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42nd Chinese control Conference, CCC 2023

作者： Zhang, Feng-Yu Yu, Gang He, Shu-Han He, Wang-Yong School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Co. Ltd. Wuhan430074 China

ISBN: (纸本)9789887581543

Given the dual robots play a key role for collaborative work. In this paper, an improved method is proposed to find the kinematic positive solution based on its D-H parameters, model the dual SCARA robot in MATLAB environment, and solve the collaborative workspace point cloud map by Monte Carlo method. The proposed method extracts and plots the boundary curves of the collaboration space by improved the α-Shapes algorithm, and obtains the shape of the common region of the collaboration space of the dual SCARA robots and the limit position parameters in the collaboration space. It provides a theoretical basis for the research of path planning, trajectory planning, dynamics analysis, mechanism parameter optimization, self-avoidance, and anti-collision problems of the dual-robot collaborative system. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Monte Carlo methods

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Joint Local Contrast and First-Order Directional Derivative Methods for Detecting Infrared Small Targets in complex Backgrounds

IEEE Journal on Miniaturization for Air and Space Systems

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IEEE Journal on Miniaturization for Air and Space systems 2025年

作者： Zheng, Hanjia Zong, Xiaofeng China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

Infrared target detection technology is one of the most key technologies of current detection systems, which is not only applied to automatic navigation, security protection and surveillance devices in daily life, but also widely used in the military. However, due to the influence of complex background, infrared detection system is often difficult to achieve accurate and fast detection of small targets, so the current small target detection methods still need to be improved. In this paper, an effective algorithm is proposed by complementally combining local contrast and first-order directional derivative algorithms, incorporating human visual characteristics for enhancement. Then according to the different characteristics of the background and small targets in infrared images, for the problem of excessive redundant information in infrared weak small target images, the high real-time and low leakage rate of LCM is used to find out the information-rich suspicious blocks, and then the low false alarm rate of foDD is used to find out the targets in the suspicious area. Through a lot number of experiments, and comparing with a variety of other algorithms. The results show that the detection algorithm proposed in this paper is significantly better than other algorithms in terms of low false alarm rate and can maintain good real-time performance. © 2019 IEEE.

关键词： Infrared imaging

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Multi-Modal Based Fuzzy Atmosfield in Human-Robot Interaction 42

Multi-Modal Based Fuzzy Atmosfield in Human-Robot Interactio...

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42nd Chinese control Conference, CCC 2023

作者： Li, Xin-Heng Liu, Zhen-Tao Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

Recently, the emotional robot has basic functions of perceiving and expressing emotions, but it still hard to communicate naturally between humans and robots. One major reason is that communication atmosphere is seldom considered in Human-robot Interaction (HRI). We propose Multi-modal (i.e., music background, speech, and semantics) Based Fuzzy Atmosfield (FA), which can not only realize the dynamic adjustment of FA but also dynamically regulate human emotions. In the experiment, a Pepper robot is used and one hundred volunteers are invited for HRI, and soothing piano pieces are used as background music. Questionnaires were filled by the volunteers after the experiments, from which the results show that 90% of the volunteers felt the dynamic changes in the communication atmosphere and 77% of the volunteers felt significant emotional regulation, which demonstrates the effectiveness of our method. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Semantics

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Distributed Solver for Discrete-Time Lyapunov Equations over Dynamic Networks with Linear Convergence Rate

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IEEE Transactions on Cybernetics 2022年第2期52卷 937-946页

作者： Jiang, Xia Zeng, Xianlin Sun, Jian Chen, Jie Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

The problem of solving discrete-Time Lyapunov equations (DTLEs) is investigated over multiagent network systems, where each agent has access to its local information and communicates with its neighbors. To obtain a solution to DTLE, a distributed algorithm with uncoordinated constant step sizes is proposed over time-varying topologies. The convergence properties and the range of constant step sizes of the proposed algorithm are analyzed. Moreover, a linear convergence rate is proved and the convergence performances over dynamic networks are verified by numerical simulations. © 2013 IEEE.

