检索结果-内蒙古大学图书馆

Far feature detection using geometric uncertainty in visual-inertial navigation system

Journal of institute of control, Robotics and systems 2021年第11期27卷 794-800页

作者： Lee, Han Yeol Jung, Jae Hyung Park, Chan Gook Department of Aerospace Engineering Automation and System Research Institute Seoul National University Korea Republic of

In this paper, we propose a new method that classifies the features in a visual-inertial navigation system. The far features provide inaccurate information on the position and velocity of a moving vehicle, and thus, the information provided by the far features should be used for attitude estimation without recovering the feature depths. In contrast, the information obtained from the near features can be used to obtain a reliable depth estimate because of the large parallax in the image plane. However, the criterion for labeling the features as near or far features is ambiguous. Previously, various geometric classification methods based on a stereo camera and measurement uncertainties have been reported. Herein, we present a criterion based on the geometric method using the MSCKF (Multi-State Constraint Kalman filter). Additionally, we define a new concept — depth uncertainty — as the criterion of feature classification in the MSCKF. Using this criterion, we can draw a limited range defined as the observable region. Implementation of this method can decrease the error caused by the low parallax of the feature. The proposed method is validated through simulations and experiments, showing a 12.7 % and 21.2 % decrease in the mean position error, respectively, using the far features classification. © ICROS 2021.

关键词： Kalman filters

来源：评论

学校读者我要写书评

暂无评论

Adaptive control of Discrete-time Nonlinear systems Using ITF-ORVFL

引用

IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 556-563页

作者： Xiaofei Zhang Hongbin Ma Wenchao Zuo Man Luo School of Automation Beijing Institute of TechnologyBeijing 100081 School of Vehicle and Mobility Tsinghua UniversityBeijing 100084China School of Automation Beijing Institute of Technologyand also with the State Key Laboratory of Intelligent Control and Decision of Complex Systems(Beijing Institute of Technology)Beijing 100081China School of Automation Beijing Institute of TechnologyBeijing 100081and he is with Beijing Institute of Electronic System EngineeringBeijing 100854China School of Automation Beijing Institute of TechnologyBeijing 100081and she is with Ant GroupBeijing 310013China

Random vector functional ink(RVFL)networks belong to a class of single hidden layer neural networks in which some parameters are randomly *** network structure in which contains the direct links between inputs and outputs is unique,and stability analysis and real-time performance are two difficulties of the control systems based on neural *** this paper,combining the advantages of RVFL and the ideas of online sequential extreme learning machine(OS-ELM)and initial-training-free online extreme learning machine(ITFOELM),a novel online learning algorithm which is named as initial-training-free online random vector functional link algo rithm(ITF-ORVFL)is investigated for training *** link vector of RVFL network can be analytically determined based on sequentially arriving data by ITF-ORVFL with a high learning speed,and the stability for nonlinear systems based on this learning algorithm is *** experiment results indicate that the proposed ITF-ORVFL is effective in coping with nonparametric uncertainty.

关键词： Adaptive control initial-training-free online learning algorithm random vector functional link networks

来源：评论

学校读者我要写书评

暂无评论

Persistent Coverage in Non-Convex Environments with Heterogeneous Robotic Networks: Constraint-based Approach ⋆

引用

IFAC-PapersOnLine 2023年第2期56卷 10708-10714页

作者： J.G. Martin T. Hatanaka J.M. Maestre E.F. Camacho Department of Systems and Automation Engineering University of Seville Spain Department of Systems and Control Engineering Tokyo Institute of Technology

In this paper, we extend a constraint-based coverage control for robotic sensor networks based on control barrier functions (CBFs) for environments with known obstacles and different types of unmanned vehicles (UV). To this end, we use a sensing function that considers the vertices of the obstacles to compute the route and the distance regarding the UVs. This way, obstacle avoidance becomes intrinsic to the CBF ensuring the coverage performance. Moreover, we consider different obstacles and speeds for each type of UV. Finally, the proposed algorithm is illustrated with a heterogeneous fleet of UVs and obstacles in a simulated thermosolar power plant.

关键词： Coordination of multiple vehicle systems Graph-based methods for networked systems Networked robotic systems control barrier function (CBF) coverage control obstacles non-convex area

来源：评论

学校读者我要写书评

暂无评论

Day-ahead Chance-constrained Energy Management of Energy Hubs:A Distributionally Robust Approach

引用

CSEE Journal of Power and Energy systems 2022年第3期8卷 812-825页

作者： Jiaxin Cao Bo Yang Shanying Zhu Chao Ning Xinping Guan Department of Automation Shanghai Jiao Tong UniversityShanghai200240China Key Laboratory of System Control and Information Processing Ministry of Education of China Robert Frederick Smith School of Chemical and Biomolecular Engineering Cornell UniversityIthacaNY 14853 USA

The day-ahead management schedules of hybrid energy hubs are intricate and usually exposed to various uncertainties with the penetration of renewable sources and different ***,it is difficult to access to precise probability distribution functions and exact moment information of uncertain *** cope with these issues,an energy management scheme based on the distributionally robust optimization approach is developed for the energy *** makes no assumptions of certain probability distributions and can be implemented with limited empirical data and partial information of underlying *** operational strategy can provide decision makers with a preliminary and robust optimal solution in the day-ahead *** results illustrate the economical benefit of the energy model,and the effectiveness of the proposed approach in chance-constrained energy management is demonstrated by comparing with other *** Terms-Chance constraint,distributionally robust optimization,energy hub,energy management.

