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第三十三届中国控制会议

作者： YANG Yawen ZHANG Peng Peng QIAO Yu YANG Jie WANG Sheng Zheng The Key Laboratory of Ministry of Education for System Control and Information Processing Institute of Image Processing and Pattern RecognitionShanghai Jiao Tong University Merchant Marine College Shanghai Maritime University

ISBN: (纸本)9781479947249

Point matching is an important component of image *** years,Coherent Point Drift(CPD) method becomes a very popular point matching *** treats point matching as a probability estimation problem and speeds up the process of matching a *** this method,one set of points are thought to be sampled from a Gaussian Mixture Model(GMM),which is centered by the other set of ***,CPD is sensitive to outliers and noises,especially when the noise ratio increased or the number of outliers gets much *** deal with this problem,we introduce shape context into the step of searching for matching points and then improve the form of prior probabilities of GMM in this *** main idea of our method is that if the most points in a data set are likely to be matched to a particular centroid,this Gaussian component should be have a more influence to ***,we set prior probability of GMM with the similarity between GMM components and the data *** the computation of similarity is based on shape *** experiments on 2D and 3D images show that when noise ratio is low,our method performs as well as CPD does,but as the ratio increased,our method is more robust and satisfactory than CPD.

关键词： CPD,Shape context,Image registration,Point matching

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Predictive Zone control of Pressure Management for Water Supply Network systems

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International Journal of Automation and computing 2016年第6期13卷 607-614页

作者： Dong-Ming Liu Shao-Yuan Li Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 China Changzhou Institute of Light Industry Technology Jiangsu 213164 China

In this paper we address the problem of pressure management in water supply system （WSS） network. The model-based predictive control （MPC） strategies have some important features to deal with WSS. By hydraulic analysis of WSS, the predictive model is derived from the dynamic model and static model of WSS. Through WSS, the consumers＇ demands are required to be met at all times according to some operational constraints that must be satisfied. The constraints of flow through actuators, the water level of reservoirs and the consumer areas＇ pressure demand are determined by a specific system. In this work, we develop a constrained MPC controller that considers the zone control of the pressure outputs and incorporates steady state economic targets in the control cost function. The designed management strategies are applied to a case study and simulation results, covering different aspects, are provided. The output nodal pressure can be controlled in the desired zone by optimal scheduling the actuators of the WSS. If the variation range of reservoir＇s water level is broader, the rate of flow through the actuators is gentle, and vice versa.

关键词： Water supply system （WSS） network mathematical modelling zone control pressure control model predictive control（MPC）.

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The optimization of location and control of pump stations in urban drainage system 35

The optimization of location and control of pump stations in...

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第35届中国控制会议

作者： CUI Yiqun HOU Shufang LI Dewei XI Yugeng CEN Lihui Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong University School of Information Science and Engineering Central South University

ISBN: (纸本)9781509009107

To reduce the overflow of the wastewater and high expense caused by redundant arrangement of the stations of pumps in the urban drainage system,a hybrid logistic optimization model is proposed to choose the locations of pump stations and the corresponding optimal control algorithm is also developed in this *** inflow in the conduit from rainfall is estimated based on rainfall-runoff model and meanwhile the performance of the pump is described by the nonlinear pump *** determining the optimal pump locations by the optimization algorithm,this paper further studies the energy saving optimal control of the *** taking both the position and the working situation of the pumps into consideration,the energy consumption of the system and the frequency of overflow can be brought down effectively.

关键词： Urban Drainage system Pump Station Locations Energy Saving Hybrid Optimization

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Data-driven Predictive control for the Industrial Processes with Multiphase and Transition

Data-driven Predictive Control for the Industrial Processes ...

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第25届中国控制与决策会议

作者： Hua Yang Shaoyuan Li College of Information Science and Engineering Ocean University of China Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China

ISBN: (纸本)9781467355339

Processes with multiphase are commonly found in process industries. Process dynamics and correlations among variables tend to change with the transitions across such phases. In this paper, we propose a new data-driven predictive control strategy with the consideration of the important multiphase feature. The method aims to feature the multiphase data and use the data to design the controller. First, the data is divided and weighted based on the multiple phases and transitions. Through the minimal image representation, the data-driven prediction of future trajectory can be obtained and thus the computation of dynamic optimization. In the proposed controller, data Hankel matrices is direct incorporated in the predictive control laws, without a model or an intermediate step to meet the given performance specifications. Finally, the proposed predictive controller is demonstrated on a multiphase process.

关键词： Multiphase predictive control data-driven

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Background extraction algorithm based on K-means clustering algorithm and histogram analysis

Background extraction algorithm based on K-means clustering ...

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2012 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2012

作者： Zhang, Yan Luo, Linkai Department of Automation Xiamen University Xiamen China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

ISBN: (纸本)9781467300865

Background extraction is a fundamental task in many computer vision applications. This paper presents a novel method based on K-means Clustering Algorithm. First, the intensity values are divided into several groups by clustering method automatically. Then the mean of intensities in the most frequent group is assigned as the background intensity. The experiment results show that the proposed approach achieves more accurate background than traditional method. © 2012 IEEE.