关键词： Convex optimization

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A Memristive Spiking Neural Network Circuit for Bio-inspired Navigation Based on Spatial Cognitive Mechanisms

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IEEE Transactions on Biomedical Circuits and systems 2024年第3期19卷 686-698页

作者： Chen, Zhanfei Wang, Xiaoping Wang, Zilu Yang, Chao Huang, Tingwen Lai, Jingang Zeng, Zhigang School of Mechanical Engineering and Automation Shenzhen518055 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation China Hubei Key Laboratory of Brain-inspired Intelligent Systems Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China Guangxi University of Science and Technology School of Computer Science and Technology Liuzhou545006 China Shenzhen University of Advanced Technology School of Computer Science and Control Engineering Shenzhen518055 China

Cognitive navigation,a high-level and crucial function for organisms' survival in nature,enables autonomous exploration and navigation within the environment. However,most existing works for bio-inspired navigation are implemented with non-neuromorphic computing. This work proposes a bio-inspired memristive spiking neural network (SNN) circuit for goal-oriented navigation,capable of online decision-making through reward-based learning. The circuit comprises three primary modules. The place cell module encodes the agent's spatial position in real-time through Poisson spiking;the action cell module determines the direction of subsequent movement;and the reward-based learning module provides a bio-inspired learning method adaptive to delayed and sparse rewards. To facilitate practical application,the entire SNN is quantized and deployed on a real memristive hardware platform,achieving about a 21× reduction in energy consumption compared to a typical digital acceleration system in the forward computing phase. This work offers an implementation idea of neuromorphic solution for robotic navigation application in low-power scenarios. © 2007-2012 IEEE.

关键词： intelligent robots

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Tracking performance limitations of networked control systems with packet dropouts and logarithmic quantization 41

Tracking performance limitations of networked control system...

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第41届中国控制会议

作者： Jianhao Li Xiaowei Jiang Hao Chen Shaoying Wang Xianhe Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System College of Science Binzhou University School of Electrical Engineering and Automation Hubei Normal University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,we focus on the tracking performance(TP) limitations of networked control systems(NCS s).The control system considered is a multi-input and multi-output(MIMO) discrete-time network control system with time delay,channel noise,packet dropouts,and logarithmic quantization communication *** modeling the channel,we assumed the channel noise to be additive white Gaussian noise(AWGN) and used a binary random process to model packet dropouts and a logarithmic quantizer to model the quantization *** explicit expression of the TP limitations of NCSs utilizing the two-degree-of-freedom(TDOF) controller is then derived using the frequency-domain approach,coprime decomposition,and Youla parameterization *** results show that the essential characteristics of the plant(locations and directions of nonminimum phase zeros and unstable poles) and network constraints(time delay,packet dropouts,quantization,and noise power spectral density) are closely related to the TP limitations.

关键词： Networked control systems tracking performance limitations packet dropouts logarithmic quantization

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A Semi-Supervised Root Cause Identification Method for Alarm Floods via Graph-Based Manifold Regularization 43

A Semi-Supervised Root Cause Identification Method for Alarm...

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43rd Chinese control Conference, CCC 2024

作者： Chen, Ning Hu, Wenkai Liu, Zhe Wang, Fei China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China Petrochemical Company Limited Wuhan430082 China

ISBN: (纸本)9789887581581

An alarm flood is a situation where the alarm rate is too high and exceeds the operator's management ability. The occurrence and propagation of an alarm flood cause difficulties for the operators to respond to critical alarms in time, which may make the situation further deteriorate into an industrial accident. In this paper, a semi-supervised method is proposed for root cause identification of alarm floods via graph-based manifold regularization. A vector representation method for industrial alarm event data is presented based on word embedding for alarm textual encoding. A semi-supervised method is proposed to identify root causes of alarm floods based on both labeled and unlabeled alarm flood sequences. The effectiveness of the proposed method is demonstrated by a case study with data generated by a public industrial simulation model. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Semi-supervised learning

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Research on Image Segmentation of Power Line Based on Encoder-Decoder Network 16th

Research on Image Segmentation of Power Line Based on Encode...

