检索结果-内蒙古大学图书馆

International Youth Conference on Energetics (IYCE)

作者： Nanyang Zhu Kaifeng Zhang Ying Wang Huiping Zheng Yanxia Pan Xueting Cheng Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing Jiangsu China State Grid Shanxi Electric Power Research Institute Shanxi China State Grid Shanxi Electric Power Company Shanxi China

ISBN: (数字)9798350372380

ISBN: (纸本)9798350372397

It is significant and challenging to forecast wind power through the knowledge learned from the historical meteorological variables and wind power itself. So far, this knowledge has been learned based on supervised learning, which is insufficient in capturing semantic dependencies between variables and cannot provide a stability model. This work proposed an unsupervised representation learning-based short-term wind power prediction method using sequences contrastive technique. This representation learning model is mainly composed of the input encoder module, feature extraction module, contrastive learning module, and regression module. The feature extraction module which fuses multiple encoders can extract abundant feature vectors from the multi-source embedding of the input encoder module. The loss function in the contrastive learning module attempts to distinguish positive pairs and negative pairs that are generated from the feature extraction module. Eventually, the regression model uses the fully learned representation matrix for the power estimation. In order to explore the feasibility of this method in wind power prediction, the benefits under different prediction intervals are studied separately through some classic evaluation criteria, and comparing the proposed representation learning-based forecasting with other state-of-the-art methods. The results show that the knowledge learned from this model can generate improved performance with reliability and effectiveness with a 6-hour prediction horizon, and allow the development of short-term wind power forecast.

关键词： Representation learning Supervised learning Stability criteria Contrastive learning Wind power generation Predictive models Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Maximum power point tracking of photovoltaic array based on improved Particle Swarm Optimization Algorithm 4

Maximum power point tracking of photovoltaic array based on ...

引用

2022 4th International Conference on Energy systems and Electrical Power, ICESEP 2022

作者： Lai, GuangZhi Li, HaoRan Zhang, ChangZhi Zhang, YiHao Wang, ZhiJin State Grid e-commerce Co. Ltd Beijing10053 China State Grid Tianjin Electric Power Company China School of Automation Southeast University Jiangsu Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

With the vigorous development of the photovoltaic industry, how to improve the efficiency of photovoltaic power generation has become an important issue, among which partial shadow occlusion is an important reason affecting the efficiency. The efficiency of photovoltaic power generation can be effectively improved by adopting the maximum power point tracking method (MPPT), but the traditional MPPT method is not ideal in the partial shadow occlusion of the photovoltaic array. To solve this problem, this paper proposes an improved particle swarm optimization method to effectively improve the tracking efficiency of MPPT when multiple peaks appear in the photovoltaic arrays power curve (P-V) under the partial shadow. The proposed method improves the learning factor of the traditional particle swarm optimization algorithm and designs the initial position of the particles according to the characteristics of the photovoltaic array. By adding the particle elimination mechanism, the number of particles changes dynamically, and the tracking speed of the algorithm for the maximum power of the photovoltaic array is improved. Through the result of the simulation, it is not difficult to get the conclusion that the improved particle swarm optimization algorithm can effectively improve the performance of the photovoltaic system under partial shadows. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Efficiency

来源：评论

学校读者我要写书评

暂无评论

Attributes Grouping and Mining Hashing for Fine-Grained Image Retrieval

arXiv

引用

arXiv 2023年

作者： Lu, Xin Chen, Shikun Cao, Yichao Zhou, Xin Lu, Xiaobo School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Nanjing Enbo Technology Co. Ltd. Nanjing China

In recent years, hashing methods have been popular in the large-scale media search for low storage and strong representation capabilities. To describe objects with similar overall appearance but subtle differences, more and more studies focus on hashing-based fine-grained image retrieval. Existing hashing networks usually generate both local and global features through attention guidance on the same deep activation tensor, which limits the diversity of feature representations. To handle this limitation, we substitute convolutional descriptors for attention-guided features and propose an Attributes Grouping and Mining Hashing (AGMH), which groups and embeds the category-specific visual attributes in multiple descriptors to generate a comprehensive feature representation for efficient fine-grained image retrieval. Specifically, an Attention Dispersion Loss (ADL) is designed to force the descriptors to attend to various local regions and capture diverse subtle details. Moreover, we propose a Stepwise Interactive External Attention (SIEA) to mine critical attributes in each descriptor and construct correlations between fine-grained attributes and objects. The attention mechanism is dedicated to learning discrete attributes, which will not cost additional computations in hash codes generation. Finally, the compact binary codes are learned by preserving pairwise similarities. Experimental results demonstrate that AGMH consistently yields the best performance against state-of-the-art methods on fine-grained benchmark datasets. Copyright © 2023, The Authors. All rights reserved.

关键词： Hash functions

来源：评论

学校读者我要写书评

暂无评论

Attentive online sequential extreme learning machine for nonlinear dynamic process monitoring

Attentive online sequential extreme learning machine for non...

