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第三十八届中国控制会议

作者： Wentao Yu Hao Fang Daiying Tian School of Automation Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

In this paper, we consider the plan recognition problem in the real-time strategy game. A probabilistic plan recognition algorithm is proposed to predict the future goals and identify the temporal logic tasks of the non-cooperative agent based on the observations. In order to model the temporal logic tasks, the plan library is composed of the Finite Transition System and Nondeterministic B ¨uchi automation. Specially, we provide a unified framework to combine the plan recognition and the planning, and propose the probability calculation algorithm to calculate the posterior probability distribution of the goals and tasks. Finally, we verify the effectiveness of the proposed algorithm by the compared simulations.

关键词： Probabilistic Plan Recognition Linear Temporal Logic Büchi automation Goal Prediction

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Wearable Human Foot Mechanical Energy Harvesting Device Based on Moving-coil Generator

Wearable Human Foot Mechanical Energy Harvesting Device Base...

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第三十八届中国控制会议

作者： Ning Ding Fang Deng Yeyun Cai Peng Gui Xinyu Fan School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems

In order to solve the problem of energy supply for smart wearable devices, this paper proposes a wearable human foot mechanical energy harvesting device based on moving-coil generator, and designs a moving-coil type power generation shoes prototype. Firstly, the human foot horizontal movement is analyzed based on the human gait model. Combined with the characteristics of wearable devices, we determine that mechanical energy harvesting device installed in the heel is the most effective. Secondly, the moving-coil generator is designed and the prototype of moving-coil type power shoes is made. Finally,using the movement test platform of the laboratory, We complete the comfort test and optimize the structure, as well as analyze the basic performance of the device, which has good high-frequency characteristics.

关键词： Wearable energy harvesting Moving-coil generator Mechanical energy Human body

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A grasping CNN with image segmentation for mobile manipulating robot

A grasping CNN with image segmentation for mobile manipulati...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Yu, Yingying Cao, Zhiqiang Liang, Shuang Liu, Zhicheng Yu, Junzhi Chen, Xuechao Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Intelligent Robotics Institute BIT Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing100081 China

ISBN: (纸本)9781728163215

This paper presents a grasping convolutional neural network with image segmentation for mobile manipulating robot. The proposed method is cascaded by a feature pyramid network FPN and a grasping network DrGNet. The FPN network combined with point cloud clustering is used to obtain the mask of the target object. Then, the grayscale map and the depth map corresponding to the target object are combined and sent to the DrGNet network for providing multi-scale images. On this basis, depthwise separable convolution is used for encoding. The results of encoders are refined according to the light-weight RefineNet as well as sSE, which can achieve a better grasp detection. The proposed method is verified by the experiments on mobile manipulating robot. © 2019 IEEE.

关键词： Image segmentation

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Impedance Modeling of PMSG Wind Farms from the Machine Side DC-Port with Outer Power Loop

Impedance Modeling of PMSG Wind Farms from the Machine Side ...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Jiajun Wang Xiaozhong Liao Bin Liu Xi Chen Xiangdong Liu Xiaoqin Lian Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing 100081 China GEIRI North America CA 95134 USA Beijing Technology and Business University Beijing 100048 China

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

Due to the advantages of large unit capacity, high efficiency and high reliability, direct-drive permanent magnet synchronous generators (PMSGs) wind turbines (WTs) have been widely used in the offshore wind power generation. The power loop controller aims to maintain the DC-Bus voltage of each PMSG-WT is equal to the others, guaranteeing that multiple WTs can be connected in DC serial parallel collection. In this paper, the DC-Port sequence impedance model of the PMSG-WT is established based on the harmonic linearization method, which takes the outer power loop into consideration. The impedance model is further verified by point-by-point scanning in MATLAB/Simulink. The proposed DC-Port impedance model of the PMSG-WT facilitates the establishment of offshore direct-drive wind farms, and is of great significance for analyzing and improving the system stability.

关键词： Impedance Mathematical model Harmonic analysis Wind farms Generators Power system stability Topology

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Dissipativity Analysis for Markovian Jump Neural Networks with Time-Varying Delay via An Extended Relaxed Integral Inequality 37

Dissipativity Analysis for Markovian Jump Neural Networks wi...

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37th Chinese control Conference, CCC 2018

作者： Wen-Juan, Lin Yong, He Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences School of Automation Wuhan430074 China

ISBN: (纸本)9789881563941

This paper investigates the problem of the strictly (\mathcal{Q}, \mathcal{S}, \mathcal{R})-\gamma -dissipativity analysis for Markovian jump neural networks with a time-varying delay. By employing an appropriate Lyapunov-Krasovskii functional and using the extended relaxed integral inequality to estimate its derivative, a delay-dependent and mode-dependent condition that guarantee the considered Markovian jump neural networks strictly (\mathcal{Q}, \mathcal{S}, \mathcal{R})-\gamma -dissipative is derived. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method. © 2018 Technical Committee on control Theory, Chinese Association of automation.

