检索结果-南通市图书馆

linear systems toolkit in Matlab :structural decompositions and their applications

在线全文

cnki会议

学校读者我要写书评

暂无评论

控制理论与应用（英文版） 2005年第3期3卷 287-294页

作者： Xinmin LIU Ben M. CHEN zongli lin Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville USA Department of Electrical and Computer Engineering National University of Singapore Singapore 117576Singapore

This paper presents a brief description of the software toolbox, linear systems toolkit, developed in Matlab environment. The toolkit contains 66 m-functious, including structural decompositions of linear autonomous systems, unforced/uuseused systems, proper systems, and singular systems, along with their applications to system factorizations, sensor/actuator selection, H-two and H-infinity control, and disturbance decoupling problems.

关键词： linear systems Structural decompositions linear control Software development

Recent research progress in the mechanism and suppression of fusion welding-induced liquation cracking of nickel based superalloys

在线全文

学校读者我要写书评

暂无评论

International Journal of Minerals,Metallurgy and Materials 2024年第5期31卷 1072-1088页

作者： zongli Yi Jiguo Shan Yue Zhao Zhenlin Zhang Aiping Wu Department of Mechanical Engineering Tsinghua UniversityBeijing 100084China College of Engineering China Agricultural UniversityBeijing 100091China State Key Laboratory of Clean and Efficient Turbomachinery Power Equipment Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China Key Laboratory for Advanced Materials Processing Technology Ministry of EducationBeijing 100084China School of Material Science and Engineering Southwest Jiaotong UniversityChengdu 610031China

Nickel-based superalloys are extensively used in the crucial hot-section components of industrial gas turbines,aeronautics,and astronautics because of their excellent mechanical properties and corrosion resistance at high *** welding serves as an effective means for joining and repairing these alloys;however,fusion welding-induced liquation cracking has been a challenging *** paper comprehensively reviewed recent liquation cracking,discussing the formation mechanisms,cracking criteria,and *** recent investigations,regulating material composition,changing the preweld heat treatment of the base metal,optimizing the welding process parameters,and applying auxiliary control methods are effective strategies for mitigating *** promote the application of nickel-based superalloys,further research on the combination impact of multiple elements on cracking prevention and specific quantitative criteria for liquation cracking is necessary.

关键词： nickel-based superalloy fusion welding liquation cracking cracking mechanism cracking suppression

Consensus of linear Multi-Agent Systems in the Presence of Bounded Measurement Noises

在线全文

学校读者我要写书评

暂无评论

Consensus of Linear Multi-Agent Systems in the Presence of B...

第三十九届中国控制会议

作者： Tingyang Meng Yijing Xie zongli lin Charles L.Brown Department of Electrical and Computer Engineering University of Virginia Department of Automation Shanghai Jiao Tong University

In this paper, we investigate the static-consensus problem of linear multi-agent systems in the presence of bounded noises in the measurements of neighbors’ states over a connected undirected communication topology. We propose two types of consensus protocols, one using full state measurements of the neighbors and the other using partial state measurements of the neighbors. With the knowledge of the noise bounds, we show that, under these consensus protocols, the agents achieve static-consensus. A numerical example is presented to illustrate the theoretical results.

关键词： Cooperative control Consensus Measurement Noises

Breast Cancer Diagnosis Using an Unsupervised Feature Extraction Algorithm Based on Deep Learning

在线全文

cnki会议

学校读者我要写书评

暂无评论

Breast Cancer Diagnosis Using an Unsupervised Feature Extrac...

