检索结果-内蒙古大学图书馆

SSRN 2022年

作者： Zhang, Zhixia Wen, Jie Wang, Hui Cai, Xingjuan Cui, Zhihua Zhang, Wensheng School of Computer Science and Technology Taiyuan University of Science and Technology China School of Information Engineering Nanchang Institute of Technology Nanchang330099 China State Key Laboratory of Intelligent Control and Management of Complex System Institute of Automation Chinese Academy of Sciences China State Key Lab. for Novel Software Technology Nanjing University China

In many-objective optimization problems (MaOPs), it is a difficult task for evolutionary algorithms to balance convergence and diversity while rapidly converging to the Pareto front. As the number of objectives increases, the difficulty of evolutionary algorithms increases with individual selection pressure. To address above problems, we propose a many-objective evolution algorithm assisted by an ideal hyperplane (MaOEA-IH). Firstly, the ideal hyperplane as a reference surface to guide the individual to search the Pareto front, which is established from the extremum of each dimension of the objective space. Secondly, a parallel p -norm mating selection strategy is proposed to improve convergence. In addition, two factors are considered in this strategy: 1) different p -norm are used to measure different spatial scales;2) individual selection uncertainty is defined by incorporating a probabilistic perturbation mechanism. Thirdly, the improved shift-based density estimation strategy is used as the evaluation criterion for environmental selection to improve the convergence and diversity of solution sets and enhance selection pressure. To verify the effectiveness of the proposed algorithm, MAOEA-IH is compared with seven excellent algorithms in three benchmark sets (DTLZ, WFG and MaF). The results show that the proposed MAOEA-IH is highly competitive in solving MaOPs. © 2022, The Authors. All rights reserved.

关键词： Geometry

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Self-Tuning Attitude control Design of Hypersonic Aircraft with Multi-Constraints Based on Soft-Constrained PI2 with Action Smooth

Self-Tuning Attitude Control Design of Hypersonic Aircraft w...

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Chinese Automation Congress (CAC)

作者： Tianyi Li Jiajun Fan Xian Guo Mingrui Hao Mingwei Sun College of Artificial Intelligence Nankai University Tianjin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Bejing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Nonlinear control has led to several great achievements for attitude control in virtual simulation environments, where the system model can be simplified to meet the application condition of those traditional nonlinear control algorithms. However, only a few of those algorithms can be applied to a practical Hypersonic Aircraft system, which suffers from uncertainties, multi-constraints, and various noises. To solve those problems effectively, in this paper, a novel reinforcement learning framework based on PI2 is proposed, wherein three kernel techniques are introduced. Firstly, a generalized path- integral-control approach is proposed to obtain the numerical solution of a stochastic dynamic model, wherein the calculation of the gradient and matrix inversion is avoided to ensure fast and reliable training convergence. Secondly, an action smooth method is used to strengthen the ability of the controller to resist noise. Thirdly, a novel RL algorithm combined with soft constrained techniques is illustrated to address the constrained nonlinear control problem. Several experiments are carried out and analyzed to demonstrate the outstanding performance of the CS-PI2.

关键词： Training Uncertainty Attitude control Atmospheric modeling Stochastic processes Resists Aircraft

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Finite Time Cooperative Guidance Law for Multiple UAVs with Intermittent Communication Topologies

Finite Time Cooperative Guidance Law for Multiple UAVs with ...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Lyu, Teng Xu, Cheng Li, Hongchun Hu, Song Zhang, Daochi System Control and Intelligent Agent Cooperation Laboratory Science and Technology on Complex Beijing China Beijing Electro-mechanical Engineering Institute Beijing China

ISBN: (纸本)9781728137926

To solve the problem of multiple Unmanned Aerial Vehicles (UAVs) with intermittent communication topologies simultaneously attack a stationary target, a time cooperative guidance law is studied in this paper. First, a novel time cooperative guidance model for multiple UAVs is constructed based on UAVs-target relative motion equations. Then, a cooperative guidance law is designed based on consensus theory, which can ensure multiple UAVs' impact times realize finite time consensus under intermittent topologies. After UAVs' impact times become to be the same, traditional PN guidance law is applied in all UAVs to guarantee that the UAVs can attack the target precisely without influencing the consensus of impact times. Finally, the validity of the proposed method is shown by numerical simulations. © 2019 IEEE.

