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Velocity-Varying Target Tracking of Mobile Sensor Network Based on Flocking control

Journal of Shanghai Jiaotong university(Science) 2021年第4期26卷 446-453页

作者： ZHANG Lalu Xiangxiang Dong YAO Lixiu CAI Yunze Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai200240China Department of Automation Shanghai Jiao Tong UniversityShanghai200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai Jiao Tong UniversityShanghai200240China

Existing coupled distributed estimation and motion control strategies of mobile sensor networks present limitations in velocity-varying target tracking. Therefore, a velocity-varying target tracking algorithm based on flocking control is proposed herein. The Kalman-consensus filter is utilized to estimate the position, velocity and acceleration of a target. The flocking control algorithm with a velocity-varying virtual leader enables the position of the center of the mobile sensor network to converge to that of the target. By applying an effective cascading Lyapunov method, stability analysis is performed. Simulation results are provided to validate the feasibility of the proposed algorithm.

关键词： mobile sensor network velocity-varying target tracking flocking control Kalman-consensus filtering

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Second-Order Consensus of Multi-agent systems via Periodically Intermittent Pinning control

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Circuits, systems, and Signal processing 2016年第7期35卷 2413-2431页

作者： Wang, Xiaoling Su, Housheng Wang, Xiaofan Liu, Bo Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan430074 China College of Science North China University of Technology Beijing100144 China

In this paper, we investigate the leader-following consensus of second-order multi-agent systems with nonlinear dynamics and time delay by employing periodically intermittent pinning control. All member agents and the virtual leader share the same nonlinear dynamics relating to the velocity and delayed velocity information. Based on Lyapunov stability theory, we obtain a novel criterion that is independent of the time delay and control width to guarantee the second-order consensus of multi-agent systems with time delay and periodically intermittent controllers. Numerical simulations are presented to illustrate the theoretical results. © 2015, Springer Science+Business Media New York.

关键词： Time delay

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Multi-Human Pose Estimation by Deep Learning-Based Sequential Approach for Human keypoint Position and Human Body Detection

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Journal of Shanghai Jiaotong University (Science) 2023年 1-11页

作者： Tahir, Rizwan Cai, Yunze Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China

Recent multimedia and computer vision research has focused on analyzing human behavior and activity using images. Skeleton estimation, known as pose estimation, has received a significant attention. For human pose estimation, deep learning approaches primarily emphasize on the keypoint features. Conversely, in the case of occluded or incomplete poses, the keypoint feature is insufficiently substantial, especially when there are multiple humans in a single frame. Other features, such as the body border and visibility conditions, can contribute to pose estimation in addition to the keypoint feature. Our model framework integrates multiple features, namely the human body mask features, which can serve as a constraint to keypoint location estimation, the body keypoint features, and the keypoint visibility via mask region-based convolutional neural network (Mask-RCNN). A sequential multi-feature learning setup is formed to share multi-features across the structure, whereas, in the Mask-RCNN, the only feature that could be shared through the system is the region of interest feature. By two-way up-scaling with the shared weight process to produce the mask, we have addressed the problems of improper segmentation, small intrusion, and object loss when Mask-RCNN is used, for instance, segmentation. Accuracy is indicated by the percentage of correct keypoint, and our model can identify 86.1% of the correct keypoints. © 2023, Shanghai Jiao Tong University.

关键词： Convolutional neural networks

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Modeling and simulation of MHD melt convection and heat transfer in CZ crystal growth

Modeling and simulation of MHD melt convection and heat tran...

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Chinese Automation Congress

作者： Ni Zhang Ding Liu Weichao Huang National and Local Joint Engineering Shaanxi key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

This paper presents an axisymmetric swirl incompressible thermal lattice Boltzmann model to study the magnetohydrodynamics (MHD) melt flow and heat transfer at high Grashof number and high Reynolds number under external magnetic field in Czochralski (CZ) crystal growth process. The model is built based on the double distribution function lattice Boltzmann equation (DDF-LBE) and is verified by benchmark problem. By using the proposed model, the evolution relationship of melt flow, temperature is constructed under the combined effects of Lorenz force, rotating inertia force and thermal buoyancy force. Furthermore, the flow patterns and the temperature distribution of silicon melt under different magnetic field strengths are simulated. The simulation results show that with the increase of magnetic field strength, the melt velocity is reduced, which suppresses the melt convection and is beneficial for suppressing the fluctuation of melt. And the temperature gradient below the crystal growth interface increases in the case of crystal rotation, which is helpful to increase the crystallization rate. The combination of Cusp magnetic field, crucible rotation and crystal rotation can be used as an effective method in the production of high-quality crystal.

关键词： Modeling Computer simulation Crystal growth Lattice boltzmann method

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A multi-objective particle swarm optimization for multiple knapsack problem with strong constraints

A multi-objective particle swarm optimization for multiple k...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Xuan Ma Ying Yan Qing Liu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an City China

Aiming at the characteristics of strong constraints of multiple knapsack problem (MKP), a method based on multi-objective particle swarm optimization is proposed in this paper. We take constraint violation as an optimal objective to avoid the troublesome of dealing with unfeasible solutions unsatisfied constraints. For updating effectively the external archive, the degree of constraint violation and the crowding degree of non-dominated particle in Pareto front are taken as two criteria. To decrease the probability of algorithm converging to a pseudo Pareto front, a mutation operator is designed. The experimental results of solving a number of MKP instances demonstrate that the proposed algorithm performs better to the MKP instances with strong constraints.

