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2020 IEEE Power and Energy Society General Meeting, PESGM 2020

作者： Wan, Feiya Li, Zhen Liu, Bin Li, Guanghui Dong, Xiaoliang Chen, Xi Yu, Samson S. Oo, Amanullah M. T. Shan, Zhenyu Liu, Xiangdong Beijing Institute of Technology School of Automation and Key Laboratory for Intelligent Control Decision on Complex Systems Beijing China China Electric Power Research Institute Beijing China State Grid Corporation of China and North China Branch of State Grid Corporation of China Beijing China GEIRI North America United States Deakin University School of Engineering 75 Pigdon Rd Waurn Ponds Victoria Australia North China University of Technology School of Electrical and Control Engineering Beijing China

ISBN: (纸本)9781728155081

With the booming installed capacity of permanent magnet synchronous generator (PMSG) for wind energy generation, the grid becomes weaker and the oscillation events are frequently observed in weak-grid-tied large-scale grid-connected PMSG wind farms. Although the impedance-based method is effective to analyze the stability of grid-connected systems, the mathematical relationship between external impedance characteristics and the internal controllers has not been quantitatively analyzed in depth, which is beneficial to the controller design. This paper studies the influence of phase-locked loop (PLL) on the impedance characteristics based on the analytical sequence impedance model of PMSG with typical topology and control structure. The shaping effect of PLL on the impedance characteristics is described so as to clearly describe the relationship between the external impedance characteristics of the wind turbines and the internal controller. Finally, the stability analysis of the grid-connected PMSG wind turbine system is provided in Matlab and simulation results are given to verify the oscillating mechanism caused by PLL. © 2020 IEEE.

关键词： Phase locked loops

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Multi-agent system Motion Planning under Temporal Logic Specifications and control Barrier Function

Multi-agent System Motion Planning under Temporal Logic Spec...

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第三十九届中国控制会议

作者： Xinyuan Huang Li Li Jie Chen IEEE IFAC Chinese Academy of Engineering Tongji University the State Key Laboratory of Intelligent Control and Decision of Complex Systems the Chinese Association of Automation the Chinese Artificial Intelligence Society College of Electronics and Information Engineering Tongji University Shanghai Reserach Institute for Intelligent Autonomous Systems

In this paper, we provide a novel scheme to solve the motion planning problem of multi-agent systems under highlevel task specifications. First, linear temporal logic is applied to express the global task specification. Then an efficient and decentralization algorithm is proposed to decompose it into local tasks. Finally, we use control barrier function to synthesize the local controller for each agent under the LTL motion plan safety constraint. Simulation results prove the effectiveness and efficiency of our proposed method.

关键词： temporal logic multi-agent system formal methods control barrier function

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Cooperative robust output regulation for second-order nonlinear multi-agent systems with an unknown exosystem

Cooperative robust output regulation for second-order nonlin...

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IEEE Annual Conference on decision and control

作者： Yi Dong Jie Chen Jie Huang Department of Automation Chinese University of Hong Kong Shatin N.T. Hong Kong State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Department of Mechanical and Automation Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong

The cooperative robust output regulation problem for a class of second-order nonlinear multi-agent systems with an exactly known exosystem has been studied recently. This paper further studies the same problem for a class of second-order nonlinear multi-agent systems subject to an unknown exosystem. We first show that the problem can be converted into the adaptive stabilization problem for a modified augmented system composed of the given multi-agent system and the distributed internal model. Due to the uncertain parameter in the exosystem, the augmented system is a nonlinear multi-input system with both dynamic and static uncertainties. By combining the adaptive control technique and the robust control technique, we solve our problem by a distributed adaptive robust state feedback controller.

关键词： Multi-agent systems Mathematical model Robustness Robust control Automation Electronic mail Nickel

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Cooperative Lane Change Motion Planning of Connected and Automated Vehicles: A Stepwise Computational Framework

Cooperative Lane Change Motion Planning of Connected and Aut...