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16th Annual Conference of China Electrotechnical Society, CES 2021

作者： Sun, Haotian Fang, Zhijian Wei, Zhiguo Xie, Fei School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9789811915277

Power line network is the main carrier of the power system, and the smooth patrol inspection plays a crucial role in the fault prevention of the power line network. With the emergence of the patrol inspection UAV, how to detect the target of the power line through the picture and carry out accurate positioning has become a major research focus of the intelligent power system. A method for detecting and locating power lines based on an encoding lightweight decoder network (EDN-light) is proposed in this paper. It provides a foundation for the research and development of intelligent inspection of power line network, such as detection and identification, fault location, and guarantee of operation safety, and puts forward a new solution to the fault location diagnosis of power line using image. By EDN-light network, it focuses on detecting high level target and eliminating irrelevant information such as background, the convolutional layer of the encoder is used for extracting features, and the deconvolutional layer of the decoder for reconstructing images. The EDN-light network can improve the detection accuracy, and generate high-quality segmentation object suggestions. Use Turkish Electricity Transmission Corporation's aviation power line network dataset and self-made dataset to train the model to improve the generalization ability of the model. Experiments have found that due to the fully convolutional network design, it can carry out multi-scale input, for power line image segmentation and detection, the accuracy is better, and the evaluation indicators of the proposed models have increased. And due to the design of the lightweight decoder, Without retraining the network, the learned model can be extended to unknown linear category targets without repeated training. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image segmentation

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An Informer Based Alarm Early Prediction Method over Consecutive Alarm Monitoring Periods 22

An Informer Based Alarm Early Prediction Method over Consecu...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Jiang, Wenbin Hu, Wenkai Liu, Zhe Wang, Fei School of Automation China University of Geosciences Wuhan430074 China Petrochemical Company Limited Wuhan430082 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798331527471

Alarm systems serve as the first layer of protection for modern process industries to monitor industrial processes and ensure operational safety. However, the presence of alarm floods is common in alarm systems and may distract operators from critical alarms. To provide decision supports to operators during alarm flood situations, alarm prediction becomes a potential effective solution. The difficulty of alarm prediction lies in how to achieve high prediction accuracy over long-term consecutive alarm monitoring periods, including situations with either high or low alarm rates. Consequently, this paper presents an industrial alarm prediction method for both alarm flood periods and non-alarm flood periods. Specifically, a strategy of combining fixed-length and fixed-time sliding windows is designed. Further, an alarm prediction model based on Informer is proposed for alarm prediction under different alarm rates. A case study is presented to prove the validity of the proposed alarm prediction method. © 2024 IEEE.

关键词： Alarm systems

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An Improved Synchronization Criterion for Time-Delayed Lur'e systems via Cubic Function Negative-Determination Lemma 42

An Improved Synchronization Criterion for Time-Delayed Lur'e...

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42nd Chinese control Conference, CCC 2023

作者： Peng, Yu-Fei Fan, Yu-Long He, Yong Shangguan, Xing-Chen School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

In this paper, the master-slave synchronization issue of chaotic Lur' e systems with time-varying-delay feedback control is investigated. Firstly, the synchronization problem of chaotic system is transformed into the stability problem of chaotic synchronization error system, which is studied based on Lyapunov-Krasovskii functional (LKF) method. Secondly, a novel augmented LKF with more cross terms that related to time-varying delay is proposed. Based on the application of the relaxation integral inequality and the reciprocally convex matrix inequality, an improved synchronization criterion is derived by using the cubic function negative-determination lemma. Finally, a numerical simulation example demonstrates the effectiveness and advantages of the proposed methods. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Synchronization

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