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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Wu, Shimeng Luo, Hao Jiang, Yuchen Li, Kuan Harbin Institute of Technology Department of Control Science and Engineering Harbin China Shanghai Aerospace Control Technology Institute Shanghai China

ISBN: (纸本)9798350399714

While cyber-physical systems (CPSs) bring convenience to industrial production and human life, they are, in the mean time, exposed to the threat of cyber-physical attacks, which have the characteristics of concealment and vital destruction. Recent reports on several horrible attack events aroused people's attention to the security of CPSs. Motivated by this, this paper proposes a defense scheme based on co-prime factorization technology, consisting of attack prevention and detection. This scheme utilizes residual signals that are commonly used in fault diagnosis to realize secure transmission because these residual signals do not contain essential system knowledge. At the same time, a filter module is added, which makes use of noise signals to cover and protect the reference signals and the operation status of the system. By this means, the secure transmission method reduces the leakage of system information and interferes with the design of stealthy attacks, which need sufficient system knowledge. Furthermore, it realizes the detection of non-stealthy attacks under the same framework. Simulation results on a linear system with random parameters demonstrate the effectiveness of the proposed scheme. © 2023 IEEE.

关键词： Cyber Physical System

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Adaptive Sampling Offspring Generation Strategy for Multi-objective Optimization 8

Adaptive Sampling Offspring Generation Strategy for Multi-ob...

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2024 8th International Conference on Machine Vision and Information technology, CMVIT 2024

作者： Wang, Ningning Fan, Jun Liu, Tingrui Kang, Honglong Zhang, Wenbo Song, Shenmin Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China Army Aviation Institute Beijing China Beijing Institute of Astronautical Systems Engineering Beijing China

A covariance adaptive sampling offspring generation strategy (CASS) based on fuzzy clustering is proposed, and a multi-objective distribution estimation algorithm (MEDCA) based on this strategy is introduced. The GK-FCM clustering partitioning strategy is designed to build a Gaussian model for each individual, collectively approximating the manifold of the Pareto solution set and generating offspring through sampling. The introduction of an individual's survival generation adapts the individual's preference for exploration and exploitation. This is achieved by incorporating it as a scaling factor of the covariance matrix in the sampling model, in order to satisfy the individual's preferences for development and exploration in different evolutionary stages. This method significantly improves the performance of MEDCA in solving complex multi-objective optimization problems through covariance matrix adaptation sampling strategy and scaling factor adaptation strategy. The experimental results demonstrate the advantages of MEDCA in the application of offspring generation strategies during model sampling. © Published under licence by IOP Publishing Ltd.

关键词： Covariance matrix

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Deep attention convolutional neural network-based adaptive multi-source information fusion for accurate short-term photovoltaic power forecast

Deep attention convolutional neural network-based adaptive m...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Bai, Mingliang Chen, Yunxiao Zhou, Zhihao Long, Zhenhua Liu, Jinfu Yu, Daren Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Energy Science and Engineering Harbin Institute of Technology Harbin China Department of Control Science and Engineering School of Energy Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350396782

Solar energy is one of the most important renewable energy sources. Photovoltaic (PV) power generation is currently one of the most important ways to utilize solar energy. PV power has strong uncertainties and is adverse to the stability of the electricity grid. PV power forecast is an important method to tackle this issue. Conventional methods only use historical PV power data. This paper proposes a new method that uses deep Convolutional Neural Networks (CNN)-based multivariable information fusions for PV forecast. Multiple variables including global horizontal irradiation (GHI), relative humidity, air temperature, cloud thickness, wind speed, etc. are used for PV forecast. Meanwhile, clear-sky GHI estimated by McClear clear-sky models are used as physical prior knowledge. Through the attention mechanism, these variables are adaptively fused with the historical PV power data to realize an accurate PV power forecast. Forecast experiments in three-year (2017-2019) actual data of Brussels PV power stations verify the significant superiority of the proposed method over conventional forecast methods. © 2023 IEEE.

