检索结果-内蒙古大学图书馆

Adaptive output regulation for two coupled anti-stable strings with unknown exosystem

ESAIM - control, Optimisation and Calculus of Variations 2025年 31卷

作者： Guo, Bao-Zhu Hu, Qing-Qing Jin, Feng-Fei School of Mathematics and Physics North China Electric Power University Beijing102206 China Academy of Mathematics and Systems Science Academia Sinica Beijing100190 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China School of Mathematics and Statistics Shandong Normal University Jinan250358 China

This paper investigates non-collocated boundary output regulation for two interconnected anti-stable string systems, where external disturbances infiltrate the plant from both the spatial domain and the boundaries. The reference signal and disturbances originate from an unknown finite-dimensional exosystem. First, we design a state feedback controller using the backstepping transformation. Second, a Sylvester equation is employed to redirect disturbances from all channels to the output end. The exosystem is then transformed into an observable canonical form. Subsequently, an adaptive observer is developed, facilitating the design of a tracking error feedback controller that incorporates an adaptive internal model. We prove that the internal signals within the closed-loop system remain bounded, and the output signal successfully tracks the reference signal. Finally, the efficacy of our proposed scheme is verified through numerical simulations. © The authors. Published by EDP sciences, SMAI 2025.

关键词： State feedback

来源：评论

学校读者我要写书评

暂无评论

Underwater Sensor Network Clock Synchronization Algorithm Based on Markov Chain Group Consistency

引用

Ruan Jian Xue Bao/Journal of Software 2019年 30卷 27-39页

作者： Wei, Lian-Suo Su, Yang Li, Hua Wu, Di School of Computer and Control Engineering Qiqihar University Qiqihar161006 China School of Computing Science and Technology Harbin Engineering University Harbin150001 China

Most of the existing UWSNs clock synchronization algorithms use nodes to exchange data frequently, but neglect the synchronization information received by neighbor nodes within the scope of node-based communication, so there are some problems such as high energy consumption and low synchronization efficiency in synchronization communication, which affect the accuracy of network clock synchronization. Therefore, based on the analysis of the influence of UWSNs multi-objective optimization network topology evolution process on clock synchronization, this paper uses the theory of group consistency and Markov chain to establish the synchronization cycle regulation mechanism and clock synchronization model without too much increase of the average transmission radius and communication energy consumption. Then, using linear regression fitting method, the inter-cluster synchronization and intra-cluster synchronization are established. Finally, the performance of UWSNs clock synchronization algorithm is verified by simulation. © Copyright 2019, Institute of Software, the Chinese Academy of sciences. All rights reserved.

关键词： Synchronization

来源：评论

学校读者我要写书评

暂无评论

A Process Tree-Based Incomplete Event Log Repair Approach

引用

Information 2025年第5期16卷 390-390页

作者： Qiushi Wang Liye Zhang Rui Cao Na Guo Haijun Zhang Cong Liu School of Computer Science and Technology Shandong University of Technology Zibo 255049 China School of Information and Control Engineering Qingdao University of Technology Qingdao 266520 China Jinan Inspur Technology Co. Ltd. Jinan 250101 China NOVA Information Management School Nova University of Lisbon 1099-085 Lisbon Portugal

The low quality of business process event logs—particularly the widespread occurrence of incomplete traces—poses significant challenges to the reliability, accuracy, and efficiency of process mining analysis. In real-world scenarios, these data imperfections severely undermine the practical value of process mining techniques. The primary research problem addressed in this study is the inefficiency and limited effectiveness of existing Petri-net-based incomplete trace repair approaches, which often struggle to accurately recover missing events in the presence of complex and nested loop structures. To tackle these limitations, we aim to develop a faster and more accurate approach for repairing incomplete event logs. Specifically, we propose a novel repair approach based on process trees as an alternative to traditional Petri nets, thus alleviating issues such as state space explosion. Our approach incorporates process tree model decomposition and innovative branch indexing techniques, enabling rapid localization of candidate branches for repair and a significant reduction in the solution space. Furthermore, by leveraging activity information within the traces, our approach achieves efficient and precise repair of loop nodes through a single traversal of the process tree. To comprehensively evaluate our approach, we conduct experiments on four real-life and five synthetic event logs, comparing performance against state-of-the-art techniques. The experimental results demonstrate that our approach consistently delivers repair accuracies exceeding 70%, with time efficiency improved by up to three orders of magnitude. These findings validate the superior accuracy, efficiency, and scalability of the proposed approach, highlighting its strong potential for practical applications in business process mining.

