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第三十八届中国控制会议

作者： Mengxi Qin Xin Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Calligraphy is an important humanistic symbol of Chinese civilization. However, most of the calligraphy is incomplete, which has only a small number of Chinese characters circulating in the world. How to use these samples to efficiently restore the remaining calligraphy characters has always been considered as a difficult task. In this work, we propose Densenetpix2 pix model based style transfer method to solve this problem. By training some samples to learn the rules of transferring the printed font images to the calligraphy characters images, Densenet-pix2 pix can predict the remaining calligraphy characters. Our method modify the generation network and optimization strategies of style transfer, which improves the generation quality of the calligraphy characters and the stability of the model. In addition, we use pre-trained feature extraction models to extract content information and style information, and scientifically evaluate the quality of our generated calligraphy characters from these two aspects. We compared our method with several other baseline methods. The experimental results show that our method can effectively restore the remaining calligraphy characters, and the generated Chinese characters are more delicate.

关键词： Calligraphy characters Style transfer Restore Generation

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Bolt positioning method based on active binocular vision

Bolt positioning method based on active binocular vision

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第三十八届中国控制会议

作者： Xu Jian Xin Chen Zhe Xiao Yipu Sun School of Automation China University of Geoscience Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

We propose a position and posture measurement method based on active binocular vision to improve localization accuracy and stability of bolts in substation fittings. Firstly, we obtain the color image and the depth image of bolts and use shape-based template matching method to obtain the image coordinates of the bolts. Secondly, we obtain the 3 D coordinates of the bolts based on the binocular camera stereo vision model. Finally, based on the point-cloud information of bolts plane, we obtain the posture information of the bolts by using the least square method. The experimental results show that the binocular system designed in this paper can accurately identify the bolts and has good stability. Within 500 mm measurement range, the position measurement error rate of bolts is less than 0.8 %, and the angle measurement error of the fitting plane is less than 1°.

关键词： Substation fittings Bolt localization Active binocular vision Least squares method

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Target tracking algorithm based on convolutional neural network and particle filtering

Target tracking algorithm based on convolutional neural netw...

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第三十八届中国控制会议

作者： Lijun Zhang Peng Chen Hui Guo Shun Huang Wei Xia Cong Hu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Aiming at the phenomenon that the target particle tracking algorithm is affected by illumination changes and occlusion in the target tracking process, the goal is lost. A target tracking algorithm based on convolutional neural network and particle filtering is proposed. The algorithm uses the convolutional neural network to automatically learn the depth features of the target,and extracts the more abstract semantic information of the target. The semantic information makes the algorithm robust to the apparent changes of the target, which can alleviate the drift problem to some extent. The algorithm can effectively combine the target apparent model based on convolutional neural network with the particle filter framework. The experimental results show that compared with the other five algorithms in the particle filter framework, the algorithm can track the moving targets with partial occlusion and morphological changes more robustly.

关键词： Convolutional Neural Network Particle Filter Target Tracking

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Hidden-Markov-model-based finite-time fault detection for networked singularly perturbed systems

Hidden-Markov-model-based finite-time fault detection for ne...

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第三十八届中国控制会议

作者： Jiankang Li Xiongbo Wan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In this paper, the problem of finite-time fault detection(FD) is investigated for networked discrete-time singularly perturbed systems under the stochastic communication protocol(SCP). To alleviate the undesired data collisions caused by largescale data transmissions via the bandwidth-limited communication network, the SCP modeled by a Markov chain is *** to practical factors such as observation error, the Markov modes of the SCP are assumed to be available to the fault detection filter(FDF) according to a hidden Markov process. Our aim is to design a hidden-Markov-model-based FDF as the residual generator such that the resulting augmented system is stochastically H∞ finite-time bounded. A sufficient condition in terms of linear matrix inequalities(LMIs) is derived which ensures the existence of such an FDF. The parameters of the desired FDF are explicitly given when there exist feasible solutions to these LMIs. Finally, the effectiveness of the FD method is demonstrated by a numerical example.

关键词： Finite-time fault detection Singularly perturbed systems Hidden Markov model Stochastic communication protocol

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On Ground Penetrating Radar Imaging Method Based on Compressed Sensing in Multi-target Environment

On Ground Penetrating Radar Imaging Method Based on Compress...

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第三十八届中国控制会议

作者： Guangjun Wang Chengyong Ma Jianjin Jiang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Recently, compressed sensing(CS) has been widely used in ground penetrating radar(GPR) imaging due to its low sampling time, high quality performance and high quality imaging results in underground imaging. However, for densely distributed underground multi-target, the error of GPR imaging based on CS is large. So, this paper proposes a filter matrix,which can effectively reduce the energy of B-scan hyperbolic arms, increase the hyperbolic apex energy, and reduce the error of GPR imaging based on CS in densely distributed multi-target environment. The algorithm also takes into account the distance between the antenna and the ground. At first, a method of the normalized is used to calculate the echo data. Then the filter matrix designed in this paper is used. Experimental results present that the filter matrix can effectively reduce the imaging error in multi-target environment.

关键词： Compressed sensing(CS) underground imaging ground penetrating radar(GPR) multi-target

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Optimal Trajectory Planning Based on Improved Adaptive Genetic Algorithm for a 6 DOF Manipulator

Optimal Trajectory Planning Based on Improved Adaptive Genet...

