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Distributed Solving Linear Algebraic Equations with Switched Fractional Order Dynamics

Journal of Systems Science & Complexity 2023年第2期36卷 613-631页

作者： YU Wenqiang CHENG Songsong HE Shuping Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China

This paper proposes a novel distributed optimization algorithm with fractional order dynamics to solve linear algebraic ***,the authors proposed“Consensus+Projection”flow with fractional order dynamics,which has more design freedom and the potential to obtain a better convergent performance than that of conventional first order ***,the authors prove that the proposed algorithm is convergent under certain iteration order and ***,the authors develop iteration order switching scheme with initial condition design to improve the convergence performance of the proposed ***,the authors illustrate the effectiveness of the proposed method with several numerical examples.

关键词： Distributed optimization fractional order dynamics initial condition iteration order linear equations

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Event-Triggered Optimal Nonlinear Systems Control Based on State Observer and Neural Network

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Journal of Systems Science & Complexity 2023年第1期36卷 222-238页

作者： CHENG Songsong LI Haoyun GUO Yuchao PAN Tianhong FAN Yuan Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China

This paper develops a novel event-triggered optimal control approach based on state observer and neural network(NN)for nonlinear continuous-time ***,the authors propose an online algorithm with critic and actor NNs to solve the optimal control problem and provide an event-triggered method to reduce communication and computation ***,the authors design weight estimation for critic and actor NNs based on gradient descent method and achieve uniformly ultimate boundednesss(UUB)estimation ***,by using bounded NN weight estimation and dead-zone operator,the authors propose a triggering condition,prove the asymptotic stability of closed-loop system from Lyapunov stability perspective,and exclude the Zeno ***,the authors provide a numerical example to illustrate the effectiveness of the proposed method.

关键词： Event-triggered control neural network optimal control state observer

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An Efficient Instance Segmentation Based on Layer Aggregation and Lightweight Convolution

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Computers, Materials & Continua 2025年第4期83卷 1041-1055页

作者： Hui Jin Shuaiqi Xu Chengyi Duan Ruixue He Ji Zhang College of Mechanical Engineering Chongqing University of TechnologyChongqing400054China Robot and Intelligent Manufacturing Technology Key Laboratory of Chongqing Education Commission of ChinaChongqing400054China

Instance segmentation is crucial in various domains,such as autonomous driving and ***,there is scope for improvement in the detection speed of instance-segmentation algorithms for edge ***,it is essential to enhance detection speed while maintaining high *** this study,we propose you only look once-layer fusion(YOLO-LF),a lightweight instance segmentation method specifically designed to optimize the speed of instance segmentation for autonomous driving *** on the You Only Look Once version 8 nano(YOLOv8n)framework,we introduce a lightweight convolutional module and design a lightweight layer aggrega-tion module called Reparameterization convolution and Partial convolution Efficient Layer Aggregation Networks(RPELAN).This module effectively reduces the impact of redundant information generated by traditional convolutional stacking on the network size and detection speed while enhancing the capability to process feature *** experimentally verified that our generalized one-stage detection network lightweight method based on Grouped Spatial Convolution(GSconv)enhances the detection speed while maintaining accuracy across various state-of-the-art(SOTA)*** experiments conducted on the publicly available Cityscapes dataset demonstrated that YOLO-LF maintained the same accuracy as yolov8n(mAP@0.537.9%),the model volume decreased by 14.3%from 3.259 to=2.804 M,and the Frames Per Second(FPS)increased by 14.48%from 57.47 to 65.79 compared with YOLOv8n,thereby demonstrating its potential for real-time instance segmentation on edge devices.

关键词： Automatic driving convolution deep learning real-time instance segmentation

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Distributed Optimization and Scaling Design for Solving Sylvester Equations

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Journal of Systems Science & Complexity 2024年第6期37卷 2487-2510页

作者： CHENG Songsong YU Xin ZENG Xianlin LIANG Shu HONG Yiguang Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 201210China

This paper develops distributed algorithms for solving Sylvester *** authors transform solving Sylvester equations into a distributed optimization problem,unifying all eight standard distributed matrix *** the authors propose a distributed algorithm to find the least squares solution and achieve an explicit linear convergence *** results are obtained by carefully choosing the step-size of the algorithm,which requires particular information of data and Laplacian *** avoid these centralized quantities,the authors further develop a distributed scaling technique by using local information *** a result,the proposed distributed algorithm along with the distributed scaling design yields a universal method for solving Sylvester equations over a multi-agent network with the constant step-size freely chosen from configurable ***,the authors provide three examples to illustrate the effectiveness of the proposed algorithms.

关键词： Distributed optimization least squares solution linear convergence rate step-size interval Sylvester equation

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Policy iteration-based adaptive optimal control for Markov jump systems: a transition-probability-free asynchronous approach

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Science China(Information Sciences) 2024年第11期67卷 363-364页

作者： Weidi CHENG Chengcheng REN Shuping HE Changyin SUN Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) School of Electrical Engineering and Automation Anhui University Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and Automation Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province Engineering Research Center of Autonomous Unmanned System Technology (Ministry of Education) School of Artificial Intelligence Anhui University

The controller and filter design problems of Markov jump systems(MJSs) have gained significant attention over the past few decades. These studies include various aspects,including stochastic stabilization [1], optimal tracking control [2], and dissipative filter design [3]. Although numerous publications address the optimal controller design for MJSs, the issue of hidden MJSs, particularly those with mismatched jumping modes between the system and the controller, has rarely been explored.

