制会议

作者： Feng Liu Hualing He Zhihua Li Zhi-Hong Guan Hua O Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems College of Automation Huazhong University of Science and Technology Department of Mechanical Engineering Boston University

In order to overcome the problem of path planning failure in traditional potential field method, an improved potential field path planning method based on genetic algorithm is proposed in this paper. Firstly, for the problem of inaccessibility of the target, a factor method is added to the traditional gravity function to solve it;then the local minimum point problem of the traditional artificial potential field method is solved to ensure that the robot can reach the target point. At the same time, in order to get the optimal path, genetic algorithm is used to optimize the combined potential field function of gravity and repulsion, to find the lowest point of potential energy directly, so as to determine the step size and moving direction of the robot. Simulation is carried out to verify the effectiveness of the method.

关键词： Path planning artificial potential field gravitation function genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

The Prediction of the Epidemic Trend of COVID-19 Using Neural Networks

引用

IFAC-PapersOnLine 2020年第5期53卷 857-862页

作者： Jing Yang Zhen Shen Xisong Dong Xiuqin Shang Wei Li Gang Xiong J. Yang is with the State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China and also with College of Information Sciences & Technology Beijing University of Chemical Technology Beijing 100029 China. Z. Shen is with the State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China and also with the Intelligent Manufacturing Center Qingdao Academy of Intelligent Industries Qingdao Shandong 266113 China. X. Dong X. Shang and W. Li are with the State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China. G. Xiong is with Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China and also with the Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Dongguan Guangdong 523808 China.

In this paper, a BP neural network and an LSTM network are applied respectively to the prediction of Coronavirus Disease 2019 (COVID-19) in Wuhan, China and South Korea. The methods do not require specific theories of modelling and the predicted values can be obtained as long as the conventional parameters are set. The mean absolute percentage error (MAPE) of all the experiments are below 5% and the values of the determinable coefficient R are all larger than 0.9. The experiments show that the models can fit the actual values well and make relatively accurate predictions. As of March 29, 2020, the cumulative number of confirmed cases in Wuhan is expected to reach 50,068 using BP neural networks and 49,972 using LSTM network, respectively. As of April 13, 2020, the cumulative number of confirmed cases in South Korea is expected to reach 8,862 using BP neural networks and 8,716 using LSTM network, respectively. The models of neural networks are effective in predicting the trend of the COVID-19 epidemic, which is meaningful to prevent and control the epidemic.

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：