关键词： process mining process tree incomplete trace repair event log

来源：评论

学校读者我要写书评

暂无评论

Retraction Note: Automated screening of congestive heart failure using variational mode decomposition and texture features extracted from ultrasound images

引用

Neural Computing and Applications 2024年第18期36卷 1-1页

作者： Raghavendra, U. Acharya, U. Rajendra Gudigar, Anjan Shetty, Ranjan Krishnananda, N. Pai, Umesh Samanth, Jyothi Nayak, Chaithra Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal University Manipal India Department of Electronics and Computer Engineering Ngee Ann Polytechnic Singapore Singapore Department of Biomedical Engineering School of Science and Technology SIM University Singapore Singapore Department of Biomedical Engineering Faculty of Engineering University of Malaya Kuala Lumpur Malaysia Department of Cardiology Kasturba Medical College and Hospital Manipal University Manipal India Department of Cardiovascular Technology School of Allied Health Sciences Manipal University Manipal India

来源：评论

学校读者我要写书评

暂无评论

Expectation Maximization Based FitzHugh-Nagumo Model Identification Under Unknown Gaussian Measurement Noise

Expectation Maximization Based FitzHugh-Nagumo Model Identif...

引用

Chinese control and Decision Conference, CCDC

作者： Li-Hui Geng Terefe Bayisa Ayele Jin-Cang Liu Brett Ninness Tianjin Key Laboratory of Information Sensing and Intelligent Control School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China School of Electrical Engineering and Computer Science The University of Newcastle Callaghan NSW Australia

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

This paper applies a new expectation maximization (EM) based identification method to estimate a generic FitzHugh-Nagumo (FHN) model under unknown Gaussian measurement noise. It is well noted that such FHN model is an elementary neuronal dynamics description and plays a significant role in deep understanding and basic analysis for complicated mechanisms of some neural diseases. Different from the most existing relevant identification methods, the applied new method is additionally capable of supplying users with variance estimation for the unknown measurement noise corrupting on the membrane potential apart from model parameter estimates. All unknown parameters can be iteratively estimated by a particle smoothing based EM algorithm, which consists of an expectation (E) step and a maximization (M) step. Smoothed joint-state particles are produced by a new particle smoothing algorithm to evaluate an expectation of a log-likelihood function in the E step, and the model parameters and noise variance can then be efficiently optimized by the gradient based methods in the M step. The resulting estimations own global convergence for a relatively wide range of parameter initializations. Finally, good convergence behaviors of the estimated model parameters and noise variance are demonstrated by a numerical simulation for a classic FHN model by using 10 simulation realizations with random initializations varying within ±100% of their respective true values.

关键词： Estimation Computational modeling Smoothing methods Numerical models Kalman filters Noise measurement Integrated circuit modeling

来源：评论

学校读者我要写书评

暂无评论

An Encoder-Decoder Network with Residual Convolution for Leukocyte Image Segmentation

An Encoder-Decoder Network with Residual Convolution for Leu...

引用

International Conference on Information science and control engineering (ICISCE)

作者： Yuanyuan Chen Shenghua Teng Zuoyong Li Fuquan Zhang Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China College of Electronics and Information Engineering Shandong University of Science and Technology Qingdao China Fuzhou Digital Healthcare Industry Technology Innovation Center Fuzhou China

The appearance analysis and counting of peripheral blood leukocytes can assist the diagnosis of blood diseases such as leukemia. Therefore, it is necessary to automatically extract leukocytes from blood smear images. In this paper, we propose an end-to-end peripheral blood leukocyte image segmentation method based on fully convolutional neural network, which can not only encode multi-scale contextual information, but also capture clear boundary information through decoding. Specifically, the proposed method first utilizes the context-aware feature encoder with residual convolutions to extract a set of multi-scale features. Then, a refinement module of parallel dilated convolutions with multiple dilation rates for expanding the receptive field of the feature maps is introduced to aggregate contextual information. Finally, clear prediction results are reconstructed by the context-aware feature decoder and skip connections. We demonstrate the effectiveness of the proposed method on two publicly available datasets.

关键词： Deep learning Image segmentation Information science Aggregates Feature extraction Decoding Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Model-based Dependability Analysis of Fault-tolerant Inertial Navigation System: A Practical Experience Report

引用

IFAC-PapersOnLine 2019年第12期52卷 394-399页

作者： Mikael Steurer Andrey Morozov Klaus Janschek Klaus-Peter Neitzke Faculty of Electrical Engineering Automatic Control and Informatics Institute of Computer Science Opole University of Technology Poland

Model-based systems engineering approaches are commonly used to develop safetycritical mechatronic systems. Recently, a new SysML-based method for the dependability analysis of Unmanned Aerial Vehicles (UAVs) has been introduced. The method consists of three main steps: (i) creation of a structural SysML model using building blocks from the underlying UAV dependability profile that extends the model with block-level reliability and time properties, (ii) transformation of the semi-formal SysML model into a formal Dual-Graph Error Propagation Model (DEPM) that captures relevant structural and behavioral properties of the system, (iii) DEPM-based evaluation of system dependability metrics using Markov chain models and state-of-the-art probabilistic model checking techniques. This paper describes the practitioner experiences and lessons learned after the application of the aforementioned method to a sophisticated real-world embedded fault-tolerant inertial navigation system. The case study revealed two particular limitations that have been overcome by the optimization of the method against the state-space explosion of underlying Markov chain models and the introduction of a new computation algorithm for DEPMs with realistic extremely low fault activation probabilities.

