检索结果-内蒙古大学图书馆

IEEE Transactions on intelligent Vehicles 2024年 1-10页

作者： Huang, Yanting Han, Honggui Zhu, Ming Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Engineering Research Center of Digital Community Ministry of Education Beijing University of Technology Beijing China Institute of Unmanned System Beihang University Beijing China

This paper develops a distributed safety-critical predefined-time control method for the 3-dimensional (3D) moving target surrounding problem of multiple UAVs. A new 3D surrounding shape is first formulated for multiple UAVs to distribute on a moving spherical surface around the target. To reduce the communication and load burden, a predefined-time distributed estimator is designed for a subset of UAVs without any access to the target, so that the target's motion information can be accurately estimated within a predefined time. Subsequently, a robust safety-constrained predefined-time control law is designed with a twofold structure, where the nominal control term guarantees the predefined-time convergence under the safety constraints, and the adjunctive control term overcomes the influence of disturbances. A new dynamic parameter-based predefined-time control method is proposed, which can relax the unnecessary requirement of control design for achieving predefined-time convergence. The corresponding dynamic parameter-based predefined-time control Lyapunov function (DPP-CLF) is constructed together with second-order control barrier function (SCBF) to map the convergence requirement and safety constraints on states to constraints on control inputs. The nominal control term is obtained by minimizing the control inputs under constraints with linear programming. The adjunctive control term is acquired by combining a filter-based estimator and an integral sliding mode surface design, providing an accurate compensation for the disturbances. The theoretical analysis and simulation results demonstrate the predefined-time stability and collision avoidance performance of the multi-UAV system. IEEE

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Soft Sensor of Effluent Ammonia Nitrogen Concentration Based on Modular Stochastic Configuration Networks

Soft Sensor of Effluent Ammonia Nitrogen Concentration Based...

引用

International Conference on Industrial Artificial intelligence (IAI)

作者： Kang Li Cui-Li Yang Da-Peng Li Jun-Fei Qiao Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing University of Technology Beijing China

This paper proposes a soft sensing method based on a brain-inspired modular stochastic configuration network for the real-time and accurate measurement of effluent ammonia nitrogen concentration in wastewater treatment processes. This method first uses grey relational analysis to extract the main variables affecting the effluent ammonia nitrogen concentration. Then, based on the fuzzy clustering method, the task is decomposed to alleviate the complexity of each modeling task. After that, following the principle of divide and conquer, a corresponding stochastic configuration network sub-model is constructed for each sub-task, and the results of each sub-model are integrated to improve the measurement performance of effluent ammonia nitrogen concentration. Finally, the effectiveness and accuracy of the proposed method are verified by simulation based on actual water quality data.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Learning Dense Visual Object Descriptors to Fold Two-Dimensional Deformable Fabrics

Learning Dense Visual Object Descriptors to Fold Two-Dimensi...

引用

IEEE International Conference on Cyber Technology in Automation, Control, and intelligent systems

作者： Yang Cao Daoxiong Gong Jianjun Yu Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing University of Technology Beijing China

Manipulating two-dimensional fabrics is a significant research field in recent years. Fabric manipulation presents a formidable challenge due to the intricate dynamics and high-dimensional state space inherent in the process, prior research has predominantly relied on robot learning of task-specific strategies as a means to effectively accomplish the corresponding fabric manipulation tasks. In this work, we utilize dense visual object descriptors trained on synthetic RGB images to learn visual representations for two-dimensional fabrics. Based on the learned descriptors, the robot can learn the correspondences of similar fabrics in different configurations. We apply a novel Siamese network architecture to improve the quality of learned descriptors for three types of fabrics, including square fabrics, T-shirts and shorts. By utilizing the learned descriptors, the equivalent actions in an unknown configuration can be computed based on a fabric folding demonstration in an initial configuration. We perform a series of fabric folding tasks in different colors, sizes and shapes. The policy can achieve 87.7% average task success rate across 7 different folding tasks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An IT2FNN with a Novel Hierarchical Learning Algorithm for Nonlinear system Modeling

An IT2FNN with a Novel Hierarchical Learning Algorithm for N...