引用

第34届中国过程控制会议

作者： Jingxin Zhang Yuying Cao Hai Zhou Department of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of EngineeringMinistry of Education Department of Automation Southeast University New Energy Research Center China Electric Power Research Institute

This paper provides a new monitoring method based on the attention mechanism and online sequential extreme learning machines(OS-ELM) for nonlinear dynamic process,referred as attentive ***-ELM provides the prediction of outputs and the update of parameters by sequential *** cope with nonlinearity,the attention mechanism is utilized to map data to a high-dimensional feature *** effect of the attention mechanism and the single hidden layer feedforward network trained with OS-ELM work collaboratively in monitoring the real-time process data to detect possible *** addition,fault detection rate and false alarm rate are adopted to evaluate the monitoring *** effectiveness of the proposed method is illustrated by a typically complicated industrial system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Heterogeneous Multi-Robot Cooperative Welding Task Allocation Based on Task-Centered Optimization: An Industrial Case Study

SSRN

引用

SSRN 2023年

作者： Liu, Wenbo Kuang, Zhian Zhou, Bo Li, Shihua School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Shanghai Friendess Electronic Technology Shanghai201100 China

In this article, the complex task assignment, schedu.ing and planning of complex heterogeneous multi-robot welding process are studied. For large workpiece welding tasks that involve complex heterogeneous multi-robot task allocation under different internal and external constraints, the traditional multi-robot task allocation (MRTA) framework is extended to a novel and unified heterogeneous multi-robot (H-MRTA) framework, and a hierarchical optimization algorithm is proposed. Firstly, an optimization model based on the H-MRTA framework is established. Taking into account constraints such as accessibility, collision and welding process, the optimization objectives are formulated by combining the total welding time and the task balance between robots. Then, to obtain the optimal solution, a stepwise optimization algorithm is devised to solve the MRTA problem from top to bottom in two layers: working area division problem and multi-robot path planning problem. For the working area division problem, a task-centered optimization model is proposed, which aims to balance the workload among robots, and is solved by branch-and-bound method. For the multi-robot path planning problem, multiple process constraints are considered and the total working time is minimized as the objective function. The effectiveness of the optimization algorithm is verified by a case study on the welding task of a large plate element in a ship hull. compared to two other state-of-the-art algorithms, the proposed optimization algorithm achieves a task allocation scheme with a shorter welding time, a shorter waiting time and a higher welding productivity, which demonstrates the effectiveness and feasibility of the stepwise optimization-based task allocation algorithm for complex heterogeneous multi-robot. © 2023, The Authors. All rights reserved.

关键词： Industrial robots

来源：评论

学校读者我要写书评

暂无评论

Adaptive Sliding Mode control for Force Tracking Using Nonlinear Observer

Adaptive Sliding Mode Control for Force Tracking Using Nonli...

引用

第34届中国控制与决策会议

作者： Linyan Han Haibo Du Shihua Li School of Automation Southeast UniversityKey Laboratory of Measurement and Control of Complex Systems of EngineeringMinistry of Education School of Electrical Engineering and Automation Hefei University of Technology

This paper focuses on the development of a control scheme capable of tracking contact forces ***,the nonlinear observer,admittance control and adaptive sliding mode control are integrated into a single *** the force sensor is absent,a nonlinear observer,which serves as a reaction force observer,can be used to estimate the contact ***,in order to track the force profile explicitly,admittance control is introduced to transform the desired contact force into the desired position *** adaptive sliding mode controller is designed to track the desired position and meanwhile compensate the estimation errors of contact forces caused by nonlinear *** stability of the whole system under the proposed controller can be guaranteed by the Lyapunov ***,several simulations are reported to demonstrate the effectiveness of the proposed approach.

关键词： Lyapunov Adaptive Sliding Mode control for Force Tracking Using Nonlinear Observer

来源：评论

学校读者我要写书评

暂无评论

Circular Formation Flight control for Unmanned Aerial Vehicles With Directed Network and External Disturbance

引用

IEEE/CAA Journal of Automatica Sinica 2020年第2期7卷 505-516页

作者： Yangyang Chen Rui Yu Ya Zhang Chenglin Liu School of Automation and Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China School of Automation Southeast UniversityNanjing 210096China Key Laboratory of Advanced Process Control for Light Industry Ministry of EducationInstitute of AutomationJiangnan UniversityWuxi 214122China

This paper proposes a new distributed formation flight protocol for unmanned aerial vehicles(UAVs)to perform coordinated circular tracking around a set of circles on a target *** from the previous results limited in bidirectional networks and disturbance-free motions,this paper handles the circular formation flight control problem with both directed network and spatiotemporal disturbance with the knowledge of its upper *** from the design of a common Lyapunov fiunction for bidirectional cases,we separately design the control for the circular tracking subsystem and the formation keeping subsystem with the circular tracking error as *** the whole control system is regarded as a cascade connection of these two subsystems,which is proved to be stable by input-tostate stability(ISS)*** the purpose of encountering the external disturbance,the backstepping technology is introduced to design the control inputs of each UAV pointing to North and Down along the special sphere(say,the circular tracking control algorithm)with the help of the switching ***,the distributed linear consensus protocol integrated with anther switching anti-interference item is developed to construct the control input of each UAV pointing to east along the special sphere(say,the formation keeping control law)for formation *** validity of the proposed control law is proved both in the rigorous theory and through numerical simulations.