第37届中国控制会议

作者： Yawen Xiao Jun Wu zongli lin Xiaodong Zhao Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information Processing of Ministry of Education The Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal University Charles L.Brown Department of Electrical and Computer Engineering University of Virginia School of Biomedical Engineering Shanghai Jiao Tong University

Breast cancer is the most often detected cancer in women. At the same time, it is one of the most curable types of cancer if diagnosed early. With the development of the detection technology, a growing amount of clinical data and highdimensional features can be used for breast cancer diagnosis. The high-dimensional data contributes to advances in the diagnostic technology, but also incurs a large amount of computational redundancy. Thus, extracting important information and reducing the feature dimension is critical to effective prediction and an accurate treatment ***, the previous works for breast cancer diagnosis are mainly based on labeled data that is difficult to obtain. To address this issue, in this paper, we demonstrate a new scheme, which integrates a deep learning based unsupervised feature extraction algorithm, the stacked auto-encoders, with a support vector machine model（SAE-SVM）, for breast cancer diagnosis. The stacked auto-encoders with the greedy layerwise pre-training and an improved momentum update algorithm is applied to capture essential information and extract necessary features of the original data. Then, a support vector machine model is employed to classify the samples with new features into malignant or benign tumors. The proposed method was tested on the Wisconsin Diagnostic Breast Cancer data set. The performance is evaluated using various measures and compared with the previously published results. The comparison results show that the proposed SAE-SVM method improves the accuracy to 98.25% and outperforms the other methods. The deep learning based unsupervised feature extraction significantly improves the performance of classification and provides a promising approach to breast cancer diagnosis.

关键词： Deep learning auto-encoder feature extraction breast cancer diagnosis unlabeled data

Enhancing the Effectiveness of Fungicides by Optimizing Their Combinations

在线全文

cnki会议

学校读者我要写书评

暂无评论

Enhancing the Effectiveness of Fungicides by Optimizing Thei...

第26届中国控制与决策会议

作者： Xiang Wang Jia Ma Xiaowei Li Xiaodong Zhao zongli lin Jie Chen Zhifeng Shao Department of Automation and Key Laboratory of System Control and Information Processing of the Ministry of EducationShanghai Jiao Tong University Department of Resource and Environmental Science School of Agriculture and BiologyShanghai Jiao Tong University School of Biomedical Engineering Shanghai Jiao Tong University Charles L.Brown Department of Electrical and Computer Engineering University of Virginia

In controlling biological diseases, it is often more potent to use a combination of agents than using individual ones. However, the number of possible combinations increases exponentially with the number of agents and their concentrations. It is prohibitive to search for effective agent combinations by trial and error as biological systems are complex and their responses to agents are often a slow process. This motivates to build a suitable model to describe the biological systems and help reduce the number of experiments. In this paper, we consider the use of fungicides to inhibit Bipolarismaydis and construct models that describe the responses to fungicide combinations. Three data-driven modeling methods, the polynomial regression, the artificial neural network and the support vector regression, are compared based on the experimental data of the inhibition rates of the southern corn leaf blight with different fungicide combinations. The analysis of the results demonstrates that the support vector regression is best suited to the construction of the response model in terms of achieving better prediction with fewer experiments.

关键词： agent combinations complex system data-driven model polynomial regression artificial neural network support vector regression

Local thermal conductivity of inhomogeneous nano-fluidic films:A density functional theory perspective

在线全文

cnki会议

学校读者我要写书评

暂无评论

Chinese Physics B 2024年第4期33卷 594-603页

作者：孙宗利康艳霜康艳梅 Department of Mathematics and Physics North China Electric Power UniversityBaoding 071003China College of Science Hebei Agricultural UniversityBaoding 071001China Hebei Key Laboratory of Physics and Energy Technology Baoding 071003China University of International Relations Beijing 100091China

Combining the mean field Pozhar-Gubbins(PG)theory and the weighted density approximation,a novel method for local thermal conductivity of inhomogeneous fluids is *** correlation effect that is beyond the mean field treatment is taken into account by the simulation-based empirical *** application of this method to confined argon in slit pore shows that its prediction agrees well with the simulation results,and that it performs better than the original PG theory as well as the local averaged density model(LADM).In its further application to the nano-fluidic films,the influences of fluid parameters and pore parameters on the thermal conductivity are calculated and *** is found that both the local thermal conductivity and the overall thermal conductivity can be significantly modulated by these ***,in the supercritical states,the thermal conductivity of the confined fluid shows positive correlation to the bulk density as well as the ***,when the bulk density is small,the thermal conductivity exhibits a decrease-increase transition as the temperature is *** is also the case in which the temperature is *** fact,the decrease-increase transition in both the small-bulk-density and low-temperature cases arises from the capillary condensation in the ***,smaller pore width and/or stronger adsorption potential can raise the critical temperature for condensation,and then are beneficial to the enhancement of the thermal *** modulation behaviors of the local thermal conductivity lead immediately to the significant difference of the overall thermal conductivity in different phase regions.