关键词： system analysis design systems architecture reliability engineering dependability SysML Markov chains microsensors space technology

来源：评论

学校读者我要写书评

暂无评论

Distributed Coordinated Emergency Frequency control Strategy for Renewables-Rich Power Systems Based on Multi-Agent Reinforcement Learning

SSRN

引用

SSRN 2025年

作者： Sun, Zhenglong Han, Junpeng Chen, Weihan Zhang, Rui Liu, Yong Levron, Yoash Belikov, Juri Department of Electrical Engineering Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering Technion—Israel Institute of Technology Haifa3200003 Israel Department of Software Science Tallinn University of Technology Akadeemia Tee 15a Tallinn12618 Estonia

With the rapid growth of renewable energy in the power system and the implementation of large-capacity LCC-HVDC projects, the frequency support capability of the grid has been reduced. Simultaneously, the renewables-rich grid faces the risk of high-power shocks due to LCC-HVDC blocking. Existing centralized, single-measure approaches and the model-based emergency frequency control (EFC) methods are facing tremendous challenges. To fill this gap, this paper proposes a frequency emergency control method for renewables-rich grids that coordinates LCC-HVDC emergency power support and load shedding. The coordination of the two stabilization measures is modeled as a decentralized partially observable Markov decision process, and a multi-agent reinforcement learning (MADRL) approach is employed to optimize the power of measures for each stabilization control substation. An MADRL algorithm that integrates the system frequency response model is developed to overcome the problem of inaccurate evaluation of centralized action value in the MADRL algorithm used for EFC. This approach allows for the global optimization of the distributed coordination strategy through centralized training. The effectiveness and adaptability of the proposed method are demonstrated through simulations of the modified IEEE 39-bus system. © 2025, The Authors. All rights reserved.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Model based reinforcement learning for robot grasping trajectory generation 4

Model based reinforcement learning for robot grasping trajec...

引用

4th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2019

作者： Xue, Hongxiang Wen, Shuhuan Yang, Chao Liu, Huaping Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China Department of Computer Science and Technology State Key Laboratory of Intelligent Technology and System Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing100084 China

ISBN: (纸本)9781728100647

Trajectory generation is a fundamental problem for successful robotic grasping. However, most of the existing work dealt with this problem using supervised learning with a prescribed model. It prevents the developed grasp strategies from being used for new unknown scenarios. In this paper, inspired by the success of the reinforcement learning method, we developed a new method which optimizes grasp trajectories using a policy search method. An important advantage of the proposed method is that the complicated 3D model could be used to generate the multi-dimensional grasp configurations. The developed algorithm has been validated on some typical robotic hand. The experimental results show that the proposed method achieves excellent performance. © 2019 IEEE.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

Colour-weighted rank transform and improved dynamic programming for fast and accurate stereo matching

引用

The Journal of Photographic science 2024年第2期72卷

作者： Mohamed Hallek Randa Khemiri Ali Aseere Abdellatif Mtibaa Mohamed Atri a Laboratory of Electronics and Microelectronics University of Monastir Monastir Tunisia b Networked Objects Control and Communication Systems Laboratory ENISO Sousse University Sousse Tunisia c College of Computer Science King Khalid University Abha Saudi Arabia d National Engineering School of Sfax University of Sfax Sfax Tunisia

ABSTRACTReal-time stereo matching with high accuracy is a dynamic research topic; it is attractive in diverse computer vision applications. This paper presents a stereo-matching algorithm that produces high-quality disparity map while maintaining real-time performance. The proposed stereo-matching method is based on three per-pixel difference measurements with adjustment elements. The absolute differences and the gradient matching are combined with a colour-weighted extension of complete rank transform to reduce the effect of radiometric distortion. The disparity calculation is realized using improved dynamic programming that optimizes along and across all scanlines. It solves the inter-scanline inconsistency problem and increases the matching accuracy. The proposed algorithm is implemented on parallel high-performance graphic hardware using the Compute Unified Device Architecture to reach over 240 million disparity evaluations per second. The processing speed of our algorithm reaches 98 frames per second on 240 × 320-pixel images and 32 disparity levels. Our method ranks fourth in terms of accuracy and runtime for quarter-resolution images in the Middlebury stereo benchmark.

关键词： Cost function rank transform guided filter dynamic programming real-time performance stereo matching GPU CUDA gradient matching

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：