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Surface-PMSM Sensorless control Strategy Based on Reduced-Order Linear Kalman Filter Cooperating With Prediction Error Rolling Compensation

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IEEE Transactions on Power Electronics 2025年第8期40卷 10804-10815页

作者： Xu, Sang Shen, Anwen Tang, Qipeng Wang, Miaomiao Luo, Pan Luo, Xin Xu, Jinbang National Key Laboratory of Science and Technology on Multispectral Information Processing Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China

Kalman filter (KF) is increasingly attracted for sensorless control of surface permanent magnet synchronous motors due to its strong robustness against measurement and system noise. However, the conventional method suffers from poor position and speed estimation accuracy under dynamic conditions and high computational cost. In order to solve these problems, an enhanced sensorless control strategy based on reduced-order linear Kalman filter (RLKF) cooperating with prediction error rolling compensation is introduced in this article. Differing from conventional methods, a reduced-order linear state equation encompassing rotor position, speed, and torque disturbance is constructed. Then, by obtaining the prediction error of system output using the motor current equation in the predictive reference frame, the optimal estimation of rotor position and speed in the KF algorithm is achieved based on the reduced-order model. This not only simplifies the calculation process but also enhances the position and speed estimation accuracy under dynamic conditions. Meanwhile, a prediction error rolling compensation algorithm is developed to minimize the estimation deviations caused by motor parameter variations. In addition, the system's dynamic performance is further improved with an adopted speed controller based on torque disturbance feedforward and acceleration feedback. Finally, experimental results verify the effectiveness and feasibility of the proposed strategy. © 1986-2012 IEEE.

关键词： Permanent magnets

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control of Virtual Synchronous Generator for Frequency Regulation Using a Coordinated Self-adaptive Method

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CSEE Journal of Power and Energy systems 2024年第1期10卷 175-184页

作者： Hongwei Fang Zhiwei Yu School of Electrical and Information Engineering and Key Laboratory of Tianjin Electric Power System Simulation and Control Tianjin UniversityTianjin 300072China

Power inverter adopting virtual synchronous generator(VSG)control can provide inertia support for distributed generation ***,it cannot take into account the dynamic regulation characteristics of ***,when the system encounters a sudden change in load or disturbance,the dynamic process of frequency regulation will be greatly *** view of this issue,an improved VSG control strategy based on a coordinated self-adaptive(CSA)method is *** time domain analysis method is used to study the influences of virtual inertia and damping parameter perturbation on the system steady and dynamic ***,in order to make the control strategy suitable for large load changes and suppress frequency variations beyond the limit,the secondary frequency modulation is introduced into the control *** the coordinated adaptive control of virtual inertia,virtual damping and frequency modulation,the dynamic performance of vSG frequency regulation can be obviously *** and experiment results have verified the effectiveness of the proposed CSA control strategy.

关键词： Coordinated self-adaptive method frequency regulation time domain analysis virtual synchronous generator

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CenterRCNN: Two-Stage Anchor-Free Object Detection Using Center keypoint-Based Region Proposal Network

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Journal of Shanghai Jiaotong University (Science) 2023年 1-9页

作者： Liu, Chen Li, Wenfa Xu, Yunwen Li, Dewei Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China

The classic two-stage object detection algorithms such as faster regions with convolutional neural network features (Faster RCNN) suffer from low speed and anchor hyper-parameter sensitive problems caused by dense anchor mechanism in region proposal network (RPN). Recently, the anchor-free method CenterNet shows the effectiveness of perceiving and classifing object by its center. However, the severe coincidence false positive problem between confusing categories caused by the multiple binary classifiers makes it still insufficient in accuracy. We introduce a two-stage network CenterRCNN to take advantage of both and overcome their shortcomings. CenterRPN is proposed as the first stage to give proposals that incorporate the center keypoint idea into RPN to perceive foreground objects, replacing dense anchor-based RPN. Then the proposals are classified by the multi-classifier of RCNN header that focuses more on the difference between confusing categories and only outputs the maximum probability one of them. To sum up, CenterRPN can eliminate the drawbacks of dense anchor based RPN in Faster RCNN, and multi-classifier’s classification ability is better than that of multiple binary classifiers in CenterNet. The experiment demonstrates that CenterRCNN outperforms both basic algorithms in the accuracy, and the speed is improved as compared with Faster RCNN. © 2023, Shanghai Jiao Tong University.

关键词： Object detection

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Indoor Vehicle Positioning Based on Multi-Sensor Data Fusion

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Journal of Shanghai Jiaotong university(Science) 2023年第1期28卷 77-85页

作者：王明阳时良仁李元龙 Department of Automation Shanghai Jiao Tong University、Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai 200240China

This study proposes a Kalman filter-based indoor vehicle positioning method for cases in which the steering angle and rotation speed of the vehicle’s wheels are *** fusing the position and velocity data from the ultra-wideband sensors and acceleration and orientation data from the inertial measurement unit,we developed two algorithms to estimate the real-time position of the vehicle based on a linear Kalman filter and extended Kalman filter,*** then conducted simulations and experiments to examine the performances of the *** the experiment,the Kalman filtering hyperparameters are configured,and we then ran the two algorithms to determine the positioning precision and accuracy with the ground truth produced via *** verified that our method can improve precision and accuracy compared with the raw positioning data and can achieve desirable effects for indoor vehicle positioning when vehicles travel at low speeds.