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2018 IEEE intelligent Vehicles Symposium, IV 2018

作者： Zhang, Youmin Li, Bai Zhang, Yue Jia, Ning Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'An University of Technology Xi'an710048 China Division of Systems Engineering Center for Information and Systems Engineering Boston University Boston United States Department of Mechanical Industrial and Aerospace Engineering Concordia Institute of Aerospace Design and Innovation Concordia University Montreal Canada Institute of Systems Engineering Tianjin University Tianjin China

ISBN: (纸本)9781538644522

This paper focuses on the scheme of cooperative lane change motion planning of multiple connected and automated vehicles, so as to minimize the time for lane change while penalizing large steering angles subject to hard collision avoidance constraints. Nominally this scheme should be formulated in a centralized way with the constraints of all the vehicles considered simultaneously. In order to facilitate the numerical solving process of this centralized optimization problem, we propose a stepwise computation framework. Starting with a sub-problem with all of the collision avoidance constraints removed, a sequence of sub-problems are defined by adding back the removed collision avoidance constraints gradually until the original problem takes shape in the end. The optimum of one sub-problem is always used as the initial guess when solving the next sub-problem. This iterative process continues until the optimum of the original problem is obtained. In this way, the difficulties in the original centralized problem are divided into multiple parts, and every progress made to address the partial difficulties is 'solidified' by the initial guess. © 2018 IEEE.

关键词： Collision avoidance

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Anti-occlusion Object Tracking Algorithm using Response Template Fusion and Combined Features

Anti-occlusion Object Tracking Algorithm using Response Temp...

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Chinese control and decision Conference, CCDC

作者： Jing Wang Yuan Wei Yisong Liu Weichao Huang Ming Hu Faculty of Printing Packaging Engineerring And Digital Media Technology Xi’an University of Technology Xi’an China Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China

The kernel correlation filtering algorithm cannot judge the occlusion by itself when the object is occluded by foreign objects, and the tracking performance is greatly affected. Aiming at this problem, this paper proposes an anti-occlusion object tracking algorithm that fuses response templates and combined features. The peak sidelobe ratio (PSR) is used to determine whether the object is occluded. When the object is partially occluded, a combined feature representation object model is introduced to enhance robustness, and a multi-response template with anti-occlusion performance is constructed to improve the performance of the object when it is occluded by foreign objects. The problem of reducing the available information, thereby improving algorithm performance. Experiments in the OTB-100 data set can prove that the success rate and accuracy of the algorithm have competitive results compared with the comparison algorithms.

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Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surface Vehicle in Marine Environment

Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surf...

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Information Technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Xianzhi Qi Wenxing Fu Pei An Bingli Wu Jie Ma National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781728152240

ISBN: (纸本)9781728152257

Point cloud preprocessing is still a challenging task in the marine environment, for it is difficult to filter out non-obstacle points while avoiding damage to the obstacle completeness. In this paper, we propose a novel data preprocessing method on 3D LiDAR data for the unmanned surface vehicle in the marine environment. It consists of two tasks: outlier removal and wake filtering. As the spatial resolution of LiDAR changes with distance, we exploit distance normalization on statistical outlier filter for robust outlier removal. Considering the gradient difference between wave wake and obstacle surface near the water, we define and calculate the vertical state of point cloud on the range image to obtain the pre-filtering point set, and then use the RANSAC method to filter out the wake points. Experiments on real data has demonstrated the effectiveness of the proposed algorithm both in terms of feasibility and accuracy.

关键词： Three-dimensional displays Laser radar Filtering Filtering algorithms Spatial resolution Task analysis Measurement by laser beam

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Deep learning for robust outdoor vehicle visual tracking

Deep learning for robust outdoor vehicle visual tracking

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Ji-ng Xin Xing Du Jian Zhang Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an P.R.China Faculty of Engineering and Information Technology University of Technology (UTS) Sydney Australia

ISBN: (纸本)9781509060689

Robust visual tracking for outdoor vehicle is still a challenging problem due to large appearance variations caused by illumination variation, occlusion and scale variation, etc. In this paper, a deep-learning-based approach for robust outdoor vehicle tracking is proposed. Firstly, a stacked denoising auto-encoder is pre-trained to learn the feature representation way of images. Then, a k-sparse constraint is added to the stacked denoising auto-encoder and the encoder of k-sparse stacked denoising auto-encoder (kSSDAE) is connected with a classification layer to construct a classification neural network. After fine-tuning, the classification neural network is applied to online tracking under particle filter framework. Extensive tracking experiments are conducted on a challenging single object online tracking evaluation platform benchmark to verify the effectiveness of our tracker. Experiments show that our tracker outperforms most state-of-the-art trackers.