关键词： Graphic methods

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H∞ Model Reduction for Takagi-Sugeno Fuzzy systems via Space Projection 48

H∞ Model Reduction for Takagi-Sugeno Fuzzy Systems via Spac...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Zheng, Hua Zou, Yuanyuan Li, Shaoyuan Shanghai Jiao Tong University Ministry of Education Key Laboratory of System Control and Information Processing Department of Automation Shanghai China

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

In this paper, the problem of model reduction for Takagi-Sugeno (T-S) fuzzy systems is studied. The virtual inner disturbance is first constructed to map a potential link between the states of two systems before and after dimensionality reduction. Based on Lyapunov theorem, the H∞ approach is then used to analyze the augmented system with the inner disturbance. The results are unrelated to reduced-order system membership functions (MFs), which can be freely selected. Furthermore, both the number of rules and the size of the reduced-order system and the inner disturbance may be flexibly chosen. An example is adapted to demonstrate the efficiency of the proposed method. © 2022 IEEE.

关键词： Membership functions

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Global Update Guided Federated Learning 41

Global Update Guided Federated Learning

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第41届中国控制会议

作者： Qilong Wu Lin Liu Shibei Xue Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Electronic Information Engineering Shanghai Dianji University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Federated learning protects data privacy and security by exchanging models instead of ***,unbalanced data distributions among participating clients compromise the accuracy and convergence speed of federated learning *** alleviate this problem,unlike previous studies that limit the distance of updates for local models,we propose global-updateguided federated learning(FedGG),which introduces a model-cosine loss into local objective functions,so that local models can fit local data distributions under the guidance of update directions of global ***,considering that the update direction of a global model is informative in the early stage of training,we propose adaptive loss weights based on the update distances of local *** simulations show that,compared with other advanced algorithms,FedGG has a significant improvement on model convergence accuracies and ***,compared with traditional fixed loss weights,adaptive loss weights enable our algorithm to be more stable and easier to implement in practice.

关键词： Federated Learning Cosine Similarity Adaptive Loss Weights

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Depth estimation and background segmentation for deformable packages from a single image using FCRN

Depth estimation and background segmentation for deformable ...

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2019 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2019

作者： Wang, Yunqing Chen, Weidong Wang, Hesheng Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China China

ISBN: (纸本)9781728137261

The depth of object is indispensable to provide the three-dimensional pose of robot grasping. In this paper, we only use one fully convolutional residual network to achieve both depth estimation and background segmentation tasks of deformable packages in the harsh steelmaking environment. The continuously depth information is discretized while packages and background are given different labels respectively. The above two tasks are completed simultaneously using a same network. During the training process, the depth estimated of the object which is close to the true value is also used to update the network weight. Kinect v2 is used to collect the color image and depth image of the deformable packages. Experiments are done to prove the effectiveness of depth estimation and background segmentation method for deformable packages which we proposed in this paper. © 2018 IEEE

关键词： Deformation

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Cognitive Navigation for Intelligent Mobile Robots:A Learning-Based Approach With Topological Memory Configuration

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1933-1943页

作者： Qiming Liu Xinru Cui Zhe Liu Hesheng Wang Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China MoE Key Laboratory of Artificial Intelligence AI InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong UniversityShanghai 200240China

Autonomous navigation for intelligent mobile robots has gained significant attention,with a focus on enabling robots to generate reliable policies based on maintenance of spatial *** this paper,we propose a learning-based visual navigation pipeline that uses topological maps as memory *** introduce a unique online topology construction approach that fuses odometry pose estimation and perceptual similarity *** tackles the issues of topological node redundancy and incorrect edge connections,which stem from the distribution gap between the spatial and perceptual ***,we propose a differentiable graph extraction structure,the topology multi-factor transformer(TMFT).This structure utilizes graph neural networks to integrate global memory and incorporates a multi-factor attention mechanism to underscore elements closely related to relevant target cues for policy *** from photorealistic simulations on image-goal navigation tasks highlight the superior navigation performance of our proposed pipeline compared to existing memory *** validation through behavior visualization,interpretability tests,and real-world deployment further underscore the adapt-ability and efficacy of our method.

关键词： Graph neural networks(GNNs) spatial memory topological map visual navigation

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Early Forest Fire Detection Based on Deep Learning 3

Early Forest Fire Detection Based on Deep Learning

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3rd International Conference on Industrial Artificial Intelligence, IAI 2021

作者： Li, Mengna Zhang, Youmin Mu, Lingxia Xin, Jing Yu, Ziquan Liu, Han Xie, Guo Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Shaanxi Xi'an710048 China

ISBN: (纸本)9781665435178

Early fire detection is very important for preventing forest fires. In this paper, a new image-based fire detection algorithm, named as h-EfflcientDet, is proposed to complete the task of early forest fire detection. h-EfflcientDet is based on a popular deep learning approach EfficientDet (scalable and efficient object detection) by replacing the nonlinear activation function swish of the EfficientDet with the hard version of swish and combing also with an efficient feature fusion network BIFPN (bidirectional feature pyramid network), which can improve significantly the efficiency of the fire detection model. The experiment results show that the proposed h-EfficientDet can detect the fire in real-time with the detection speed of 21 FPS. The detection accuracy is up to 98.35% with a low miss detection rate. © 2021 IEEE.

关键词： Fires

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