引用

Chinese Automation Congress (CAC)

作者： Zijian Sun Xi Meng Junfei Qiao Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing University of Technology Beijing China

Interval type-2 fuzzy neural networks (IT2FNNs) have been widely used for modeling in industrial processes, and the efficient parameter learning methods are crucial for obtaining accurate models. However, the problem of low computational efficiency and poor convergence performance still exists in existing learning methods. In this study, a novel hierarchical learning algorithm is proposed for constructing IT2FNN with better learning ability and generalization performance. Firstly, the improved recursive least square (RLS) method with an adaptive forgetting factor is designed to learn the consequent parameters. Next, the advanced stochastic gradient descent (SGD) method is adopted to learn the antecedent parameters. Finally, the proposed method is applied to real industrial processes and compared with various state-of-the-art IT2FNNs. Simulation results demonstrate the superiority of the proposed method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Missing-Pattern-Aware-Based Multi-Model Imputation Method for Wastewater Treatment Process

Missing-Pattern-Aware-Based Multi-Model Imputation Method fo...

引用

IEEE International Conference on Cyber Technology in Automation, Control, and intelligent systems

作者： Meiting Sun Honggui Han Fangyu Li Faculty of Information Technology and Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing University of Technology Beijing China

In wastewater treatment process (WWTP), data-based implement techniques ensure the stable operation and reduce energy consumption. Different missing patterns of missing values often occur due to some harsh environments and sensor failures. However, existing imputation methods are difficult to obtain satisfactory data for implementation techniques as they only consider a single missing pattern. To solve this problem, a missing-pattern-aware-based multi-model imputation method (MPAMI) is proposed. First, a missing pattern aware network combining the advantages of the encoder and the axial attention mechanism is designed to identify different missing patterns. The network employs the encoder to extract nonlinear feature representations and utilizes the axial attention mechanism to focus on the most informative differential features. Second, a hybrid multi-model imputation method based on the long short-term memory network and the denoising autoencoder is developed to recover missing values. The imputation method utilizes the spatiotemporal information of missing patterns to improve imputation performance. Finally, experiments are conducted on a real WWTP dataset to validate the imputation performance of the proposed MPAMI.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Parallel systems Framework: A Safe and Efficient Testbed for Unmanned Ships 4

Parallel Systems Framework: A Safe and Efficient Testbed for...

引用

4th IEEE International Conference on Digital Twins and Parallel intelligence, DTPI 2024

作者： Fu, Long Shen, Zhen Dong, Xisong Han, Yunjun Yang, Shuguang Xiong, Gang Wang, Fei-Yue University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Beijing100190 China Chinese Academy of Sciences Guangdong Engineering Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Dongguan523808 China Shandong Jiaotong University Schoool of Rail Transportation Jinan250399 China Chinese Academy of Sciences State Key Laboratory for Management and Control for Complex Systems Institute of Automation Beijing100190 China

ISBN: (纸本)9798350349252

In this study, unmanned ships test platform based on the parallel systems framework is proposed to improve the test efficiency and accuracy of unmanned ships in complex ocean environment. The parallel intelligence theory and ACP approach, the efficient interaction between virtual and real environment is achieved, which provides more comprehensive and accurate data for unmanned ships testing. Future research will further expand the scope of virtual environment simulation and improve systems accuracy and response speed to a wider range of unmanned ships test requirements. © 2024 IEEE.

关键词： Virtual environments

来源：评论

学校读者我要写书评

暂无评论

Dynamics Modeling with Realistic Constraints for Trajectory Tracking Control of Manipulator∗

Dynamics Modeling with Realistic Constraints for Trajectory ...

引用

2022 IEEE International Conference on Real-Time computing and Robotics, RCAR 2022

作者： Liu, Lu Zuo, Guoyu Li, Jiangeng Li, Jianfeng Beijing Key Laboratory of Computing Intelligence and Intelligent Systems Beijing100124 China Beijing University of Technology Faculty of Materials and Manufacturing Beijing100124 China Faculty of Materials and Manufacturing Beijing University of Technology Beijing100124 China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

To meet the practical operation requirements of manipulators in industry, service and collaboration scenarios, trajectory tracking accuracy and system stability of manipulators are usually regarded as critical control objectives. This paper proposes a novel manipulator control method with three-level constraints, called the real deep Lagrangian network (Real-DeLaN). In this method, real data (also called physical data) are collected from the physical manipulator and utilized to train the Lagrangian dynamics network model to improve the migration ability from simulation to reality. The torque output of the dynamic model is corrected by the real-Time calculation of friction in the network. The contact force on the end effector of the manipulator is compensated based on the principle of virtual displacement work. The experimental results show that Real-DeLaN can better control the joints to perform trajectory tracking, reduce the friction error of the manipulator, and show better anti-interference ability. © 2022 IEEE.