关键词： Robustness Object tracking Machine learning Feature extraction Biological neural networks Visualization

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Load Curve Modeling Based on Behavior Analysis of Distributed Power Customers

Load Curve Modeling Based on Behavior Analysis of Distribute...

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2019 4th Asia Conference on Power and Electrical Engineering (ACPEE 2019)

作者： Xinyang HAN Yu ZHANG Yuqiao JIAO Yue ZHANG Yanjing QU Min DING State Grid Energy Research Institute School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System State Grid Shanghai Municipal Electric Power Company

As renewable power generation directly affects the customers' traditional electricity behavior and then offsets the power load,this paper proposes a load curve modeling method for renewable power customers based on the behavior ***,customers' active behavior is represented by the quantity of active customer *** on the analysis of customer behaviors,a modeling method for the quantity of active customer households is proposed based on Markov Chain Monte Carlo ***,with the inputs as the quantity of active customer households and time of photovoltaic power generation,an inference model based on fuzzy logic is proposed to get the quantity of customer household starting electrical *** combing the average usage time of electrical appliances,load characteristics are analyzed based on usage state of electrical appliance of distributed power ***,the simulation results verify the effectiveness of the proposed method.

关键词： Carlo Monte Markov Load Curve Modeling Based on Behavior Analysis of Distributed Power Customers

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Research and Application of Composite Stochastic Resonance In Enhancement Detection

SSRN

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SSRN 2023年

作者： Gao, Rui Jiao, Shangbin Xue, Qiongjie Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi’an710048 China School of Electronic and Electrical Engineering Baoji University of Arts and Sciences Baoji721016 China

Aiming at the problem that the intermediate potential part of the traditional tristable method cannot be adjusted independently, a new composite stochastic resonance (NCSR) model is proposed by combining the Woods Saxon (WS) model and the improved piecewise bistable model. All the parameters in the new model have no coupling characteristics. Moreover, the model retains the characteristics of the independent parameters of WS model and the improved piecewise model has no output saturation. Understable noise environment, the new model is used to detect periodic signal and aperiodic signal, the detection results indicate that the new model has better noise utilization and better detection effect. Finally, through image denoising experiments, the output signal-to-noise ratio (SNR) and correlation number of NCSR method is higher than that of other commonly used linear denoising methods and classical SR methods under the same conditions, the effectiveness of the new model is verified. © 2023, The Authors. All rights reserved.

关键词： Image denoising

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A high-precision vision-based mobile robot slope detection method in unknown environment

A high-precision vision-based mobile robot slope detection m...

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Chinese Automation Congress

作者： Kenan Du Jing Xin Yaqian Shi Ding Liu Youmin Zhang CETC 20 Shaanxi key Laboratory of Integrated and Intelligent Navigation Xi'an P.R. China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi‘an University of Technology Xi'an P.R. China Department of Mechanical and Industrial Engineering Concordia University Quebec Canada

Aiming at satisfying the demand of slope perception accuracy for mobile robots in the unknown environment, a high-precision vision-based mobile robot slope detection method in unknown environment is proposed in this paper. Firstly, the RGB images of slopesin the unknown environment arecaptured by the Kinect sensor installed on the mobile robot, and edge sharpening is performed on the images of slopes. Then, the coordinates of the slope edge pixel in the image coordinate system are transformed into the camera coordinate system to obtain the real length of the slope. Finally, the single image depth estimation method based on convolution neural network (CNN) is used to estimate the depth of theslope image toobtain the projection length of the slope only using a single slope image, and the slope angle is obtained by the inverse cosine function. The experimental results show that the slope detection method proposed in this paper has higher detection accuracy and can satisfy the demand of slope sensing accuracy of mobile robot in unknown environment.

关键词： Slope detection Coordinate transformation Single image Depth estimation Convolutional neural network (CNN)

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