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High Performance and Smart Computing (HPSC), IEEE International Conference on

作者： Huapin Geng Hongtao Ma Jiahui Tong Ning Wang Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-mechanical Engineering Institute Beijing China Beijing Xinghang Electro-mechanical Equipment Beijing China Beijing Electro-mechanical Engineering Institute Beijing China

ISBN: (数字)9798350389463

ISBN: (纸本)9798350389470

In order to scientifically and effectively evaluate the performance indexes of aircraft, the common Bayes multi-source data fusion method can comprehensively utilize a variety of information types under the condition that the decision risk is as small as possible, but there are risks such as insufficient data utilization and small sample data being “submerged” by large sample data in the fusion. This paper proposes a test data expansion method based on the combination of probability features and BP neural network model, and is verified by typical application to ensure that the sample size of multi-source data is comparable. Supplementary data not only retains the probability features of the original data, but also the sample generation has physical connotation.

关键词： Atmospheric modeling Computational modeling Neural networks Data integration Data models Performance analysis Bayes methods

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A Cooperative Route Planning Method for Multi-UAVs Based-on the Fusion of Artificial Potential Field and B-spline Interpolation

A Cooperative Route Planning Method for Multi-UAVs Based-on ...

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Chinese control Conference (CCC)

作者： Wenbin Bai Xiande Wu Yaen Xie Yu Wang Han Zhao Kefan Chen Yong Li Yong Hao College of Aerospace and Civil Engineering Harbin Engineering University Harbin China College of Automation Harbin Engineering University Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Qian Xuesen Laboratory of Space Technology Beijing China

This paper deals with the route planning problem for multi-UAVs formation. It provides a method of improved artificial potential field by introducing a longitudinal random factor and B-spline interpolation. The longitudinal random factor is used to solve the problem of falling into local minimum, when the B-spline interpolation is used to smooth the planned route. The simulated results show that the proposed method can solve the route planning problem of multi-UAVs.

关键词： Planning Force Space missions Splines (mathematics) Interpolation Heuristic algorithms Unmanned aerial vehicles

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Research on Depth Estimation Method of Single Aerial Image

Research on Depth Estimation Method of Single Aerial Image

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IEEE Information technology, Networking, Electronic and Automation control Conference

作者： Wang Gao Lin Pu Lei Li Fei Deng Lingzhi Bie Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Institute of Mechanical and Electrical Engineering Beijing China School of Geodesy and Geomatics Wuhan University Wuhan China Wuhan Tianjihang Information Technology Co. Ltd Wuhan China

Aiming at the problem that the current depth estimation of single image mostly uses the ground public data set, and there is less research on aerial images, this paper uses the collected visible and infrared aerial image data sets to study the depth estimation. We used FCRN and LapDRN to extract the depth estimation results of visible aerial image and infrared aerial image under global and single object respectively, and compared the results extracted from the two types of networks by qualitative and quantitative methods. The results show that the depth estimation accuracy of visible aerial image is higher than that of infrared image, but the increase rate of infrared image accuracy index is higher than the increase rate of image depth range. The image depth estimation results extracted by LapDRN method are superior to FCRN in accuracy, structure consistency and edge clarity, which indicates that LapDRN is more effective in the estimation of aerial image depth information.

关键词： Automation Image edge detection Estimation Data mining Indexes

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Incremental control system Design and Flight Tests of a Micro-Coaxial Rotor UAV

arXiv

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arXiv 2022年

作者： Liu, Zhenchang Zhang, Yufei Chen, Haixin Zhang, Zhiduo Science And Technology On Complex System Control And Intelligent Agent Cooperation Laboratory School Of Aerospace Engineering Beijing100074 China Tsinghua University School Of Aerospace Engineering Beijing100084 China Beijing Institute Of Technology School Of Aerospace Engineering Beijing100081 China