关键词： indoor vehicle positioning multi-sensor data fusion ultra-wideband linear Kalman filter extended Kalman filter

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Applications of artificial intelligence to lipid nanoparticle delivery

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Particuology 2024年第7期90卷 88-97页

作者： Ye Yuan Yuqi Wu Jiabei Cheng Kaiyuan Yang Yilin Xia Hongguang Wu Xiaoyong Pan Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of ChinaChina Songjiang Research Institute Songjiang District Central HospitalShanghai Jiao Tong University School of MedicineShanghaiChina

Lipid nanoparticles(LNPs)are nanocarriers composed of four lipid components and can be used for gene therapy,protein replacement,and vaccine ***,LNPs also face several challenges,such as toxicity,immune activation,and low delivery *** overcome these challenges,artificial intelligence can be used to optimize the design and formulation of LNPs,as well as to predict their properties and ***,antibody-targeted conjugation can be used to enhance the specificity and selectivity of LNPs by attaching an antibody that recognizes a specific antigen on the cell surface to LNPs.

关键词： Artificial intelligence Lipid nanoparticles Antibody Targeted conjugation

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Strong Structural controllability of Multi-Agent systems with Uncertain Connection Topologies

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Journal of systems Science & Complexity 2025年

作者： CHEN Qitian LI Shaoyuan Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper investigates the strong structural controllability(SSC) of multi-agent systems(MASs) defined over Laplacian dynamics on directed graphs. The agents that are divided into leaders and followers are connected based on the consensus law and only leaders are manipulated by the external control input directly. In contrast to existing work, the topology of MAS contains uncertain interconnection edges between agents. The interconnection graph has a zero/nonzero/arbitrary structure, to handle the parameters uncertainty problem in MASs. Under this framework, the authors propose a color-changing rule based on the zero-forcing set(ZFS). A graph-theoretic sufficient condition of SSC is proved. Next, the authors investigate the leader selection problem to ensure the SSC of MASs. A greedy algorithm based on ZFS is introduced. In addition, the authors figure out that the redundant property of edges in MASs can help us decide the leader selection problem. A new heuristic algorithm of polynomial complexity is developed to select minimum leaders of the multi-agent ***, the authors support the proposed analysis with numerical results on various simulations.

关键词：

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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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Safety-Aware Scheduling of Real-Time control systems With Burst Computing Tasks

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical systems 2025年 3卷 218-227页

作者： Cheng, Ting Liang, Yonghui Li, Hui Xu, Qimin Zhu, Shanying Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China

This paper investigates the safety-aware task scheduling problem of real-time control systems in the presence of burst computing tasks. The basic idea is to adaptively release resources from low-criticality control tasks, ensuring timely completion of burst computing tasks and keeping the control system state within a safe threshold. An efficient algorithm called ADP-Opt is proposed to solve the problem. It first decouples the complex original problem into multiple subproblems, which greatly reduces the search space and improves the solution efficiency. In the subproblem, safety is maintained by limiting the upper bound of the system state's deviation to below the threshold. By introducing a penalty term in the cost function related to computing resources, we aim to balance the impact of control computing tasks on control performance and the consumption of computing resources. Consequently, the overall cost of the control system can be minimized while releasing enough resources for burst computing tasks. Simulation results show that the scheduling decisions made by ADP-Opt approach the optimal decision and maintain the safety of the control systems. © 2023 IEEE.

关键词： Real time control

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3D Localization for Multiple AUVs in Anchor-Free Environments by Exploring the Use of Depth information

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1051-1053页

作者： Yichen Li Wenbin Yu Xinping Guan the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240 the Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai Jiao Tong UniversityShanghai 200240China

Dear Editor,This letter investigates the cooperative localization problem for multiple autonomous underwater vehicles(AUVs)in underwater anchor-free environments,where AUV localization errors grow without bound due to the accumulated errors in inertial measurements(termed accumulated errors hereafter)and the lack of anchors(with known positions).

关键词： AUVs underwater hereafter

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C2P-Net: Comprehensive Depth Map to Planar Depth Conversion for Room Layout Estimation

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年第7期47卷 5350-5367页

作者： Zhang, Weidong Zhou, Mengjie Cheng, Jiyu Liu, Ying Zhang, Wei Xi'an University of Posts & Telecommunications School of Communications and Information Engineering China Xi'an Key Laboratory of Image Processing Technology and Applications for Public Security China Shandong University School of Control Science and Engineering China Ministry of Education Key Laboratory of Machine Intelligence and System Control China

Room layout estimation seeks to infer the overall spatial configuration of indoor scenes using perspective or panoramic images. As the layout is determined by the dominant indoor planes, this problem inherently requires the reconstruction of these planes. Some studies reconstruct indoor planes from perspective images by learning pixel-level or instance-level plane parameters. However, directly learning these parameters has the problems of susceptibility to occlusions and position dependency. In this paper, we introduce the Comprehensive depth map to Planar depth (C2P) conversion, which reformulates planar depth reconstruction into the prediction of a comprehensive depth map and planar visibility confidence. Based on the parametric representation of planar depth we propose, the C2P conversion is applicable to both panoramic and perspective images. Accordingly, we present an effective framework for room layout estimation that jointly learns the comprehensive depth map and planar visibility confidence. Due to the differentiability of the C2P conversion, our network autonomously learns planar visibility confidence by constraining the estimated plane parameters and reconstructed planar depth map. We further propose a novel approach for 3D layout generation through sequential planar depth map integration. Experimental results demonstrate the superiority of our method across all evaluated panoramic and perspective datasets. © 1979-2012 IEEE.

关键词： Layout Three-dimensional displays Image reconstruction Estimation Cameras Floors Cognition Transforms Training Semantics

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