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第三十八届中国控制会议

作者： Haoyang Zhang Yan Yuan Xin Chen School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper is concerned with the optimal trajectory planning for a 6 degree-of-freedom(DOF) manipulator, where the energy minimization is considered under the constraint of power. Firstly, based on the establishment of kinematics model, the influence of main factors on power is analyzed by using Jacobian matrix and Lagrange equation. Then the energy consumption is calculated as the objective function by the power consumption of each joint, and in order to obtain the desired trajectory for the arm, each joint locus is approximated by a 3-5-3 spline interpolation curve. To this end, in order to obtain the most reliable solutions for trajectory planning, the improved adaptive genetic algorithm(IAGA) is used to optimize the energy under the constraint of power, speed and acceleration, and the crossover rate and mutation rate are effectively adjusted with ***, we conduct the simulation by using the dynamics analysis software-ADAMS. The results demonstrate the effectiveness of minimizing the optimized energy in the case of constrained power mainly.

关键词： Energy optimization trajectory planning improved adaptive genetic algorithm

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Modeling and Optimization of the Activated Sludge Process

Modeling and Optimization of the Activated Sludge Process

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第三十八届中国控制会议

作者： Shun Huang Lijun Zhang Hui Guo Peng Chen Wei Xia Cong Hu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In the process of urban sewage treating, reducing the energy consumption and improving the quality of the effluent are significantly meaningful. According to the activated sludge method, the key factors affecting the energy consumption and water quality of wastewater treatment are determined. In order to minimize the energy consumption of the activated sludge process and maximize the quality of the effluent, four different objective functions are modeled [i.e., the airflow rate, the carbonaceous biochemical oxygen demand(CBOD) of the effluent, the total phosphorus(TP) of the effluent, and the ammonia nitrogen of the effluent(NH4-N)]. These models are developed using a back propagation(BP) neural network based on industrial data, and dissolved oxygen(DO) is the controlled variable. A multi-objective model was evaluated by six evaluation indicators. Based on the analysis of the model and the mechanism of activated sludge process, the multi-objective particle swarm optimization(MOPSO)algorithm was used to optimize the energy consumption and water quality of the activated sludge process. The experimental results show that eventually reduce aeration energy consumption by 17%.

关键词： Activated sludge Wastewater treatment Energy consumption Back propagation neural network Multi-objective particle swarm optimization

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Dynamic event-triggered communication based fault detection for networked singularly perturbed systems

Dynamic event-triggered communication based fault detection ...

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第三十八届中国控制会议

作者： Tizhuang Han Xiongbo Wan Jianqi An School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper investigates the problem of fault detection(FD) for networked singularly perturbed systems under the dynamic event-triggered communication. To save the network resources, a dynamic event-triggered communication mechanism(DETCM) is proposed, which contains some existing triggering mechanisms as special cases. Our aim is to design a fault detection filter(FDF) under such a DETCM, which ensures that the resulting filtering error dynamics of FD is asymptotically stable and satisfies an H∞ performance requirement. By constructing a Lyapunov function dependent on both the singular perturbation parameter(SPP) and flexible variable of the DETCM, a sufficient condition is obtained in terms of linear matrix inequalities(LMIs), which ensures the existence of the desired FDF. When these LMIs have feasible solutions, the parameters of the FDF are explicitly given and the admissible upper and lower bounds of the SPP are evaluated. A numerical example is provided to demonstrate the effectiveness of the design method of the FDF.

关键词： Fault detection Dynamic event-triggered communication Singularly perturbed systems Networked systems

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Large-scale hyperspectral image clustering using contrastive learning

arXiv

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arXiv 2021年

作者： Cai, Yaoming Zhang, Zijia Liu, Yan Ghamisi, Pedram Li, Kun Liu, Xiaobo Cai, Zhihua School of Computer Science China University of Geosciences Wuhan430074 China Helmholtz Institute Freiberg for Resource Technology Freiberg09599 Germany Vienna1030 Austria College of Electronic Science and Technology National University of Defense Technology Changsha410073 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan430074 China

Clustering of hyperspectral images is a fundamental but challenging task. The recent development of hyperspectral image clustering has evolved from shallow models to deep and achieved promising results in many benchmark datasets. However, their poor scalability, robustness, and generalization ability, mainly resulting from their offline clustering scenarios, greatly limit their application to large-scale hyperspectral data. To circumvent these problems, we present a scalable deep online clustering model, named Spectral-Spatial Contrastive Clustering (SSCC), based on self-supervised learning. Specifically, we exploit a symmetric twin neural network comprised of a projection head with a dimensionality of the cluster number to conduct dual contrastive learning from a spectral-spatial augmentation pool. We define the objective function by implicitly encouraging withincluster similarity and reducing between-cluster redundancy. The resulting approach is trained in an end-to-end fashion by batch-wise optimization, making it robust in large-scale data and resulting in good generalization ability for unseen data. Extensive experiments on three hyperspectral image benchmarks demonstrate the effectiveness of our approach and show that we advance the state-of-the-art approaches by large margins. Copyright © 2021, The Authors. All rights reserved.

关键词： Spectroscopy

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Voltage Sensitivity of Tag Antennas for Inductively Coupled RFID systems

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Journal of Physics: Conference Series 2021年第1期1738卷

作者： Cheng Jin Jixuan Zhu School of Automation China University of Geosciences (Wuhan) Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China

This paper describes a parameter of voltage sensitivity to recognize the performance differences of tag antennas for inductively coupled RFID systems. Based on the equivalent circuit model of the RFID tag and reader, an expression for the voltage sensitivity is educed. Then, the design steps of measuring platform to obtain the voltage sensitivity of tag antenna are introduced in detail. Finally, the feasibility of the proposed method was verified with the market available tag antennas through the measuring platform.

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