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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Aleksey Cherednichenko Xinqi Huang Yanyan Wang Yingsong Li Harbin Engineering University Harbin China Intelligent Agent Cooperation Laboratory Science and Technology on Complex System Control Beijing China

ISBN: (数字)9781728198057

ISBN: (纸本)9781728198064

This paper presented a p-norm constraint Lorentzian adaptive algorithm to estimate the sparse multi-path channel inα-stable noise environment. We derived the proposed algorithm based on the Lagrange multiplier method and we also evaluated the performance of the developed adaptive algorithm via estimating a sparse multi-path channel. The gotten results on the basis of computer simulations proved that the developed Lorentzian adaptive algorithm is superior to the popular method in the comparisons.

关键词： Computer simulation Adaptive algorithms Channel estimation Adaptive arrays

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Failure mode and effects analysis based on intuitionistic fuzzy sets and evidential correlation coefficient

Failure mode and effects analysis based on intuitionistic fu...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Zhang, Hang Huang, Chan Lu, Mingsheng Dong, Xiaofei School of Software Northwestern Polytechnical University Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Xi'an Beijing China Northwestern Polytechnical University School of Electronics and Information Xi'an China Agent Cooperation Laboratory Science and Technology on Complex System Control and Intelligent Beijing China

ISBN: (纸本)9781728137926

As an effective implement, failure mode and effects analysis (FMEA) is widely applied in the security of system for practical application. Nowadays, many methods determine the order of fault mode by a crisp risk priority number (RPN). However, these methods exist several shortcomings, for instance, the correlation of the assessments given by team members are not fully considered. In this article, a new method for risk assessment and sequence for failure modes in FMEA is proposed on account of the D-S evidence theory and the evidential correlation coefficient. By using the proposed approach, the weights of team members for each failure mode and risk factor is obtained. Then the weighted assessments are used to perform the aggregation process by Intuitionistic fuzzy weighted averaging (IFWA) operator. A classic application regarding risk assessment is used to verify the effectiveness of the proposed method. © 2019 IEEE.

关键词： Failure modes

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Design of Reusable Effectiveness Evaluation Model Framework

Design of Reusable Effectiveness Evaluation Model Framework

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Chinese control and Decision Conference, CCDC

作者： Shuang Zhang Wei Li Shenglin Lin Ming Yang Jiahui Tong Control and Simulation Center Harbin Institute of Technology Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

In order to make the effectiveness evaluation models of the weapon equipment system universal and flexible, and adapt to different evaluation objects, a framework of effectiveness evaluation model is designed. Next a series of modular and reusable effectiveness evaluation models are proposed under the framework. Each type of evaluation model is built based on IDEF0, and the corresponding input and output of each model are designed. To further improve reusability, several models are mathematically described and model interface is designed based on XML.

关键词： Indexes Data models Data mining Analytical models Mathematical model Optimization Adaptation models

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Motion Parallax Estimation for Ultra Low Altitude Obstacle Avoidance

Motion Parallax Estimation for Ultra Low Altitude Obstacle A...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Wang, Changqing Liang, Xinkai Zhang, Shan Shen, Chao Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728137926

By making full use of the curvature of the earth and ground clutter, the ultra-low altitude flight technique can significantly increase the difficulty of detecting and intercepting unmanned aerial vehicles (UAVs), and improve their penetration probabilities. However, unpredicted static/dynamic obstacles seriously threaten the flight safety of the ultra-low altitude UAVs. Therefore, fine autonomous spatial perception capability is essential for ultra-low altitude UAVs with limited loads and computing resources to avoid obstacles. To solve the difficult problem of spatial perception for ultra-low altitude obstacle avoidance, a motion parallax estimation algorithm is proposed by combing the deep learning and the epipolar geometry in this paper. By utilizing the deep neural network, the end-to-end mapping relationship from sequence images to depth values of pixels is constructed for spatial perception. At the same time, to overcome the interference caused by the image consistency hypothesis, the loss function is constructed based on the 3D geometric information of the scene rather than the re-projection error between images. Finally, the proposed algorithm is evaluated on the KITTI dataset and infrared image dataset to verify its effectiveness and generalization. © 2019 IEEE.

关键词： Deep neural networks

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Spirometer and sEMG respiratory patterns for clinical decision support system

Spirometer and sEMG respiratory patterns for clinical decisi...

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IEEE Instrumentation and Measurement technology Conference

作者： Amit Krishan Kumar Mansour H. Assaf Voicu Z. Groza Emil M. Petriu Faculty of Electrical-Electronic Engineering Duy Tan University Da Nang Vietnam Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing China School of Information Technology Engineering Mathematics and Physics The University of the South Pacific Suva Republic of Fiji School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

To improve support system for subjects with respiratory ailments, this work analyses the respiratory patterns from spirometer and surface electromyography (sEMG). The patterns are integrated with risk and biochemical systems model to optimise the clinical decision support system (CDSS). The work considers terminal events for the spirometer and sEMG. The events and their associated patterns are correlated and projected on a hyperspace prior implementing it in decision support system. The proposed method shows that the different characteristics of breathing indicate some essential hidden information which when used as 4D scattered projection, optimises the decision making in CDSS. The analysis shows the effectiveness of bimodal respiratory patterns for different breathing capacities, which is promising for the modelled conditions.

