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第41届中国控制会议

作者： Pengyang Fan Chao Zhai School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In the problem of multi-agent coverage,a group of agents are required to cover a given region or clean the workload as soon as *** workload partition can improve the work efficiency of multi-agent *** addition,the communication delays play a key role in the stability of multi-agent ***,a distributed control algorithm of workload partition with time delay is proposed in this ***,an approach based on nonlinear matrix inequality is presented to find the maximum delay of multi-agent ***,experiments are carried out to investigate the effect of delay on system stability on the ZigBee platform.

关键词： Multi-agents systems Time delay Nonlinear matrix inequality Distributed algorithm Workload partition

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Multi-Agent Cooperative Localization via Extraction and Matching of Image Feature 41

Multi-Agent Cooperative Localization via Extraction and Matc...

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第41届中国控制会议

作者： Xiong Lei Yulin Xu Chao Zhai School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In multi-agent system(MAS),it is of great significance to study the problem of cooperative *** this work,we propose a vision-based cooperative localization scheme for multi-agent systems equipped with RGB-D ***,we formulate the cooperative localization problem of ***,the relative pose between agents with overlapping field of view in MAS can be solved by using an improved feature extraction and matching algorithm,which requires the index function to screen the unimportant feature points in the image to reduce the computation *** system does not require all agents to have a common area of view,and we can calculate the relative pose between agents whose field of view does not overlap at all by accumulating the ***,experiments are carried out to validate the effectiveness and feasibility of this method.

关键词： Multi-agent system Cooperative localization Feature extraction and matching Index function

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An Improved SimAM Based CNN for Facial Expression Recognition 41

An Improved SimAM Based CNN for Facial Expression Recognitio...

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第41届中国控制会议

作者： Lan-Qin Zhang Zhen-Tao Liu Cheng-Shan Jiang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

To achieve effective deployment of the facial expression recognition(FER) system on marginalized devices,we designed a lightweight neural network based on ShufflenetV2,which can balance the relationship between the number of network parameters and the accuracy of *** this paper,a non-parameter SimAM attention module that can extract 3 D features is employed in the ShufflenetV2 network to enhance the spatial features extraction ability of the network,and the shortcut branch is introduced in Bottleneck for information interaction and feature fusion between *** tests were carried out on the RaFD dataset,and the recognition accuracy reaches 98.04%,while the number of model parameters is only 1.4 M.

关键词： Facial expression recognition Shufflenet SimAM Lightweight Neural Network

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A hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction

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Energy and AI 2024年第4期18卷 368-379页

作者： Weipeng Li Yuting Chong Xin Guo Jun Liu School of Automation and Information Engineering Xi’an University of TechnologyNo.5 Jinhua South RoadXi’an710048ShaanxiChina Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing No.5 Jinhua South RoadXi’an710048ShaanxiChina

Efficient and accurate wind power prediction is crucial for enhancing the reliability and safety of power *** data-driven forecasting methods are regarded as an effective ***,the inherent randomness and nonlinearity of wind power systems,along with the abundance of redundant information in measurement data,present challenges to forecasting *** integration of precise and efficient techniques for data feature decomposition and extraction is essential in conjunction with advanced driven data-forecasting *** on the seasonal variation characteristics of wind energy,a hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction is *** effectiveness and superiority of the proposed method in predictive accuracy are demonstrated through comprehensive multi-model experiment comparisons.

关键词： Wind power prediction Data-driven Hybrid model Seasonal feature decomposition Gated recurrent networks Attention mechanism

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An Inverse Kinematic Optimization Method for the S-R-S Redundant Manipulator Considering Joint Limit and Singular Position Avoidance 41

An Inverse Kinematic Optimization Method for the S-R-S Redun...

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第41届中国控制会议

作者： Yisheng Mei Xin Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Aiming at the problem of how to avoid the joint limit and singular position in continuous trajectory planning of the S-R-S redundant manipulator,a new inverse kinematics optimization algorithm is proposed in this ***,according to the special geometry of S-R-S manipulator,we take the arm angle as the redundant parameter to obtain the joint angle expressions under the given tip pose and arm *** we discuss the feasible arm angles under joint limit in nonsingular and singular cases,and give a complete method to obtain the effective arm ***,we introduce the concept of virtual force to represent the degree that the joint is far from the limit,and define the optimization objective function with the virtual force as the weight to avoid joint limit,the complex relationship between the arm angle and joint angles is linearized by the difference method to simplify the objective function to quadratic function,combine with the feasible arm angle range,we realize singularity avoidance and joint limit avoidance at the same *** simulation result shows that compared with the traditional algorithm,the algorithm proposed in this paper has better joint limit avoidance ability on the premise of avoiding singularity which reflects the superiority of the algorithm and can be used for the motion planning of the manipulator in practical engineering.