关键词： Topology

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Study on the Modeling Method of Sip Target for Uav-borne Bi-SAR

Study on the Modeling Method of Sip Target for Uav-borne Bi-...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Guijie Diao Jia Huitong Hong Ni Zhe Liu Ningbo Gon Liang Yang Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing hina Beijing Electro-mechanical Engineering Institute Beijing China

ISBN: (数字)9781728180250

ISBN: (纸本)9781728180267

To solve the simulation problem of uav-borne bi-static synthetic aperture radar (SAR) for sea surface targets, a scattering signatures modeling method of sea-surface target for bi-static imaging radar is proposed, based on the coupling scattering mechanism between the ship and sea surface. A bistatic scattering signature signal model for sea-surface target in conjunction with high frequency asymptotic techniques for electromagnetic (EM) scattering calculation, the multi-path EM scattering model, the time-evolving complex reflection coefficient model and the ship motion dynamics. The time varying scattering signatures for a typical ship on time evolving sea-surface are simulated and analyzed.

关键词： Sea surface Imaging Radar imaging Radar scattering Reflection coefficient Marine vehicles Synthetic aperture radar

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Multi-agent Cooperative Search based on Reinforcement Learning

Multi-agent Cooperative Search based on Reinforcement Learni...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Yinjiang Sun Rui Zhang Wenbao Liang Cheng Xu Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781728180250

ISBN: (纸本)9781728180267

Regional cooperative search is an important scenario for Unmanned Aerial Vehicle (UAV) fleet. It is difficult for the UAV fleet to adapt to the dynamic environment by using traditional search method, which needs pre-planning. In this paper, a reinforcement learning approach is employed to train the UAV agents to search without pre-determined strategies. By designing reward function, state and action spaces, agents can learn to make decisions all by themselves based on their own observations and cooperate with each other effectively. The proposed method is experimentally validated by numerical simulations, and the result show that the UAV fleet can complete task with a pretty high coverage and few repetitions at the same location.

关键词： Zirconium Radio frequency Hafnium Erbium

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Aircraft Autonomous Positioning Based on a Coarse to Fine Multi-modal Image Registration Scheme

Aircraft Autonomous Positioning Based on a Coarse to Fine Mu...

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Power Electronics, Computer Applications (ICPECA), IEEE International Conference on

作者： Fangde Sun Wenxing Fu Xiaohui Lu Jing Dong Songlai Han School of Aeronautics and Astronautics Central South University Changsha China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China People’s Liberation Army 91039th Unit Beijing China Aerospace Science and Engineering National University of Defense Technology Changsha China

ISBN: (数字)9781728190044

ISBN: (纸本)9781728190051

In this paper, an autonomous positioning method based on coarse-to-fine multi-modal image matching is proposed for UAV navigation in GPS denied environment. Coarse image matching refers to roughly determining the approximate position of the real-time image in the reference image. Fine image matching refers to iterative matching around the position obtained by coarse image matching to achieve more accurate matching results. Besides, RANSAC is adopted to eliminate the outliers of image matching. After getting the result of image matching, we use PNP to estimate the position of the aircraft. The proposed position method has the advantages of high accuracy and reliability. The experimental results show that the average error of the position of the proposed method is 59%.

关键词： Image registration Image matching Aerospace electronics Real-time systems Power electronics Reliability Aircraft

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Monocular Visual-Inertial Odometry Based on Point and Line Features

Monocular Visual-Inertial Odometry Based on Point and Line F...

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International Conference on Computer and Communications (ICCC)

作者： Gongyan Chen Hai Zhang Wenxing Fu Yiqun Qiao School of Automation Science and Electrical Engineering Beihang University Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

In order to solve the problem that the point feature tracking is not robust enough to reduce the accuracy of the system in a low-texture environment, this paper proposes a visual inertial odometry system based on point-line features (PL-VINS). Firstly, the system improves the extraction and matching algorithm of line features to increase the speed and accuracy of the algorithm; then the line features are added to the front-end tracking and back-end optimization. Finally, the EuRoc public data set is used as the experimental object to prove the effectiveness of the algorithm.

关键词： Visualization Conferences Feature extraction Cameras Real-time systems Optimization Optical flow

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Temperature prediction of generator carbon brush based on LSTM neural network

Temperature prediction of generator carbon brush based on LS...