关键词： attention mechanism convolutional neural network photovoltaic power forecast solar energy

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A Finite-time Distributed Cooperative control Approach for Microgrids

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CSEE Journal of Power and Energy Systems 2022年第4期8卷 1194-1206页

作者： Jiancheng Zhang Xinsheng Wang Lingyu Ma Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150006China Department of Information Engineering Shandong Management UniversityJinan 250100China

Reactive power sharing cannot be achieved using many existing microgrid(MG)control methods,but the convergence speed of these methods is *** solve these problems,a finite-time distributed control approach is proposed in this paper,which is based on the hierarchical control *** hierarchical control structure consists of a dual loop control,a droop control used as a primary control and a secondary ***,the secondary controller is modeled,and the MG system composed of distributed generators(DGs)is considered as a multi-agent *** secondary controller consists of a frequency regulator,voltage regulator and power ***,the adaptive virtual impedance module is established,using the output of the reactive power regulator as its ***,a dual loop controller is combined with a primary controller and secondary controller to generate a pulse width modulation(PWM)signal to control the power and voltage of the *** order to reduce the fluctuation of the MG,a damping module is introduced when the structure of the system ***,the stability of the proposed control strategy is proved by the related theorems.A simulation system is established in the Matlab environment,and the simulation results show that the proposed method is effective.

关键词： Consensus droop control finite-time microgrid power sharing virtual impedance

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A Contact-Aided Model for Soft Continuum Robots Moving in Unstructured Environment

A Contact-Aided Model for Soft Continuum Robots Moving in Un...

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2024 China Automation Congress, CAC 2024

作者： Jingyu, Zhang Qin, Fang Mingjian, Sun Rong, Xiong Wang, Yue Haojian, Lu School of Information Science and Engineering Harbin Institute of Technology Weihai China Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Department of Control Science and Engineering Harbin Institute of Technology Heilongjiang China

ISBN: (纸本)9798350368604

Due to their inherent flexibility and high human-computer interaction potential, soft continuum robots have been developed and popularized in industrial and medical scenarios. However, when moving in an unstructured environment, the contact with environment will change the configuration parameters of the robot, which brings problems to the control. Aiming at improving the control performance of soft continuum robots in an unstructured environment, a contact-aided model is proposed to estimate the varying configurations of the robot. Besides, a model-based controller is proposed to control the robot in an unstructured environment. To verify the performance of the proposed method, a small-scale soft continuum robot is designed and fabricated. Through the characterization experiment, the robot shows a large workspace by changing the contact position, and the kinematic model is verified. Through the trajectory tracking experiment, the robot showed good accuracy, with an average error of 1.2mm. Through an exploration experiment in the unstructured environment, the robot showed good control effect, with an average error of 1.9mm. This work enhances the application capability of the soft continuum robots in unstructured environments. © 2024 IEEE.

关键词： Microrobots

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A dual-path instance segmentation network based on nuclei contour in histology image

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Discover Artificial Intelligence 2023年第1期3卷 35页

作者： Li, Jiangqi Li, Xiang Li, Minglei Yan, Pengfei College of Mathematical Sciences BoHai University JinZhou121000 China Department of Control Science and Engineering Harbin Institute of Technology Harbin150001 China

Accurate segmentation of nuclei in histology images is essential for digital pathology. However, previous work should have considered integrating nuclei contour information into network learning. The main problems are (1) nuclei contour information needs to be fully considered, resulting in inaccurate spatial location of nuclei. (2) Small nuclei in dense regions or irregularly shaped nuclei cannot be segmented. (3) Mainstream networks consider more long-distance semantic information and larger receptive fields and do not consider the fusion of feature maps with different semantics. To solve the above problems, we have proposed a contour-based dual-path instance segmentation network. Firstly we reconstructed the nuclei contour information using algorithms and morphological manipulations. Provide input for subsequent contouring networks. Then we designed a dual-path network. It can extract nuclei features and contour features independently in the encoding stage and fuse the feature maps at different scales in the decoding stage. In the decoding stage, we use the attention module with a newly designed fusion mechanism, which allows us to fuse different semantics of feature maps for simple and efficient fusion. Finally, using the watershed algorithm, we use the network segmentation results to get the instance segmentation results of the nuclei. We used four publicly available datasets, including Kumar, CPM-15, CPM-17, and TNBC, which contain the nuclei of many organs and different forms of nuclei in the human body. Compared with the mainstream methods, we obtained the best AJI metrics, which are 0.656,0.717, and 0.602. In conclocess can effectively improve the performance of the nuclei instance segmentation network. It can accurately locate the scattered nuclei in space with small segmented nuclei in dense regions. © The Author(s) 2023.

关键词： Semantics

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Sneak Circuit Analysis Covering Interface Circuits in Spacecraft Integrated Chips while Considering Faults 6

Sneak Circuit Analysis Covering Interface Circuits in Spacec...