关键词： Lyapunov functions

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Learning Hidden Markov Models for Linear Gaussian systems with Applications to Event-based State Estimation

arXiv

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arXiv 2020年

作者： Zheng, Kaikai Shi, Dawei Shi, Ling State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong

This work attempts to approximate a linear Gaussian system with a finite-state hidden Markov model (HMM), which is found useful in solving sophisticated event-based state estimation problems. An indirect modeling approach is developed, wherein a state space model (SSM) is firstly identified for a Gaussian system and the SSM is then used as an emulator for learning an HMM. In the proposed method, the training data for the HMM are obtained from the data generated by the SSM through building a quantization mapping. Parameter learning algorithms are designed to learn the parameters of the HMM, through exploiting the periodical structural characteristics of the HMM. The convergence and asymptotic properties of the proposed algorithms are analyzed. The HMM learned using the proposed algorithms is applied to event-triggered state estimation, and numerical results on model learning and state estimation demonstrate the validity of the proposed algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Hidden Markov models

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Convex Relaxation with Log-Determinant Divergence-L1 Regularization for 3D Shape Reconstruction

Convex Relaxation with Log-Determinant Divergence-L1 Regular...

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第三十八届中国控制会议

作者： Wei Cao Luefeng Chen Min Wu Witold Pedrycz School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical and Computer Engineering University of Alberta

Investigated is the problem of estimating the 3 D shape of an object defined by a set of 3 D landmarks with their 2 D correspondences in a single image. To solve this problem, we use a dictionary of the basic shape with LDD-L1 regularization,which is the construction of the shape space model. Based on the proposed convex optimization method, 3 D human pose reconstruction by shape space model and 3 D variable shape model was carried out on the mocap database. To improve accuracy and reduce the number of iterations, we use PSO algorithm to optimize initial value of the key parameter. The experimental results show that the improved algorithm exhibits less iterations but higher accuracy, which can be much helpful in practical applications.

关键词： LDD-L1 regularization 3D reconstruction PSO

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Visual enhancement by spectral optimization of light sources 8

Visual enhancement by spectral optimization of light sources

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8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Applications, ISCIIA and ITCA 2018

作者： Jin, Xing Cheng, Xianghui Yang, Xiang Zhang, Jinjin School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

The visualization of an object image is directly affected by the spectral power distribution of the illuminated light source. In addition, the quality and the clarity of an object image can be evaluated by the color entropy value. Therefore, in order to obtain higher color entropy value of the target object image, a visual enhancement method is proposed by optimizing the spectral of the illumination. The optimal light source spectrum of the target image is obtained by the maximum color entropy, and the spectral reflectance of the object is obtained by the reconstruction method of the RBF neural network. The images under the optimal illumination source were compared with those of other commercial white light sources (6774K, 5000K, 2700K, 3000K,). The result shows that the optimized light source has a better visual effect and the lines in the image are more apparent. © ISCIIA and ITCA 2018 - 8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Application.

关键词： Light sources

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Attenuation of PMSM Torque-Ripple Based on Combination of Equivalent-Input-Disturbance Approach and Sliding-Mode control

Attenuation of PMSM Torque-Ripple Based on Combination of Eq...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Ruoyu Jiang Jinhua She Zhentao Liu Danyun Li Wangyong He Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Engineering Tokyo University of Technology Tokyo Japan

Torque-ripples in a permanent magnet synchronous motor (PMSM) deteriorate control precision. This paper presents a method of attenuating such a kind of a torque-ripple based on the combination of the equivalent-input-disturbance (EID) and the sliding-mode control (SMC). While a low gain of an SMC system avoids chattering phenomenon, the robustness of the system is not satisfied. The EID estimator is incorporated in the system to solve this problem. The effectiveness of the combination of the EID approach and the SMC has been verified by simulations. A comparison with the conventional SMC method demonstrates the priority of the presented method.

关键词： Torque Sliding mode control Forging Harmonic analysis Synchronous motors Stators Attenuation

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Feature Aggregation Attention Network for Single Image Dehazing

Feature Aggregation Attention Network for Single Image Dehaz...

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IEEE International Conference on Image Processing

作者： Lan Yan Wenbo Zheng Chao Gou Fei-Yue Wang The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Software Engineering Xi’an Jiaotong University Xi’an China School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou China

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

Due to its ill-posed nature, single image dehazing is a challenging problem. In this paper, we propose an end-to-end feature aggregation attention network (FAAN) for single image dehazing. It incorporates the idea of attention mechanism and residual learning and can adaptively aggregate different level features. In particular, in the proposed FANN, we design a novel block structure consisting of feature attention module, smoothed dilated convolution and local residual learning. The local residual learning allows the less useful information to be bypassed through multiple skip connections. The feature attention module is designed to assign more weight to important features. The smoothed dilated convolution is adopted to enlarge the receptive field without the negative influence of gridding artifacts. The experiments on the RESIDE dataset show that the proposed approach acquires state-of-the-art performance in both qualitative and quantitative measures.

关键词： Convolution Atmospheric modeling Kernel Image color analysis Task analysis Training

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