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2021 China Automation Congress, CAC 2021

作者： Zhang, Qing Jiao, Tingyang Ma, Yinxing Zhang, Youmin Wu, Xiaohui Wu, Pengyue Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China The Faculty of Computing Science The University of Alberta EdmontonABT6G 2R3 Canada Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi 'an University of Technology Xi'an710048 China Department of Mechanical Industrial and Aerospace Engineering Concordia University MontrealQCH3G 1M8 Canada Huaneng Weihai Power Generation Co. Ltd Weihai264200 China Xi 'an Thermal Power Research Institute Co. Ltd Xi'an710048 China

ISBN: (纸本)9781665426473

In order to improve the prediction accuracy of the carbon brush temperature trend of the generator, analyzing the operating state of the generator more accurately, and reduce other accidents like the unplanned outage caused by carbon brush failure of the generator in the power plant. A multi-step temperature prediction model based on the LSTM (Long Short-Term Memory) neural network is proposed. The data comes from real operating carbon brush temperature of Weihai Power Plant in ten days. Then the temperature prediction model is established to achieve an accurate prediction of the carbon brush temperature in the future day. The prediction error is stable within 0.4 °C. By comparing the predicted results of the BP model and Elman model, the error between the predicted results of each model and the actual temperature data is analyzed. By comparing the indicators and analyzing the actual curves, the results show that LSTM neural network has higher accuracy in predicting the temperature of generator carbon brush. This method is of reference significance for the accurate analysis of the operation state of the generator and the load analysis of the excitation system. © 2021 IEEE

关键词： Long short-term memory

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Application of Neutrosophic Multiple Criteria Decision Making in Unmanned system

Application of Neutrosophic Multiple Criteria Decision Makin...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Zhong, Yu Zhao, Jiajia Northwestern Polytechnical University School of Electronics and Information Xi'an China Control and Intelligent Agent Cooperation Laboratory Science and Technology on Complex System Bejing China

ISBN: (纸本)9781728137926

The multiple criteria decision making (MCDM) is universal and applicable for plenty of unmanned systems which are widely concerned in civil and military fields due to their adaptability and safety. The contributing factors of decision making in unmanned systems are complicated due to the inhomogeneity and nondeterminacy of environment and the relative importance of criteria. Consequently, these critical factors fail to be considered felicitously in many traditional methods. In this paper, a neutrosophic MCDM approach is proposed to mitigate this matter. The neutrosophic set generated from collected information of multiple sources would be fused by the aggregation operator to obtain the decision matrix, then the weights of criteria would be obtained via the proposed method based on the decision matrix, and the decision results could be determined by the aggregation operator and defuzzification method of aggregated neutrosophic set. The application of neutrosophic set can handle numerous uncertain matters in unmanned systems. Finally, an example was provided to illustrate the reasonableness and stability of the proposed approach. © 2019 IEEE.

关键词： Decision making

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Failure Mode and Effects Analysis of UAV Power system Based on Generalized Dempster-Shafer Structures

Failure Mode and Effects Analysis of UAV Power System Based ...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Zhang, Zhuo Hao, Mingrui Northwestern Polytechnical University School of Electronics and Information Xian China Intelligent Agent Cooperation Laboratory Science and Technology on Complex System Control Beijing China

ISBN: (纸本)9781728137926

The unmanned aerial vehicle(UAV) power system consists of components that provide flight power for the UAV, which mainly includes three parts: motor, electronic speed controller(ESC), and battery. Since the UAV always operates in the open air, which requires high stability of the power system, the failure mode and effects analysis(FMEA) is particularly significant and it has been widely used to examine potential failures in systems or components. However, the traditional FMEA method has many unreasonable points. In order to better deal with the uncertainty and improve the stability of the UAV power system, we propose a FMEA method which is based on the generalized Dempster-Shafer structures, the failure modes are comprehensively analyzed and the risks are ranked by combining the characteristic information of risk factors with the generalized evidence theory. The new method can not only deal with the uncertainty of risk assessment, but also further improve the reliability of effects analysis. In addition, the FMEA experiment of the UAV power system is carried out in this paper. The experimental results show that the method is effective for practical applications. © 2019 IEEE.

关键词： Fuzzy set theory

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