关键词： Manipulators

来源：评论

学校读者我要写书评

暂无评论

An Efficient Lightweight Spatio-temporal Attention Module for Action Recognition 11

An Efficient Lightweight Spatio-temporal Attention Module fo...

引用

11th International Conference on computing and Pattern Recognition, ICCPR 2022

作者： Sun, Zhonghua Dai, Meng Yi, Ziwen Wang, Tianyi Feng, Jinchao Jia, Kebin Faculty of Information Technology Beijing University of Technology Beijing Laboratory of Advanced Information Networks Beijing China Faculty of Information Technology Beijing University of Technology China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing University of Technology China

ISBN: (纸本)9781450397056

Effective feature learning is one of the prime components for human action recognition algorithm. Three-dimensional convolutional neural network (3D CNN) can directly extract spatio-temporal features, however it is insufficient to capture the most discriminative part of the action video. The redundant spatial regions within and between temporal frames would weak the descriptive ability of the 3D CNN model. To address this problem, we propose a lightweight spatio-temporal attention module (ST-AM), composed of spatial attention module (SAM) and temporal attention module (TAM). SAM and TAM can effectively encode the semantic spatial areas and suppress the redundant temporal frames to reduce misclassification. The proposed SAM and TAM have complementary effects and can be easily embedded into the existing 3D CNN action recognition model. Experiment on UCF-101 and HMDB-51 datasets shows that the ST-AM embedded model achieves impressive performance on action recognition task. © 2022 ACM.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

An improved stable motion control method for quadruped robot based on CPG and VMC

An improved stable motion control method for quadruped robot...

引用

Chinese Control and Decision Conference, CCDC

作者： Tingdong Ji Xiaoqing Zhu Xiaogang Ruan Borui Nan Lanyue Bi Xiaoyu Zhu Department of Information Beijing University of Technology Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

The gait control of a quadruped robot is the key to the robot's movement in complex terrain. In order to realize the stable motion of the quadruped robot on special terrains such as slopes, the hopf oscillator is used as the central mode generator to control the gait of the quadruped robot. The output of the oscillator is converted into the trajectory of the foot, the trajectory of the foot is adjusted by sensory feedback, the gait phase is switched by detecting the pressure of the foot, and the virtual model is used to control the movement of the foot along the given trajectory to achieve Stable motion of a quadruped robot. The simulated quadruped robot is built on the WEBOTS platform and verified by experiments. The results show that the improved gait controller can achieve smooth and compliant motion for the quadruped robot on flat ground and slopes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Variational Clustering and Denoising of Spatial Transcriptomics

Variational Clustering and Denoising of Spatial Transcriptom...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Li, Cuiyuan Zhang, Fa Hu, Kai Cui, Xuefeng Shandong University School of Computer Science and Technology Qingdao China Beijing Institute of Technology School of Medical Technology Beijing China Xiangtan University Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan China Xiangnan University Key Laboratory of Medical Imaging and Artificial Intelligence of Hunan Province Chenzhou China

ISBN: (纸本)9798350337488

Spatial transcriptomics data provides a unique opportunity to investigate both gene expression and spatial structure in tissues at the same time. However, incorporating spatial information to accurately identify spatial domains is difficult due to factors such as high-dimensionality, sparsity, noise, and dropout events. To address these issues, we introduce vGraphST, a novel graph-based deep learning approach tailored for spatial transcriptomics data. Our method combines auto-encoder and contrastive learning techniques to process high-dimensional data and generate meaningful low-dimensional embeddings. Additionally, we use continuous distributions instead of discrete values in both the latent space and the denoised gene expression space. Specifically, Gaussian distributions are used to model the latent space, while zero-inflated Poisson distributions are used to model the denoised gene expression space. Experimental results demonstrate the effectiveness of vGraphST in accurately representing and analyzing spatial transcriptomics data. When compared to other methods using the DLPFC dataset, vGraphST achieves an average Adjusted Rand Index (ARI) of 0.58, demonstrating its superiority in segmenting spatial domains and recognizing biologically relevant spatiotemporal patterns. © 2023 IEEE.

关键词： clustering contrastive learning denoising spatial transcriptomics variational auto-encoder

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：