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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Yong, Panxiao Jia, Yubin Guo, Jun Zhou, Jun Liu, Zhimin Southeast University School of Automation Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9798350303636

High voltage direct current (HVDC) lines allow low-loss transmission over long distances. The multi-terminal HVDC network consists of multiple terminals connected by HVDC lines, and each area shares the frequency reserve. Through secondary frequency control, the frequency of AC and DC areas can be regulated back to the set point when the system frequency has deviated. In this paper, a data-driven model predictive control (MPC) strategy is proposed. The Kooman operator is used to obtain the high-dimensional linear model of a nonlinear system, and the Deep Learning method is used to approximate the infinite-dimensional Koopman operator. The nominal MPC is used for optimization and control, and the optimal problem is solved for the Koopman linearized system. The optimal control is applied to the original nonlinear system. Simulation results show the effectiveness of the proposed method. © 2023 IEEE.

关键词： data-driven Koopman operator model predictive control Multi-terminal HVDC

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Non-convex Optimization Based On Deep Koopman Operator 38

Non-convex Optimization Based On Deep Koopman Operator

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Guo, Jun Jia, Yubin Yong, Panxiao Zhou, Jun Liu, Zhimin Southeast University School of Automation Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9798350303636

Non-convex optimization problems are prevalent in various fields, and finding the global optimal solution for such problems remains challenging. This paper proposes an optimization method based on deep Koopman operator, which leverages the power of deep neural networks to provide a data-driven architecture for the Koopman function. The Koopman operator is used to linearly represent non-convex problems, and the proposed method utilizes model predictive control to optimize the resulting linear systems. Simulation results show that this method can solve the non-convex optimization problem effectively, quickly and accurately, while obtaining the global optimal solution. © 2023 IEEE.

关键词： Koopman operator model predictive control Non-convex

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Interval analysis for neural networks with application to fault detection

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Science China(Information Sciences) 2024年第11期67卷 222-237页

作者： Zhenhua WANG Youdao MA Song ZHU Thach Ngoc DINH Yi SHEN Department of Control Science and Engineering Harbin Institute of Technology National Key Laboratory of Complex System Control and Intelligent Agent Cooperation School of Mathematics China University of Mining and Technology The CEDRIC-Lab Conservatoire National des Arts et Métiers (CNAM)

This paper investigates an interval analysis method for neural networks and applies it to fault detection for systems with unknown but bounded measurement noise. First, a novel interval analysis method is presented, which can compute the bounds of the output of a feedforward neural network subject to a bounded input. By applying the proposed interval analysis method to a network trained with fault-free system data, adaptive thresholds for fault detection are computed. Finally, one can acquire fault detection results via a fault detection strategy. The proposed method can achieve tight bounds of the network output and employ simple operations, which leads to accurate fault detection results and a low computational burden.A numerical simulation and an experiment on an AC servo motor are given to illustrate the effectiveness and superiority of the proposed method.

关键词： interval analysis feedforward neural network fault detection adaptive thresholds

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Creation and integration mechanism of instrumentation flexible developing system

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机械工程前沿 2011年第2期6卷 235-240页

作者： Xiaoli XU Qiushuang LIU Beijing Key Laboratory Measurement and Control of Mechanical and Electrical System Beijing Information Science & Technology University Beijing 100092 China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081 China Beijing Key Laboratory Measurement and Control of Mechanical and Electrical System Beijing Information Science & Technology University Beijing 100092 China

To solve many key technical problems during the development of modern instrumentation system integration and provide a new mode and fundamental technical equipment for the research and development (R&D) of modern instrumentation products, based on the concept of an instrumentation flexible developing system (IFDS), this paper discusses the creation and open flexible integration mechanism, perfects the integrated supporting environment and integrated system of the flexible interconnection, and constructs the new flexible integrated system. Based on the operation mechanism of the modern instrumentation developing system and the research and optimization of the rapid integration design method, the paper emphasizes the dynamic integrating method of multiple types of knowledge in a modem instrument R&D system, to effectively utilize the rich integrated resource and achieve rapid integration of the system. Applications show that the new IFDS can improve the integration level and efficiency of R&D of the modern instrumentation system, enforce the reliability of the system, shorten the R&D period, and reduce the development costs.

关键词： modern instrumentation developing flexible interconnection flexible integration mechanism rapid integration system dynamic integrating method

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Bearing fault signal detection based on whale algorithm to optimize stochastic resonance parameters 34

Bearing fault signal detection based on whale algorithm to o...

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第34届中国控制与决策会议

作者： Huang Weichao Zhang Ganggang Faculty of automation and Information Engineering Xi'an University of Technology Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781665478977

Aiming at the problem that the traditional stochastic resonance system cannot adaptively adjust the structural parameters in the bearing fault signal detection,this paper proposes a parameter adaptive stochastic resonance bearing fault signal detection method based on the whale optimization *** method is based on the bistable stochastic resonance system model,and the structural parameters of the bistable stochastic resonance are optimized through the adaptive whale algorithm,so that the fault signal is enhanced,and the bearing fault signal detection is *** method was verified by actual bearing fault signals,and a series of comparative experiments were carried *** results show that the method in this paper has a simple model,few algorithm parameters,fast convergence speed,and a large output signal-to-noise ratio of the stochastic resonance system,which can accurately and efficiently detect bearing fault signals.

