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Position control of planar three-link underactuated manipulator based on wavelet neural network model

Position control of planar three-link underactuated manipula...

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第三十九届中国控制会议

作者： Yawu Wang Huiqing Yang Pan Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper presents a control strategy for a planar three-link underactuated manipulator（UM） with a passive first link based on a wavelet neural network（WNN） model. Firstly, by using the particle swarm optimization（PSO） algorithm, the target angles of all links are calculated according to the established kinematic model and the given target position. Then, a WNN model is trained to describe the coupling relationship between the passive link and the second link. The difference between the current angle and the target angle of the passive link is converged to zero by repeatedly controlling the second link to rotate an angle which is calculated by the trained WNN model. Next, the active links are controlled to rotate to their target angles with low speeds. Finally, the effectiveness of the proposed control strategy is verified through experimental results.

关键词： planar underactuated manipulator position control wavelet neural network coupling relationship

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A Novel Eye State Detection Method via WBCNN

A Novel Eye State Detection Method via WBCNN

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第三十九届中国控制会议

作者： Zhen-Tao Liu Si-Han Li Cheng-Shan Jiang Dan-Yun Li Man Hao School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In the field of face recognition and analysis, eye state detection is an essential step, which is the prerequisite and breakthrough of drowsiness estimation and auxiliary driving. This paper presents an eye state detection method based on Weight Binarization Convolution Neural Network（WBCNN）. The weight of the network is constrained by binarization, which can limit the weight to 1 or-1, reducing the power dissipation and internal storage considerably. The human eye state features which can be extracted by convolution neural network effectively, and binary network not only contributes to reducing the storage size of the model, but also accelerates the computation. Experiments on eye state detection were conducted on the Closed Eyes in the wild（CEW） and FER2013 Databases, from which the results show that our method achieved average test accuracy of 97.41%on CEW. We used the FER2013 facial expression database for pre-training, which can make up for the lack of CEW training samples. The computational speed of non-binary is slower than binary network. Moreover, less storage capacity is required by our method.

关键词： Eye state detection Convolution neural network Image processing Weight Binarization

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Analysis of Bit-Rock Interaction Models Using Finite Element Simulation Data

Analysis of Bit-Rock Interaction Models Using Finite Element...

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第三十九届中国控制会议

作者： Hengyu Huang Min Wu Sike Ma Luefeng Chen Chengda Lu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

The study of bit-rock interaction model is essential to describe the rock breaking process. In practice, it is difficult to get downhole measurement, and the downhole rock-breaking data is difficult to obtain. Therefore, this paper uses finite element simulation to obtain the kinetic data of bit-rock interaction, based on the analysis and comparison of existing models, an effective analysis method is provided for bit-rock interaction. Firstly, by using the Drucker-Prager rock criterion, actual bit and rock parameters, we develop the finite element bit-rock interaction experiments, and we obtain the data of rotating speed, rate-ofpenetration, weight-on-bit. Then, based on multiple nonlinear regression method, we identify the existing Young model, Jorden and Shirley model, Richard model, Ritto model parameters. Through the analysis and comparison of identification effects and characteristics of each model, we obtain the relationship among parameters of the bit-rock interaction.

关键词： Bit-rock interaction Weight on bit Finite element method Parameter identification

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An Improved Faster-RCNN Algorithm for Object Detection in Remote Sensing Images

An Improved Faster-RCNN Algorithm for Object Detection in Re...

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第三十九届中国控制会议

作者： Rui Liu Zhihua Yu Daili Mo Yunfei Cai School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Compared with conventional object detection, remote sensing images are taken from the air. The angle of view is not fixed and the object direction, scale which compared with conventional object detection algorithm are quite different. These factors lead to the object detection in remote sensing images difficult. To solve the above problems, this paper proposes an improved remote sensing object detection method based on Faster-RCNN algorithm. Using online difficult example mining technology,feature pyramid structure, Soft-NMS technology, and RoI-Align technology to enhance the capabilities of Faster-RCNN in small object detection task in remote sensing images. The algorithm in this paper was evaluated on the RSOD-Dataset, compared with the original Faster-RCNN algorithm, the proposed algorithm improves the detection accuracy and training convergence speed,which shows that these improvements are of great significance to the object detection algorithm of remote sensing images.

关键词： Remote Sensing Images Faster-RCNN Small Object Detection

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A Composite Cost-Sensitive Neural Network for Imbalanced Classification

A Composite Cost-Sensitive Neural Network for Imbalanced Cla...