关键词： Chance constraint distributionally robust optimization energy hub energy management

来源：评论

学校读者我要写书评

暂无评论

BCLH2Pro:A novel computational tools approach for hydrogen production prediction via machine learning in biomass chemical looping processes

引用

Energy and AI 2024年第4期18卷 13-26页

作者： Thanadol Tuntiwongwat Sippawit Thammawiset Thongchai Rohitatisha Srinophakun Chawalit Ngamcharussrivichai Somboon Sukpancharoen Department of Mechanical Engineering Faculty of EngineeringKhon Kaen UniversityKhon Kaen 40002Thailand Department of Automation Robotics and Intelligent System Faculty of EngineeringKhon Kaen UniversityKhon Kaen 40002Thailand Department of Chemical Engineering Faculty of EngineeringKasetsart UniversityBangkok 10900Thailand Center of Excellence in Catalysis for Bioenergy and Renewable Chemicals(CBRC) Faculty of ScienceChulalongkorn UniversityPathumwanBangkok 10330Thailand Institute of Nanoscience and Nanotechnology(ION2) Universiti Putra MalaysiaSerdang 43400SelangorMalaysia Department of Agricultural Engineering Faculty of EngineeringKhon Kaen UniversityKhon Kaen 40002Thailand Center for Alternative Energy Research and Development Khon Kaen UniversityKhon Kaen 40002Thailand

This study optimizes biomass chemical looping processes(BCLpro),a technique for converting biomass to energy,through machine learning(ML)for sustainable energy *** study proposes an integrated Fe_(2)O_(3)-based,BCLpro combining steam gasification for H2 *** Plus is used as the primary tool to generate extensive datasets covering 24 biomass types with 18 feature inputs in a supervised model.A methodology involving K-Nearest Neighbors(KNN),Extreme Gradient Boosting(XGB),Light Gradient Boosting Machine(LGBM),Support Vector Machine(SVM),Random Forest(RF),and CatBoost(CB)algorithms was employed to predict H_(2)yields in the BCLpro,utilizing 10-fold cross-validation for robust model *** highlight the CB algorithm’s superior performance,achieving up to 98%predictive accuracy,with carbon content,reducer temperature,and Fe_(2)O_(3)/Al_(2)O_(3)mass ratio identified as crucial *** algorithm has been developed into a user-friendly tool,BCLH2Pro,accessible via a web *** tool is designed to assist in reducing costs,optimizing biomass selection,and planning operational conditions to maximize H2 yield in BCLpro *** to the tool can be obtained through the following link:http://***/.

关键词： Artificial intelligence Supervised learning Process simulation Chemical looping Agricultural waste

来源：评论

学校读者我要写书评

暂无评论

Multi-Trajectory Prediction of Pedestrian Based on Deep Neural Network Architecture 6

Multi-Trajectory Prediction of Pedestrian Based on Deep Neur...

引用

6th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2023

作者： Astuti, Lia Lin, Yu-Chen Chen, Wen-Hui Feng Chia University Department of Automatic Control Engineering Taichung Taiwan National Taipei University of Technology Department of Graduate Institute of Automation Technology Taipei Taiwan

ISBN: (纸本)9798350323535

Multimodal learning input has been used to predict the single trajectory of pedestrians. However, the single-trajectory is not efficient in making the vehicle avoid the sudden direction changes of the pedestrian in the drivable area. Therefore, we proposed a multi-trajectory prediction model with a Deep Neural Network (DNN) using an egocentric perspective. First, we input unimodal learning i.e., the historical trajectory sequences into the temporal encoder module. Second, the vision DNN-based network module was used to process the trajectory predictions through the temporal attention mechanism. Third, the linear projection was used for the decoder module to generate single- and multi-trajectory predictions for collision avoidance of vehicles and pedestrians. Finally, the proposed model outperformed previous state-of-the-art models in the experiments on publicly available Pedestrian Intention Estimation (PIE) and Joint Attention in Autonomous Driving (JAAD) datasets. © 2023 IEEE.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy

引用

Plasma Science and Technology 2024年第7期26卷 148-156页

作者：吕一涵宋惟然侯宗余王哲 State Key Laboratory of Power System Operation and Control International Joint Laboratory on Low Carbon Clean Energy InnovationDepartment of Energy and Power EngineeringTsinghua UniversityBeijing 100084People’s Republic of China School of Energy and Electrical Engineering Qinghai UniversityXining 810016People’s Republic of China Tsinghua University Shanxi Research Institute Clean EnergyTaiyuan 030032People’s Republic of China

Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal ***,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification *** this work,we propose a hybrid variable selection method to improve the performance of LIBS *** variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash ***,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model *** proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline *** is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline *** results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,*** LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,*** results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the acc

关键词： laser-induced breakdown spectroscopy(LIBS) coal ash content quantitative analysis variable selection empirical knowledge partial least squares regression(PLSR)

来源：评论

学校读者我要写书评

暂无评论

Multi-Branch Spatial-Temporal Attention Graph Convolution Network for Skeleton-based Action Recognition 41

Multi-Branch Spatial-Temporal Attention Graph Convolution Ne...

引用

第41届中国控制会议

作者： Daoshuai Wang Dewei Li Yaonan Guan Gang Wang Haibin Shao Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Skeleton-based human action reco gnition has attracted considerable research interest due to its robustness to dynamic environments and complex *** based on graph neural networks have achieved great success in this ***,most of these graph neural network based methods adopt a single-branch or two-stream structure with limited input *** to the separation of space and time,many methods cannot pay attention to the critical information of human skeleton sequence,and multi-scale spatial-temporal dependent attention modeling becomes the key to *** paper proposes a novel multi-branch Spatio-temporal attention graph convolutional neural network(MB-STAGCN) to recognize human actions from skeleton *** proposed model adopts a multi-branch structure,fuses three-stream features,and then inputs them into the backbone network to extract features from multiple perspectives to a greater ***,we design a new temporal convolutional block for multi-scale extraction of information in the backbone *** also propose an attention block named Spatio-temporal Concat Attention(STCatAtt) to capture critical *** on benchmark datasets show remarkable performance for human action reco gnition,demonstrating the effectiveness of our method.

关键词： Skeleton-based human action recognition MB-STAGCN STCatAtt

来源：评论

学校读者我要写书评

暂无评论

Stability Analysis of Boolean Networks: Exploring the Influence of Multi-bit Function Perturbations 63

Stability Analysis of Boolean Networks: Exploring the Influe...

引用

63rd IEEE Conference on Decision and control, CDC 2024

作者： Liu, Aixin Wang, Lin Chen, Guanrong Guan, Xinping Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China City University of Hong Kong Department of Electrical Engineering Hong Kong

ISBN: (纸本)9798350316339

This study investigates the impact of multi-bit function perturbations (MFPs) on the steady-state distribution of Boolean networks (BNs), with a focus on robust stability. First, the algebraic formulation of BNs under MFPs is introduced. Then, a novel stability criterion is proposed, demonstrating that monotonically decreasing perturbations can effectively ensure the stability of BNs against MFPs. A significant advantage of this approach is that it enables robust stability assessment without remodeling the perturbed BNs. Applying this methodology to a simplified Boolean model of the lactose operon in Escherichia coli reveals that MFPs can serve as strategic tools to promote stability within BNs, rather than being merely disruptive. © 2024 IEEE.

关键词： Stability criteria

来源：评论

学校读者我要写书评

暂无评论

Robust Consensus Tracking control of Uncertain Multi-Agent systems With Local Disturbance Rejection

引用

IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 427-438页

作者： Pan Yu Kang-Zhi Liu Xudong Liu Xiaoli Li Min Wu Jinhua She the Faculty of Information Technology and the Beijing Institute of Artificial Intelligence Beijing University of TechnologyBeijing 100124China IEEE the Department of Electrical and Electronic Engineering Chiba UniversityChiba 263-8522Japan the Beijing Aerospace Automatic Control Institute Beijing 100854China the School of Automation China University of GeosciencesWuhan 430074China the School of Engineering Tokyo University of TechnologyHachiojiTokyo 192-0982Japan

In this paper,a new distributed consensus tracking protocol incorporating local disturbance rejection is devised for a multi-agent system with heterogeneous dynamic uncertainties and disturbances over a directed *** is of two-degree-of-freedom ***,a robust distributed controller is designed for consensus tracking,while a local disturbance estimator is designed for each agent without requiring the input channel information of *** condition for asymptotic disturbance rejection is ***,even when the disturbance model is not exactly known,the developed method also provides good disturbance-rejection ***,a robust stabilization condition with less conservativeness is derived for the whole multi-agent ***,a design algorithm is ***,comparisons with the conventional one-degree-of-freedombased distributed disturbance-rejection method for mismatched disturbances and the distributed extended-state observer for matched disturbances validate the developed method.

关键词： Directed graph distributed control disturbance rejection dynamic uncertainties multi-agent systems robust control

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：