关键词： Optimization Sociology Statistics Particle swarm optimization Heuristic algorithms complex systems control systems

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Optimizing multi-criteria k-shortest paths in graph by a natural routing genotype-based genetic algorithm

Optimizing multi-criteria k-shortest paths in graph by a nat...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Yang Wang Qing Liu Haipeng Ren Xuan Ma Long Liu Wenqing Wang Jing Zhang Department of Information and Control Engineering Xi'an University of technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

k-shortest path problem (KSP) is a more general form of the classical shortest path problem in graph. Its task is no longer to find the shortest path between two vertices, but to find the shortest k paths. So far, the reported KSP-algorithms only considers finding shortest k paths with regard to a single criterion, while far more application scenarios of the KSP require to determine k paths by taking more criteria into account. This article formulates the KSP as a multi-objective optimization problem. In consideration of the problem's property and genetic algorithm's great success in multi-objective optimization, the genetic algorithm is utilized as the optimization tool. The genotype is directly represented as the form of natural routing. In order to make the related genetic operators risk-free, the conception of gene-bank is introduced. And the crossover and mutation are both implemented based on the introduced gene-bank. The proposed genetic algorithm is tested on an undirected graph of 9-vertex/65-edge. The testing result shows that, our proposed algorithm is valid and outperforms some other swarm intelligence-based algorithms in terms of the obtained paths' quality.

关键词： Genetic algorithms Optimization Genetics Routing Task analysis Encoding Sociology

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Algorithm for Solving Traveling Salesman Problem Based on Self-Organizing Mapping Network

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 463-470页

作者：朱江辉叶航航姚莉秀蔡云泽 Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent Equipment and System Ministry of EducationShanghai 200240China Huawei Technologies Co. Ltd.Shanghai 201206China

Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization *** on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from the perspectives of network update strategy,initialization method,and parameter *** paper compares the performance of the proposed algorithms with the performance of existing SOM network algorithms on the TSP and compares them with several heuristic *** show that compared with existing SOM networks,the improved SOM network proposed in this paper improves the convergence rate and algorithm *** with iterated local search and heuristic algorithms,the improved SOM net-work algorithms proposed in this paper have the advantage of fast calculation speed on medium-scale TSP.

关键词： traveling salesman problem(TSP) self-organizing mapping(SOM) combinatorial optimization neu-ral network

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Layout Optimization of Large-scale Urban Water Supply Network Pressure Measuring Point Distribution Using Genetic Algorithm 36

Layout Optimization of Large-scale Urban Water Supply Networ...

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第36届中国控制会议

作者： Huayi Luo Jingcheng Wang Xiaocheng Li Jiayu Zhu Department of Automation Shanghai JiaoTong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China Autonomous Systems and Intelligent Control International Joint Research Center Xi'an Technological University

ISBN: (纸本)9781538629185

In the urban water supply system, the location and quantity of the pressure monitoring nodes play a significant role for the monitoring effect and the response warning of the pipe burst. However, most installation of pressure monitoring nodes are based on human experience, which cannot totally present the whole water supply system condition. In view of the unreasonable layout of pressure monitoring nodes, this paper presents a solution Integrating sensitivity analysis, genetic algorithm, hydraulic model calculation and pipe network topology. Then optimize the number of pressure monitoring nodes by considering the amount of water covered and the number of associated nodes. This solution offers a relatively accurate and reasonable way to optimize the layout of pressure monitoring nodes in large-scale site selection, presenting better comprehensive effect compared with previous layout. To a certain extent, this optimized layout of pressure monitoring nodes reduce the impact of human factors and improve the monitoring of water supply network operation results.

关键词： pressure measuring point layout optimization genetic algorithm urban water supply network

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A Class of Distributed Variable Structure Multiple Model Algorithm Based on Posterior information of information Matrix

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Journal of Shanghai Jiaotong university(Science) 2022年第5期27卷 671-679页

作者： HUANG Yinghao WU Yi YAO Lixiu CAI Yunze Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai200240China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai200240China Alibaba(China)Co. Ltd.Hangzhou311121China

The tracking of maneuvering targets in radar networking scenarios is studied in this *** the interacting multiple model algorithm and the expected-mode augmentation algorithm,the fixed base model set leads to a mismatch between the model set and the target motion mode,which causes the reduction on tracking *** adaptive grid-expected-mode augmentation variable structure multiple model algorithm is *** adaptive grid algorithm based on the turning model is extended to the two-dimensional pattern space to realize the self-adaptation of the model ***,combining with the unscented information filtering,and by interacting the measurement information of neighboring radars and iterating information matrix with consistency strategy,a distributed target tracking algorithm based on the posterior information of the information matrix is *** the problem of filtering divergence while target is leaving radar surveillance area,a k-coverage algorithm based on particle swarm optimization is applied to plan the radar motion trajectory for achieving filtering convergence.

关键词： radar network system variable structure multiple model consistency filtering information matrix particle swarm optimization

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Using artificial plant optimization algorithm with dynamic population and cluster methods to optimize the performance of DV-Hop

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Sensor Letters 2014年第8期12卷 1313-1317页

作者： Wu, Xuexue Cui, Zhihua Dai, Chaohua Chen, Weirong Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Shanxi China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Electric Engineering Southwest Jiaotong University Sichuan China

Artificial plant optimization algorithm is a novel stochastic population-based evolutionary algorithm by simulating the plant growing process. In this paper, a new variant, which is called APOA-DC is proposed by incorporating with dynamic population size and cluster methods, furthermore, to investigate the performance, APOA-DC is applied to optimize the DV-Hop localization algorithm, simulation results show it achieves better performance than the DV-Hop algorithm.

关键词： Evolutionary algorithms

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