In this paper, the incremental nonlinear dynamic inversion (INDI) method is applied to the control system design of coaxial rotor UAVs. The aerodynamic uncertainty and anti-disturbance problems are solved in the control system design. The designed controller gives the UAV excellent flight performance and control robustness. An incremental gain method (IGM) is proposed for the delay problem of the state derivative. This method has the advantages of less calculation load and simple parameter adjustment, which provides excellent convenience for applying INDI controllers to coaxial rotor UAVs. The principle of IGM is demonstrated by the stability analysis method of the discrete system, and the parameter selection strategy of the IGM is analyzed in detail by simulation. The advantages of the controller design method are verified by comparative flight tests of nonlinear dynamic inversion (NDI) and INDI. The experimental results show that the average trajectory tracking error of INDI is only 58.3% of that of NDI under the same wind speed. When the angular acceleration delay is less than 0.06 s, IGM can easily keep the system stable. In addition, INDI has better robustness under obvious model errors and strong input disturbance. Copyright © 2022, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Adaptive sliding mode control of electromechanical actuator with improved parameter estimation

Adaptive sliding mode control of electromechanical actuator ...

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作者： Li, Hao Bai, Yongqiang Su, Zhong School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Ministry of Education Beijing 100081 China Key Laboratory of Modern Measurement and Control Technology Beijing Information Science and Technology University Ministry of Education Beijing 100101 China

ISBN: (纸本)9788995605646

An adaptive sliding mode control scheme for electromechanical actuator has been presented. The adaptive control strategy can estimate the uncertain parameters and adaptively compensate the modeled dynamical uncertainties, while the sliding mode control method overcomes the unmodelled dynamics. In the adaptive law an equivalent output injection of the sliding mode observer which contains the parameter estimation error is used, and estimates of parameters can approximate the true values without prediction-error that is typically used in compositive adaptive law. Due to the improved estimation of uncertain parameters, the sliding mode law can robustifies the design against model uncertainties with a small swithcing gain. Stability of the system with the proposed approach has been proved and it has also been shown that the system states can reach the sliding mode in finite time. Finally, the effectiveness of the proposed control scheme has been exhibited via simulation examples. © 2011 Asian control Association.

关键词： Parameter estimation

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An Algorithm for Cooperative Navigation using Neural Network to Identify Colored Noise Online

An Algorithm for Cooperative Navigation using Neural Network...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Danting Sheng Jin Cheng Fengyi Li Mingrui Hao Beijing Electro-mechanical Engineering Institute CASIC Beijing China HIWING Technology Academy of CASIC CASIC Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation CASIC Beijing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

In practical applications of cooperative navigation algorithms based on Kalman filtering, noise is often colored noise, which does not meet the requirement of Gaussian white noise for Kalman filtering. Therefore, an algorithm is proposed to identify and compensate for colored noise online using a BP neural network. Firstly, a cooperative navigation model based on Kalman filtering is established. Then, by studying the update process of Kalman filtering, the neural network is incorporated into the prediction calculation of the observations, following the online learning and updating of the Kalman filter. Mathematical simulations show that under conditions of colored noise, the results of the Kalman filter diverge. However, after correction by the BP neural network, the filtering converges, providing high reference value for improving the accuracy of cooperative navigation.

关键词： Accuracy Filtering Navigation Neural networks Collaboration White noise Mathematical models Kalman filters Colored noise Convergence

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Prediction of piRNA-mRNA interactions based on an interactive inference network

Prediction of piRNA-mRNA interactions based on an interactiv...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Liu, Yajun Li, Ru Li, Aimin Fei, Rong Guo, Xie Wu, Fang-Xiang Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China University of Saskatchewan Division of Biomedical Engineering Department of Computer Science Department of Mechanical Engineering Saskatoon Canada

ISBN: (纸本)9798350337488

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions. © 2023 IEEE.

关键词： interactive inference network noncoding RNA piRNA-mRNA interactions positive-unlabeled learning

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A non-uniform Gauss pseudospectral method based on curvature information for dynamic optimization problem

A non-uniform Gauss pseudospectral method based on curvature...