关键词： Markov processes

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The ringed residual u-net with non-natural regions feature for image splicing forgery detection and localization

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Journal of intelligent and Fuzzy Systems 2024年第4期46卷 7447-7459页

作者： Wang, Qi Lu, Tongwei School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China

Recently, with the emergence of many image editing tools (photoshop, Topaz studio, etc.), the authenticity of images has been severely challenged. However, the performance of some existing traditional feature extraction methods and detection methods based on convolutional neural network (CNN) is poor, and the information provided by the features extracted from the network is limited and single. In this paper, an end-To-end ringed residual U-Net is proposed to detect image splicing forgery by blending features of non-natural regions. Some regions with significant differences from the image background are defined as non-natural regions(such as the irregular border at the splicing of images). In this paper, a feature enhancement module for non-natural regions is constructed, which the image through the pooling of four different scales, and these features are then combined with the original image and input to the backbone network for processing, aiming to highlight regions of the image that differ significantly from the background. Therefore, after adding the feature enhancement module for non-natural regions to the end-To-end ring residual U-Net, more attention will be paid to the tampering regions in the feature extraction stage, image manipulation detection and localization will also become more accurate. Compared with some mainstream methods, this method achieves better performance on the three standard datasets(CASIA2.0, NIST2016, COLUMBIA). In addition, it has excellent robustness under JPEG compression attack and noise corruption attack. © 2024-IOS Press. All rights reserved.

关键词： Topaz

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Enhancing stability and safety:A novel multi-constraint model predictive control approach for forklift trajectory

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IET Cyber-Systems and robotics 2024年第4期6卷 32-47页

作者： Yizhen Sun Junyou Yang Donghui Zhao Moses Chukwuka Okonkwo Jianmin Zhang Shuoyu Wang Yang Liu School of Electrical Engineering Shenyang University of TechnologyShenyangChina Intelligent Robot Laboratory Shenyang Open UniversityShenyangChina School of Information Engineering Shenyang UniversityShenyangChina Department of Intelligent Mechanical Systems Engineering Kochi University of TechnologyKochiJapan

The advancements in intelligent manufacturing have made high-precision trajectory tracking technology crucial for improving the efficiency and safety of in-factory cargo *** study addresses the limitations of current forklift navigation systems in trajectory control accuracy and stability by proposing the Enhanced Stability and Safety Model Predictive Control(ESS-MPC)*** approach includes a multi-constraint strategy for improved stability and *** kinematic model for a single front steeringwheel forklift vehicle is constructed with all known state quantities,including the steering angle,resulting in a more accurate model description and trajectory *** ensure vehicle safety,the spatial safety boundary obtained from the trajectory planning module is established as a hard constraint for ESS-MPC *** optimisation constraints are also updated with the key kinematic and dynamic parameters of the *** ESSMPC method improved the position and pose accuracy and stability by 57.93%,37.83%,and 57.51%,respectively,as demonstrated through experimental validation using simulation and real-world *** study provides significant support for the development of autonomous navigation systems for industrial forklifts.

关键词： automatic guided vehicles mobile robots robot manipulator tracking control

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Effective distributed algorithm for solving linear matrix equations

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Science China(Information Sciences) 2023年第8期66卷 265-266页

作者： Songsong CHENG Jinlong LEI Xianlin ZENG Yuan FAN Yiguang HONG Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and Automation Anhui University Department of Control Science and Engineering Tongji University Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

Dear editor,Solving linear matrix equations is a basic and important problem in many fields such as the computation of generalized inverses of matrices and(generalized) Sylvester equations. Also, the linear algebraic ...

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Multi-objective configuration optimization method based on antlion algorithm for customer-oriented modular process

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Journal of intelligent and Fuzzy Systems 2024年第3-4期47卷 265-277页

作者： Zhang, Qianqian Fan, Bo Sun, Lifan Information Engineering College Henan University of Science and Technology Luoyang China Henan Key Laboratory of Robot and Intelligent Systems Henan University of Science and Technology Luoyang China

Process parameter configuration needs to respond quickly in the customized manufacturing environment. A multi-objective optimization method based on antlion algorithm for product process configuration design is proposed. The weight mapping mechanism of customer demands is established to clarify the relationship between customer demands and manufacturing process, which also simplifies the process attribute analysis of customized products. The parameters to be optimized in the customization process are analyzed: product performance, process cost and production time. Based on the objective function including these parameters, a multi-objective optimization model of modular process reconstruction is established. The proposed model and algorithm can optimize these parameters in parallel and realize the rapid configuration of product modular process. In the application case of this paper, the proposed method is suitable for the whole process modular configuration of copper plate and strip. The feasibility and effectiveness of the model and algorithm in the proposed configuration scheme are verified. © 2024-IOS Press. All rights reserved.

关键词： Multiobjective optimization

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DSSNet: a transformer-based network for dense scene text detection and recognition in complex environments 5

DSSNet: a transformer-based network for dense scene text det...

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5th International Conference on Signal Processing and Computer Science, SPCS 2024

作者： Li, Jing Zhou, Huabing College of Computer Science and Engineering Wuhan Institute of Technology Hubei Key Laboratory of Intelligent Robot Wuhan China

ISBN: (数字)9781510686731

ISBN: (纸本)9781510686724

This paper presents a novel approach for dense scene text detection called DSSNet (Dense Script Spotter Network). The network leverages ResNet and FPN for feature extraction, employing multi-scale feature fusion and Transformer-based feature processing to enhance text recognition across varying sizes. The method generates text instance shapes using Bézier central curves and performs text recognition by integrating positional query information. Experimental results on the DSTD1500 and ICDAR2015 datasets demonstrate that DSSNet outperforms existing methods in terms of text localization accuracy, recognition accuracy, and annotation flexibility. © 2025 SPIE.

关键词： Feature extraction

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