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6th International Conference on System Reliability and Safety engineering, SRSE 2024

作者： Liu, Weiming Chen, Cen Xiao, Kaiwen Feng, Mingtao Zhang, Haonan Zhai, Guofu Harbin Institute of Technology Department of Electrical Engineering & Automation Harbin China Beijing Aerospace Automatic Control Institute Beijing China Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350356083

Sneak circuit analysis is a crucial reliability design process. In the design of spacecraft electronic systems, it is challenging to identify sneak circuits related to integrated chip interface circuits, and there are few targeted researches. In extreme working conditions, the coupling sneak circuits caused by the failure of integrated chips are difficult to identify, affecting the design optimization. The paper proposes a typical interface information specification model for integrated chips to simulate the electrical information characteristics of interfaces. And the typical failure models of intrinsic components inside the chip are determined through multi-physics field analysis. Then, based on the digital model, a sneak circuit diagnosis process based on excitation and fault injection are proposed, and a sneak circuit screening method based on Python virtual prototyping is implemented in the case study. Finally, the design constraint clues for the chip's external circuit are obtained, which provides a reference for related fault diagnosis and reliability optimization works. © 2024 IEEE.

关键词： Integrated circuit design

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Improvement of Steering Performance for Autonomous Vehicles Based on Preview Model 42

Improvement of Steering Performance for Autonomous Vehicles ...

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42nd Chinese control Conference, CCC 2023

作者： Yang, Zipeng Zhao, Linhui Zhao, Xinyi Liu, Haifeng Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China

ISBN: (纸本)9789887581543

This paper presents an approach to traveling along a reference path and evading obstacles with smooth steering angle for autonomous vehicles when trajectory planner and control run asynchronously. Trajectory in this paper is composed of position and time information, which is produced through decision maker, reference line calculator, trajectory smoother and speed planner. In order to restrain possible oscillation of steering angle, a vehicle dynamic model with preview is applied. It is transformed into a standard form of state space and can be directly used in control. Considering the control runs at a higher frequency than planning, a progression method coordinating these two parts is applied, which bases on time points on the trajectory and matches points with vehicle position after preview. The simulation results demonstrate improvement on the smoothness of steering angle. And vehicle's lateral error on tracking trajectory is kept small. © 2023 Technical Committee on control theory, Chinese Association of Automation.

关键词： Trajectories

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Multi-vision Based 3D Reconstruction System for Robotic Grinding 18

Multi-vision Based 3D Reconstruction System for Robotic Grin...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Zhang, Qimin Cao, Yu Wang, Qiang Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China

ISBN: (纸本)9798350312201

High-precision grinding process often requires to plan the grinding paths based on the reconstructed models of the workpieces. This paper presents a multi-vision based 3D reconstruction system which uses four industrial cameras to capture RGB images from multiple angles to reconstruct the 3D models of the workpieces to be ground. Feature extraction, feature matching and loop closure correction were applied for reconstructing the rough outline of the workpiece. Then we used depth map estimation and fusion to expand sparse point clouds into denser point clouds to improve the reconstruction performance. Poisson reconstruction was finally used to repair the voids on the surface to get a smooth model. The experimental results show that this system can obtain a complete and accurate 3D point cloud model of the workpiece in preparation for the path planning of the robotic grinding. © 2023 IEEE.

关键词： Feature extraction

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Fault diagnosis of control moment gyroscope based on a new CNN scheme using attention-enhanced convolutional block

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Science China(Technological Sciences) 2022年第11期65卷 2605-2616页

作者： ZHAO HaoTian LIU Ming SUN YiYong CHEN Zhang DUAN GuangRen CAO XiBin Research Center of Satellite Technology School of AstronauticsHarbin Institute of TechnologyHarbin 150001China School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Department of Automation TsinghuaUniversityBeijing 100084China Control Theory and Guidance Technology School of AstronauticsHarbin Institute of TechnologyHarbin150001China

control moment gyroscope(CMG)is a typical attitude control system component for satellites and mobile robots,and the online fault diagnosis of CMG is crucial because it determines the stability and accuracy of the attitude control *** paper develops a data-driven CMG fault diagnosis scheme based on a new CNN *** this design,seven types of fault signals are converted into spectrum datasets through short-time Fourier transformation(STFT),and a new CNN network scheme called AECB-CNN is proposed based on attention-enhanced convolutional blocks(AECB).AECB-CNN can achieve high training accuracy for the CMG fault diagnosis datasets under different sliding window ***,simulation results indicate that the proposed fault diagnosis method can achieve an accuracy of nearly 95%in 1.28 s and 100%in 2.56 s,respectively.

关键词： fault diagnosis control moment gyroscope CNN scheme attention-enhanced convolutional block

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