关键词： Stochastic Resonance Whale Optimization Algorithm Bearing Failure Signal

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Mean-square exponential stability for stochastic time-varying delay systems with Markovian jumping parameters:a delay decomposition approach

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Journal of systems engineering and Electronics 2011年第5期22卷 816-824页

作者： Li Ma Feipeng Da Key Laboratory of Measurement and Control for Complex Systems of Engineering Ministry of Education Research Institute of Automation Southeast University Nanjing 210096 E R. China College of Electronic and Information Engineering Jiangsu University Zhenjiang 212013 P. R. China

The mean-square exponential stability problem is investigated for a class of stochastic time-varying delay systems with Markovian jumping parameters. By decomposing the delay interval into multiple equidistant subintervals, a new delay-dependent and decay-rate-dependent criterion is presented based on constructing a novel Lyapunov functional and employing stochastic analysis technique. Besides, the decay rate has no conventional constraint and can be selected according to different practical conditions. Finally, two numerical examples are provided to show that the obtained result has less conservatism than some existing ones in the literature.

关键词： stochastic systems time-varying delay Markov chain linear matrix inequality （LMI）.

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Robot Visual Sliding Mode Servoing using SIFT Features 35

Robot Visual Sliding Mode Servoing using SIFT Features

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第35届中国控制会议

作者： XIN Jing RAN Bao-jing MA Xiao-min School of Automation & Information Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

To solve the robot visual servoing problem in the natural scene,a robot visual sliding servoing method using SIFT features in the framework of epipolar-geometry-based visual servoing is ***,corresponding image feature points from the current image feature and the desired image are obtained by SIFT algorithm;Then the features error of the whole robot visual servoing system are calculated according to the corresponding points;Finally,considering characteristics of epipolar geometry for robot visual servoing system,the rotation sliding mode controller and translation sliding mode controller are sequentially designed to calculate the rotation movement and translation movement of the robot *** positioning experiments on a 6DOF industrial robot demonstrate that the proposed method can effectively locate an object in the natural scene.

关键词： Epipolar geometry Visual servoing Sliding mode control SIFT features

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Prescribed-Time Nash Equilibrium Seeking for Pursuit-Evasion Game

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1518-1520页

作者： Lei Xue Jianfeng Ye Yongbao Wu Jian Liu D.C.Wunsch Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationNanjing 210096 School of Automation Southeast UniversityNanjing 210096China Department of Electrical and Computer Engineering Missouri University of Science and TechnologyRollaMO 65409 USA IEEE

Dear Editor,This letter is concerned with prescribed-time Nash equilibrium(PTNE)seeking problem in a pursuit-evasion game(PEG)involving agents with second-order *** order to achieve the prior-given and user-defined convergence time for the PEG,a PTNE seeking algorithm has been developed to facilitate collaboration among multiple pursuers for capturing the evader without the need for any global ***,it is theoretically proved that the prescribedtime convergence of the designed algorithm for achieving Nash equilibrium of ***,the effectiveness of the PTNE method was validated by numerical simulation results.A PEG consists of two groups of agents:evaders and *** pursuers aim to capture the evaders through cooperative efforts,while the evaders strive to evade *** is a classic noncooperative *** has attracted plenty of attention due to its wide application scenarios,such as smart grids[1],formation control[2],[3],and spacecraft rendezvous[4].It is noteworthy that most previous research on seeking the Nash equilibrium of the game,where no agent has an incentive to change its actions,has focused on asymptotic and exponential convergence[5]-[7].

关键词： seeking prescribed convergence

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Visual Navigation for Mobile Robot with Kinect Camera in Dynamic Environment 35

Visual Navigation for Mobile Robot with Kinect Camera in Dyn...

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第35届中国控制会议

作者： XIN Jing JIAO Xiao-liang YANG Yin LIU Ding School of Automation & Information Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

To solve the problem of the visual navigation for mobile robot in dynamic environment,a visual navigation system for mobile robot with Kinect camera is ***,the improved RBPF(RAO Blackwellized particle filters) algorithm is used to build the 2D grid map of the indoor environment and on the basis of this map operation of inflating obstacles is applied to build the global grid map considering the actual size of the ***,cost map using motion primitives is built while using this cost map,anytime Repairing A*(ARA*) global path planning algorithm,which has property of anytime algorithm,is combined with Dynamic Window Approach(DWA) local path planning algorithm to plan a smooth path from start point to target point and generate the optimal control input for robot ***,the adaptive monte carlo localization method(KLD-Sampling) is used to locate the robot and then a visual navigation system for mobile robot with Kinect camera is *** indoor mobile robot navigation experiment results show that the designed robot navigation system can plan a smooth path which is in accordance with robot kinematics and autonomously avoid the static and moving obstacles in the environment.

关键词： Kinect Camera Motion primitives Cost map Visual navigation Dynamic environment

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Effective Indoor Fire Detection with Channel Shuffle Module 21

Effective Indoor Fire Detection with Channel Shuffle Module

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5th International Conference on Computer Science and Application engineering, CSAE 2021

作者： Ge, Haotian Cao, Yichao Lu, Xiaobo School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781450389853

In recent years, methods based on computer vision and deep learning become the mainstream approaches in fire detection. However, the expensive computation cost of 3D convolutional neutral network (CNN) is unbearable and it is difficult for them to capture the fire regions of videos in time. In this paper, we design a module named channel shuffle module (CSM) based on 2D CNN to keep the balance between computation cost and accuracy. By fusing RGB frame and differential frame, CSM improves the ability of 2D CNN in temporal information extraction which much less cost than methods based on 3D CNN. Four different structures of CSM are proposed and we choose the best one by experiment results. Also, experiments prove that the performances of TSN and TSM are improved with CSM in sequence classification. The accuracy of TSM with CSM is 99.2045%, false positive rate reaches 0.7890% and false negative rate reaches 0.4530%, which demonstrates the efficiency of CSM in temporal feature modeling.. © 2021 Association for Computing Machinery. All rights reserved.

关键词： Fires

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