关键词： Arm angle Singular position avoidance Joint limit avoidance Inverse kinematic optimization

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Design of Intelligent Monitoring System for Blast Furnace Hearth Erosion 41

Design of Intelligent Monitoring System for Blast Furnace He...

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第41届中国控制会议

作者： Shuqiao Wang Yan Yuan Jingjie Liang Zhuofu Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper takes the iron-making blast furnace in operation of a steel plant as the specific object,analyzes the erosion status and characteristics of different parts of the furnace hearth and bottom combined with iron-making process and erosion mechanism of the blast furnace,designs an intelligent monitoring system for erosion of the furnace hearth lining,visualizes the temperature measurement *** erosion calculation model is established by using the heat transfer mechanism to quickly solve the erosion boundary for the area with low erosion degree and rate,and performs a fast solution of the erosion *** areas with high erosion degree and rate,the particle swarm optimization algorithm is selected by using its adaptive *** solves the erosion boundary accurately from the rough solution of the mechanism model,and the residual thickness of furnace lining is output and displayed,which helps ironmakers optimize the blast furnace production operation,maintenance strategy,improve production efficiency and reduce energy consumption.

关键词： Blast furnace lining erosion Particle swarm optimization algorithm Intelligent monitoring system

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Finite-time H∞ state estimation for genetic regulatory networks with observations of two hidden-Markov modes 41

Finite-time H∞ state estimation for genetic regulatory netw...

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第41届中国控制会议

作者： You Wu Xiongbo Wan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper investigates the problem of finite-time H state estimation for discrete time-delayed genetic regulatory networks（GRNs） with observations of two hidden-Markov modes.A new GRN model with two Markov jump delays is proposed,of which the mode observations are governed by two hidden-Markov *** sufficient conditions are derived,which guarantee the finite-time boundedness of the estimation error dynamics with prescribed H disturbance attenuation *** state estimator parameters are designed by solving several matrix inequalities.A numerical example is given to illustrate the validity of our results.

关键词： Genetic regulatory networks finite-time H_∞ state estimation hidden Markov model Markov jump delays

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Prediction Method of Blast Furnace Fuel Ratio Based on Spectral Clustering and Extreme Learning Machine Model 41

Prediction Method of Blast Furnace Fuel Ratio Based on Spect...

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第41届中国控制会议

作者： Jingjie Liang Yan Yuan Shuqiao Wang Zhuofu Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The blast furnace fuel ratio,as the main index reflecting the blast furnace fuel consumption,plays an important role in guiding blast furnace *** order to solve the problem of insufficient stability of the existing fuel ratio prediction model under the condition of process parameters fluctuation,a prediction method of blast furnace fuel ratio based on spectral clustering and extreme learning machine model is ***,on the basis of analyzing the influencing factors of fuel ratio,the classification results after clustering are visualized with t-SNE dimension reduction downscaling and spectral clustering method;Secondly,for the classification results after clustering,the extreme learning machine is used to establish the sub-models,and the PSO algorithm was used to optimize the input weights of hidden layer and the bias of hidden layer *** results show that the proposed method has high prediction accuracy.

关键词： Fuel Ratio Spectral Clustering Extreme Learning Machine(ELM) t-SNE Particle Swarm Optimization(PSO)

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Adaptive Leader-Following Consensus for a Class of Time Delay Multi-Agent systems 41

Adaptive Leader-Following Consensus for a Class of Time Dela...

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第41届中国控制会议

作者： Jiachun Sun Shiqi Zheng Liangguang Li Tao Song Qing Chang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,we study the leader-following consensus for multi-agent systems with long input time delay under jointly connected directed switching *** adopt an adaptive distributed observer that can make every agent estimate the information of the *** we propose a new controller utilizing the predictor feedback technique,and then map MAS s into ODE-PDE(Ordinary differntial equations-Partial differntial equations) target systems so that we can utilize Lyapunov-Krasovskii function to analyze the stability of the *** are used to vertify the results in the end.

关键词： Multi-agent system distributed observer long input delay directed switching network

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Particle Detection of complex Images Based on Convolutional Neural Network 41

Particle Detection of Complex Images Based on Convolutional ...

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第41届中国控制会议

作者： Yuting Ge Yi Liu Chi Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Particle Detection plays important roles in industrial and medical image ***-learning based methods can only deal with the particle images with simple backgrounds and sparse *** most neural network based methods can also hardly to deal with overlapping objects and small particles,besides,the huge amount of parameters of these methods also has a great demand for annotated data,which is difficult to ***,we use bright pixels to represent the spatial position of particles,and artificially divid the sizes of particles into multiple intervals.A feature representation called Light-spots Maps is proposed to replace the bounding box and pixel classifications in our detection *** Light-weight networks based on ResNets is used to transform the particle images into Light-spots maps to detect the particle *** experiments,we prove the effectiveness of our method.

关键词： Objects Detection Particles Detection Convolutional Neural Network

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