关键词： Directed network external disturbance flight control unmanned aerial vehicles(UAVs)

来源：评论

学校读者我要写书评

暂无评论

Enabling few-shot learning with PID control: a layer adaptive optimizer 24

Enabling few-shot learning with PID control: a layer adaptiv...

引用

Proceedings of the 41st International Conference on Machine Learning

作者： Le Yu Xinde Li Pengfei Zhang Zhentong Zhang Fir Dunkin School of Automation Southeast University Nanjing China and Nanjing Center for Applied Mathematics Nanjing China and Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China School of Automation Southeast University Nanjing China and Nanjing Center for Applied Mathematics Nanjing China and Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China and Southeast University Shenzhen Research Institute Shenzhen China School of Automation Southeast University Nanjing China and Nanjing Center for Applied Mathematics Nanjing China

Model-Agnostic Meta-Learning (MAML) and its variants have shown remarkable performance in scenarios characterized by a scarcity of labeled data during the training phase of machine learning models. Despite these successes, MAMLbased approaches encounter significant challenges when there is a substantial discrepancy in the distribution of training and testing tasks, resulting in inefficient learning and limited generalization across domains. Inspired by classical proportional-integral-derivative (PID) control theory, this study introduces a Layer-Adaptive PID (LA-PID) Optimizer, a MAML-based optimizer that employs efficient parameter optimization methods to dynamically adjust task-specific PID control gains at each layer of the network, conducting a first-principles analysis of optimal convergence conditions. A series of experiments conducted on four standard benchmark datasets demonstrate the efficacy of the LA-PID optimizer, indicating that LA-PID achieves state-of-the-art performance in few-shot classification and cross-domain tasks, accomplishing these objectives with fewer training steps. Code is available on https://***/yuguopin/LA-PID.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Asymptotic Stabilization of Time-Varying Delay System with Actuator Saturation via Multi-dimensional Taylor Network

Asymptotic Stabilization of Time-Varying Delay System with A...

引用

International Conference on Robotics and Automation engineering (ICRAE)

作者： Guo-Biao Wang Hong-Sen Yan School of Automation Southeast University Nanjing Jiangsu China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing Jiangsu China

This paper addresses the stabilization problem of time-varying delay systems subject to actuator saturation. A novel class of Lyapunov functional with a nonlinear metric is developed to guarantee that there exists a Lyapunov-Razumikhin function that strictly decreases for the controlled system. Such a nonlinear metric is parameterized by a multi-dimensional Taylor network with concise topology, which brings into the high-order dynamic information and guarantees real-time performance. A sum-of-squares programming approach based on the designed Lyapunov functional is formulated to dedu.e the stability criteria, which maximizes the estimate of the region of attraction and ensures the uniform asymptotic stability of the closed-loop system theoretically. A numerical example demonstrates the effectiveness of the proposed stabilization control scheme.

关键词： measurement Actuators Asymptotic stability Delay systems Stability criteria Programming Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Probabilistic Decomposition Transformer for Time Series Forecasting

SSRN

引用

SSRN 2022年

作者： Tong, Junlong Xie, Liping Yang, Wankou Zhang, Kanjian School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing 210096 China

Time series forecasting is crucial for many fields, such as disaster warning, weather prediction, and energy consumption. The Transformer-based models are considered to have revolutionized the field of sequence modeling. However, the complex temporal patterns of the time series hinder the model from mining reliable temporal dependencies. Furthermore, the autoregressive form of the Transformer introduces cumulative errors in the inference step. In this paper, we propose the probabilistic decomposition Transformer model that combines the Transformer with a conditional generative model, which provides hierarchical and interpretable probabilistic forecasts for intricate time series. The Transformer is employed to learn temporal patterns and implement primary probabilistic forecasts, while the conditional generative model is used to achieve non-autoregressive hierarchical probabilistic forecasts by introducing latent space feature representations. In addition, the conditional generative model reconstructs typical features of the series, such as seasonality and trend terms, from probability distributions in the latent space to enable complex pattern separation and provide interpretable forecasts. Extensive experiments on several datasets demonstrate the effectiveness and robustness of the proposed model, indicating that it compares favorably with the state of the art. © 2022, The Authors. All rights reserved.

关键词： Time series

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：