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第32届中国过程控制会议(CPCC2021)

作者： Lu Lv Qian Zhang Jianzhong Su Wenhai Wang Jianquan Yuan Zijian Tian Zhenghui Zhang Long Xiao Zeyin Zhang Xinggao Liu Zhejiang University NGICS Platform State Key Laboratory of Industrial Control TechnologyControl DepartmentZhejiang University Tianjin Jinhang Institute of Technical Physics Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Mathematics Department Zhejiang University

Dynamic optimization for hypersonic reentry vehicle(HRV) is a challenge for complex nonlinear constraints during a global strike *** to the strong nonlinearity of HRV,it is difficult to guarantee the precision of complex constraints on non-collocation points with traditional Gauss pseudospectral method(GPM).A novel approach which provides an optimal control strategy considering the above challenges is then ***,an adaptive mesh refinement strategy based on curvature information is presented to improve the accuracy of GPM.A collocation point redistribution method based on error analysis is then proposed to further improve the accuracy of the ***,a detection mechanism is proposed to correct the results on-line when the path constraint is not *** proposed approaches are finally applied to a classic HRV problem and compared with other literature work in *** research results validate the effectiveness of the proposed methods.

关键词： nonlinear optimal control Gauss pseudospectral method adaptive mesh refinement hypersonic reentry vehicle

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Cooperative trajectory planning algorithm of USV-UAV with hull dynamic constraints

arXiv

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arXiv 2022年

作者： Huang, Tao Chen, Zhe Gao, Wang Xue, Zhenfeng Liu, Yong Institute of Cyber-Systems and Control Zhejiang University No.38 Zheda Road Hangzhou310027 China Research Center for Intelligent Perception and Control Huzhou Institute of Zhejiang University No.819 Xisaishan Road Huzhou313098 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100191 China

Efficient trajectory generation in complex dynamic environments remains an open problem in the unmanned surface vehicle (USV). The perception of the USV is usually interfered with by the swing of the hull and the ambient weather, making it challenging to plan the optimal USV trajectories. In this paper, a cooperative trajectory planning algorithm for the coupled USV-UAV system is proposed to ensure that USV can execute a safe and smooth path in the process of autonomous advance in multi-obstacle maps. Specifically, the unmanned aerial vehicle (UAV) plays the role of a flight sensor, providing real-time global map and obstacle information with a lightweight semantic segmentation network and 3D projection transformation. And then, an initial obstacle avoidance trajectory is generated by a graph-based search method. Concerning the unique under-actuated kinematic characteristics of the USV, a numerical optimization method based on hull dynamic constraints is introduced to make the trajectory easier to be tracked for motion control. Finally, a motion control method based on NMPC with the lowest energy consumption constraint during execution is proposed. Experimental results verify the effectiveness of the whole system, and the generated trajectory is locally optimal for USV with considerable tracking accuracy. © 2022, CC BY.

关键词： Numerical methods

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Safe Tracker: A Robust Aerial system for Safe Tracking in Cluttered Environments

Safe Tracker: A Robust Aerial System for Safe Tracking in Cl...

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Chinese control Conference (CCC)

作者： Yulin Hui Bailing Tian Xuewei Zhang Hanchen Lu Hongming Shen School of Electrical and Information Engineering Tianjin University Tianjin P. R. China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing P. R. China

This paper proposes Safe Tracker, an autonomous aerial tracking framework based on vision sensor that can deal with challenging tracking missions and guarantee safety and visibility. Firstly, a RGB-D sensor based segmentation method is employed to locate the target in real-time. Then target motion is predicted for a short time horizon, based on which a heuristic path searching method is applied to generate an occlusion-free path. Finally, particular formulations to balance visibility and safety are designed, and an effective non-linear trajectory optimization method enables to generate an optimal tracking trajectory. Autonomous aerial tracking experiments using a vision sensor are conducted to demonstrate the effectiveness of the proposed Safe Tracker in a challenging cluttered forest and a room full of sharp turns using Gazebo. Benchmark comparisons validate that our method tracks more safely and robustly than the state-of-art method.

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