关键词： thermal conductivity nano-fluidic films density functional theory

A fast forward computational method for nuclear measurement using volumetric detection constraints

在线全文

学校读者我要写书评

暂无评论

Nuclear Science and Techniques 2024年第2期35卷 47-63页

作者： Qiong Zhang lin-Lv lin University of Electronic Science and Technology of China Chengdu 610000China

Owing to the complex lithology of unconventional reservoirs,field interpreters usually need to provide a basis for interpretation using logging simulation *** the various detection tools that use nuclear sources,the detector response can reflect various types of information of the *** Monte Carlo method is one of the primary methods used to obtain nuclear detection responses in complex ***,this requires a computational process with extensive random sampling,consumes considerable resources,and does not provide real-time response ***,a novel fast forward computational method(FFCM)for nuclear measurement that uses volumetric detection constraints to rapidly calculate the detector response in various complex environments is ***,the data library required for the FFCM is built by collecting the detection volume,detector counts,and flux sensitivity functions through a Monte Carlo ***,based on perturbation theory and the Rytov approximation,a model for the detector response is derived using the flux sensitivity function method and a one-group diffusion *** environmental perturbation is constrained to optimize the model according to the tool structure and the impact of the formation and borehole within the effective detection ***,the method is applied to a neutron porosity tool for *** various complex simulation environments,the maximum relative error between the calculated porosity results of Monte Carlo and FFCM was 6.80%,with a rootmean-square error of 0.62 *** field well applications,the formation porosity model obtained using FFCM was in good agreement with the model obtained by interpreters,which demonstrates the validity and accuracy of the proposed method.

关键词： Nuclear measurement Fast forward computation Volumetric constraints

Enhancing Safety in Autonomous Vehicle Navigation:An Optimized Path Planning Approach Leveraging Model Predictive Control

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第9期80卷 3555-3572页

作者： Shih-lin lin Bo-Chen lin Graduate Institute of Vehicle Engineering National Changhua University of EducationChanghua50007TaiwanChina

This paper explores the application of Model Predictive Control(MPC)to enhance safety and efficiency in autonomous vehicle(AV)navigation through optimized path *** evolution of AV technology has progressed rapidly,moving from basic driver-assistance systems(Level 1)to fully autonomous capabilities(Level 5).Central to this advancement are two key functionalities:Lane-Change Maneuvers(LCM)and Adaptive Cruise Control(ACC).In this study,a detailed simulation environment is created to replicate the road network between Nantun andWuri on National Freeway No.1 in *** MPC controller is deployed to optimize vehicle trajectories,ensuring safe and efficient *** onboard sensors,including vehicle cameras and millimeterwave radar,are used to detect and respond to dynamic changes in the surrounding environment,enabling real-time decision-making for LCM and *** simulation resultshighlight the superiority of the MPC-based approach in maintaining safe distances,executing controlled lane changes,and optimizing fuel ***,the MPC controller effectively manages collision avoidance,reduces travel time,and contributes to smoother traffic flow compared to traditional path planning *** findings underscore the potential of MPC to enhance the reliability and safety of autonomous driving in complex traffic *** research will focus on validating these results through real-world testing,addressing computational challenges for real-time implementation,and exploring the adaptability of MPC under various environmental *** study provides a significant step towards achieving safer and more efficient autonomous vehicle navigation,paving the way for broader adoption of MPC in AV systems.

关键词： Autonomous driving model predictive control(MPC) lane change maneuver(LCM) adaptive cruise control(ACC)

PID Control of Planar Nonlinear Uncertain Systems in the Presence of Actuator Saturation.

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论