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Observability Enhancement of the Target Tracking Model Based on Infrared Semi-strapdown Seeker

Observability Enhancement of the Target Tracking Model Based...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Siting, Peng Qian, Zhao Yichao, Ma Cheng, Xu Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728137926

As an important device for target interception, The seeker is used to search, recognize and track the target autonomously. Infrared semi-strapdown seekers are widely used in applications due to their low cost and small size. However, one non-negligible disadvantage of semi-strapdown infrared seekers is that the observability of target tracking model is poor, especially for the interception of high-speed maneuvering weapons. In this paper, the target tracking model ( i.e., the filtering estimation model) based on the infrared simi-strapdown seeker is established. The observability of the target tracking model is analyzed and the evaluation method of the observability is studied. Simulation results show that the observability of the filtering estimation model can be improved by increasing the relative motion between missile and target which results in faster changes of the line-of-sight (LOS) angle. According to the results on the observability analysis, the desired trajectory is obtained through the design of proper guidance law. Nonlinear filtering algorithm is also introduced for the trajectory design. Simulation experiments are conducted for the integrated filtering and guidance, and simulation results illustrate the effectiveness of the proposed observability enhancement method. © 2019 IEEE.

关键词： Observability

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Cross-cycle iterative unmanned aerial vehicle reentry guidance based on reinforcement learning

Cross-cycle iterative unmanned aerial vehicle reentry guidan...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Cheng, Yang Shui, Zunshi Xu, Cheng Feng, Tianyu Jiang, Yiyang Beijing Aerospace Technology Research Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728137926

The traditional predictive correction algorithm requires a large number of iterative calculations for the predicted trajectory, which greatly occupies a large amount of computing resources, so that the real-time solution of the guidance command can not be guaranteed, and the guidance accuracy will have a large impact. And the prediction correction guidance requires the algorithm to have the ability of selfadaptation and intelligent learning. Therefore, this paper proposes a cross-cycle iterative hypersonic UAV predictive correction guidance method based on reinforcement learning. The parametric control variable (CVP) method is used to construct the parametric model of the guidance command. The actor-critic-based reinforcement learning method is used to solve the guidance command in real time, and the guidance information is effectively transmitted in the adjacent guidance solution cycle. The guidance error converges to within the allowable accuracy range during the cross-cycle iteration. Monte Carlo simulation shows that the proposed method has good adaptability to initial conditions and flight parameter uncertainty, and can guarantee the real-time performance of the guidance command while achieving high-precision guidance. © 2019 IEEE.

关键词： Reinforcement learning

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Parameter adaptive terminal sliding mode control of flexible coupling air-breathing hypersonic vehicle

Parameter adaptive terminal sliding mode control of flexible...

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AIAA Scitech Forum, 2020

作者： Jin, Hengxian Chen, Haibing Lin, Wei Xu, Cheng School of Energy And Power Engineering Beihang University Beijing100191 China Airworthiness Technologies Research Center School of Transportation Science and Engineering Beihang University Beijing100191 China School of Transportation Science and Engineering Beihang University Beijing100191 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Flexible air-breathing hypersonic vehicles have very wide range of flight and show significant and complex aerodynamic, scramjet propulsion system, flight dynamic and elastic coupling characteristics, which usually are highly nonlinear. These result in huge uncertainties, parameter perturbation and internal disturbance, which can no longer be ignored, and therefore, extreme difficulties for flight control design. A unique parameter adaptive nonsingular terminal sliding mode method is proposed for longitudinal control law design of a flexible coupling air-breathing hypersonic vehicle. Other than conventional adaptive terminal sliding mode control, this method uses adaptive reaching law gain instead of additional adaptive compensation term to handle the uncertainty to improve robustness. The stability of the close loop system is proved via a Lyapunov way. The longitudinal tracking control law for velocity and angle of attack is designed based on a rigid dynamic model of a flexible air-breathing hypersonic vehicle. A strong coupling model of this vehicle, considering aerodynamic-scramjet engine-flight dynamic-elastic couplings, is established as the verification platform of control law designed. The remarkable differences of flight dynamics characteristics between this strong coupling model and the rigid body model can be seen, which mean the controller needs to endure very great uncertainty, unmodeled dynamics and other internal disturbance. Simulation based on the coupling model is carried on and results demonstrate that the control law designed has good performance and acceptable robustness. © 2020, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Hypersonic vehicles

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An initial alignment approach for improving the accuracy of azimuth setting

An initial alignment approach for improving the accuracy of ...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Guan, Xujun Wang, Xing Guo, Jianzhong Fu, Wenxing Meng, Lingbao Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China China Aerospace Science and Industry Corporation Beijing China

ISBN: (纸本)9781728137926

Considering the azimuth discrepancy between the main and sub-inertial navigation systems (INS) for a platform-carried unmanned aerial vehicles(UAV) in case of tilted launching at a large pitch angle, an initial alignment method for improving the accuracy of the azimuth setting is proposed. First, an algorithm for computing the azimuth discrepancy is derived. Then, a mathematical model for initial alignment is established based on azimuth setting. The simulation results show that correcting the azimuth discrepancy between the main and sub-INS can greatly improve the accuracy of azimuth setting, and therefore the initial alignment accuracy of the sub-INS. Meanwhile, the drift for the gyros in three directions can be effectively estimated. © 2019 IEEE.

关键词： Inertial navigation systems

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A Many-Objective Evolutionary Algorithm Assisted by Ideal Hyperplane

SSRN

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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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