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第三十九届中国控制会议

作者： Lei Chen Yuan Zhu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Imbalanced data with skewed class distributions and different misclassification costs is common in many real-world applications. Traditional classification approach does not work well for imbalanced data, because they assume equal costs for each class. To deal with this problem, cost-sensitive approaches assign different misclassification costs for different classes without disrupting the true original distributions of samples. However, due to lack of prior knowledge, the misclassification costs are usually unknown and hard to choose in practice. Whats more, even instances in the same class may have different misclassification costs. As an extension of class-dependent costs, this paper presents a composite cost-sensitive deep neural network(CCS-DNN) for imbalanced classification. A specifically-designed cost-sensitive matrix, which is composed of exampledependent costs and class-dependent costs, is embedded into the loss function to improve the classification performance. And the parameters of both the cost-sensitive matrix and the network are jointly optimized during training. The results of comparative experiments on some benchmark datasets indicate that the CCS-DNN performs better than other baseline methods.

关键词： Cost-sensitive Learning Composite Costs Imbalanced Classification Deep Learning

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Delay-Dependent Stability Analysis of Delayed Discrete-Time systems via State-Connecting-Based Zero-Value Equations

Delay-Dependent Stability Analysis of Delayed Discrete-Time ...

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第三十九届中国控制会议

作者： Ke-You Xie Wen-Hu Chen Li Jin Chuan-Ke Zhang Yong He 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 stability analysis of discrete time-delay system. Firstly, an improved augmented functional form is proposed and the positive definite condition of functional is derived. Then, the forward difference of functional is estimated by applying summation inequalities and a state-connecting-based zero-value equation. As a result, an improved stability criterion is established. Finally, a numerical example is given to show the efficiency and merit of the proposed method.

关键词： Discrete-time systems stability analysis time-varying delay zero-value equation

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Stability Analysis of Milling Process With Time-Varying Delays Via Lyapunov-Krasovskii Functional

Stability Analysis of Milling Process With Time-Varying Dela...

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第三十九届中国控制会议

作者： Jiang He Chen Yan Hong-Zhang Wang Dan-Yun Li School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

The regenerative chatter during milling seriously affects the stability of the *** paper proposes a method based on Lyapunov-Krasovski functional analysis for the stability of the milling ***,the mechanism analysis of the milling process is performed,then the state-space equation of the time-varying delay system caused by the regeneration effect is ***,based on the model of a time-delay system,a stability criterion is developed by constructing an augmented LyapunovKrasovski functional(LKF) and using auxiliary function inequality with reciprocally convex combination ***,the validity of the method is verified through an example,and the milling stability domain lobe diagram with a parameter combination of spindle speed-cutting depth is obtained which provides operational guidelines to guarantee a stable vibration-free process.

关键词： Milling process time-varying delay Lyapunov reciprocally combination technology stability

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Improved-YOLOv3 network for object detection in simulated Space Solar Power systems images

Improved-YOLOv3 network for object detection in simulated Sp...

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第三十九届中国控制会议

作者： Guangjun Wang Nongwei Lei Huimin Liu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In this paper, the object detection technology based on deep learning is applied to the assembly process of space power station simulation, which can provide assistance for the attitude adjustment and navigation of the aircraft through the detection of some components. Firstly, the 3 D modeling and rendering of the space power station are carried out, on which the image dataset is collected and established. Then, based on the YOLOv3 network, we improve the structure of feature *** fusing the information of shallow and deep features, we can improve the detection ability of the network for different scale *** and quantitative experimental results show that the improved YOLOv3 network can accurately and effectively detect the key components of the Space solar power station.

关键词： Space Solar Power systems object detection YOLOv3 multiscale features

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Novel Synchronization Criteria of Chaotic Lur’e systems With Time-varying Delayed Feedback PD control

Novel Synchronization Criteria of Chaotic Lur’e Systems Wit...

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第三十九届中国控制会议

作者： Run-Zhe Tao Ying Zhang Lei-Chao Pang Xing-Chen Shangguan Dan-Yun Li 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 problem of asymptotical synchronization of chaotic Lur’e systems controlled via PD controller with time-varying delay. Firstly, a new Lyapunov-Krasovskii functional（LKF） with more information of time-varying delay is constructed. Then, by applying the Wirtinger-based integral inequality and the extended reciprocally convex combination lemma（RCCL）, a new synchronization criterion for time-varying delay is obtained, and a less conservatism corollary for the constant delay is established by weakening some terms of LKF. Finally, a numerical example is given to show the better performance of the proposed criteria.

关键词： Synchronization Chaotic Lur’e systems Time-varying delay PD feedback control

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Improved current-based droop control strategy for microgrids inverter

Improved current-based droop control strategy for microgrids...

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第三十九届中国控制会议

作者： Danyun Li Jiawei Li School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Inconsistent feeder impedances in microgrids easily lead to uneven reactive power output of the inverter. This paper proposes an improved current-based droop control strategy for this problem. The droop coefficient is adjusted by the inverter capacity ratio, and the reactive current measured at the point of common coupling（PCC） is used as a reference value for improved differential control to compensate the voltage and control its reactive power output. It is found that the improved droop control has good adaptive ability and stability. The simulation results also prove the correctness and feasibility of the proposed strategy.

关键词： microgrids inverter capacity ratio current-based droop control reactive power

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