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检索条件"机构=Key Laboratory for Intelligent Control&Decision of Complex Systems"

共 577 条记录，以下是421-430 订阅

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Power system state estimation via feasible point pursuit: Algorithms and Cramér-rao bound

Power system state estimation via feasible point pursuit: Al...

引用

作者： Wang, Gang Zamzam, Ahmed S. Giannakis, Georgios B. Sidiropoulos, Nicholas D. State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Department of Electrical and Computer Engineering University of Virginia CharlottesvilleVA22904 United States

Accurately monitoring the system's operating point is central to the reliable and economic operation of an autonomous energy grid. Power system state estimation (PSSE) aims to obtain complete voltage magnitude and angle information at each bus given a number of system variables at selected buses and lines. Power flow analysis amounts to solving a set of noise-free power flow equations, and is cast as a special case of PSSE. Physical laws dictate quadratic relationships between available quantities and unknown voltages, rendering general instances of power flow and PSSE nonconvex and NP-hard. Past approaches are largely based on gradient-type iterative procedures or semidefinite relaxation (SDR). Due to nonconvexity, the solution obtained via gradient-type schemes depends on initialization, while SDR methods do not perform as desired in challenging scenarios. This paper puts forth novel feasible point pursuit (FPP)-based solvers for power flow analysis and PSSE, which iteratively seek feasible solutions for a nonconvex quadratically constrained quadratic programming reformulation of the weighted least-squares (WLS). Relative to the prior art, the developed solvers offer superior numerical performance at the cost of higher computational complexity. Furthermore, they converge to a stationary point of the WLS problem. As a baseline for comparing different estimators, the Cramér-Rao lower bound is derived for the fundamental PSSE problem in this paper. Judicious numerical tests on several IEEE benchmark systems showcase markedly improved performance of our FPP-based solvers for both power flow and PSSE tasks over popular WLS-based Gauss-Newton iterations and SDR approaches. © 1991-2012 IEEE.

关键词： State estimation

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The Modeling and Estimation of Asynchronous Multirate Multisensor Dynamic systems

The Modeling and Estimation of Asynchronous Multirate Multis...

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第三十二届中国控制会议

作者： Liping Yan Bo Xiao Yuanqing Xia Mengyin Fu School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781479900305

This paper is concerned with the state estimation of a linear dynamic system and the fusion of asynchronous multirate multisensor *** dynamic system is described at the finest scale with multiple sensors observing a single target independently at different scales with different sampling *** main result is that the multiscale measurements are properly formulated,and an optimal recursive fusion algorithm is presented.A numerical example is given to show the feasibility and efficiency of the algorithm.

关键词： state estimation recursive fusion asynchronous multirate multiscale Kalman filter

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Data-Driven Model for Detection, Isolation and Accommodation of Faulty Angle of Attack Sensor Measurements in Fixed Winged Aircraft

Data-Driven Model for Detection, Isolation and Accommodation...

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Chinese control and decision Conference, CCDC

作者： Bemnet Wondimagegnehu Mersha Hongbin Ma School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665478977

Ethiopian Airlines’ Boeing 737-8 MAX nosedived and crashed shortly after takeoff on March 10, 2019, at Ejere Town, south of Addis Ababa. A faulty angle of attack (AOA) sensor was the cause of the crash. Many airplane accidents have been linked to faulty AOA sensors in the past. The majority of the AOA sensor fault detection, isolation, and accommodation (SFDIA) literature relied on linear model-driven techniques, which are not suitable when the system’s model is uncertain, complex, or nonlinear. Traditional multilayer perceptron (MLP) models have been employed in data-driven models in the literature and the effectiveness of deep learning-based data-driven models has not been investigated. In this work, a data collection and processing method that ensures the collected data is not monotonous and a data-driven model for AOA SFDIA is proposed. The proposed model uses a deep learning-based recurrent neural network (RNN) to accommodate for faulty AOA measurement under flight conditions with faulty AOA measurement, faulty total velocity measurement, and faulty pitch rate measurement. Conventional residual analysis with a fixed threshold is used to detect and isolate faulty AOA sensors. The proposed and benchmark models are trained with the adaptive momentum estimation (Adam) algorithm. We show that the proposed model effectively detects, isolates, and accommodates faulty AOA measurements when compared to other data-driven benchmark models. The method is able to detect and isolate faulty AOA sensors with a detection delay of 0.5 seconds for ramp failure and 0.1 seconds for step failure.

关键词： Adaptation models Recurrent neural networks Atmospheric modeling Fault detection Transportation Benchmark testing Velocity measurement

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An algorithm for Quadruped Robot’s Inverse Kinematic Problems Based on PSO

An algorithm for Quadruped Robot’s Inverse Kinematic Proble...

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第37届中国控制会议

作者： Wei Shen Min Li Junzheng Wang Changkun Chai Wen Zheng Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Institute of Software Chinese Academy of Sciences Siemens China LTD

The inverse problem is an essential problem in robot *** order to deal with the inverse kinematic problems of hydraulic quadruped robot,the motion process of a single leg is modeled,simulated and analyzed.A new method based on particle swarm optimization（PSO） is proposed in this paper to overcome low computational efficiency,long calculation time and accumulative *** proposed algorithm is attributed to:1) limit the range of particles initialization;2) select suitable compressibility factors;3) employ linear interpolation method to improve the efficiency of the inverse *** simulation results demonstrate that the developed method can provide enhanced computational efficiency and significantly reduce the calculation time while ensuring the precision requirement,and can also eliminate the accumulative error.

关键词： Inverse kinematics Motion optimization Particle swarm optimization Quadruped robot

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Robust Scene Matching Method Based on Sparse Representation

Robust Scene Matching Method Based on Sparse Representation

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第35届中国控制会议

作者： Sai Yang Bo Xiao Liping Yan Yuanqing Xia Yang Liu Mengyin Fu Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781509009107

This article presents two efficient scene matching methods based on sparse representation,which are robust to noise and *** process of searching for the correct matching position in the reference image can be considered as finding a certain atom in a dictionary to represent the vectorized sensed *** atoms that form the dictionary are vectorized blocks which represent all the possible matching *** also use two steps matching to speed up the running time,and further improve the performance to some *** demonstrate that our scene matching methods perform better than traditional methods due to the inherent robustness to corruption of sparse representation.

关键词： scene matching sparse representation visual navigation

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Optimal sequential estimation for multirate dynamic systems with unreliable measurements and correlated noise

Optimal sequential estimation for multirate dynamic systems ...

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第35届中国控制会议

作者： Liping Yan Jun Liu Lu Jiang Yuanqing Xia Bo Xiao Yang Liu Mengyin Fu Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781509009107

In the field of target tracking and navigation,multi-sensor data fusion has been widely *** of the data fusion algorithms are built on the premise that the sensor observation information is ***,in practical problems,due to the limitation of communication and sensor fault,etc.,data missing or unreliable measurements will happen *** addition,at present a lot of research is aimed at the situation where measurement noise between various sensors is not relevant,and process noise and measurement noise is *** correlation is more *** this paper,a multi-rate multi-sensor data fusion state estimation algorithm with unreliable observations under correlated noises is presented.A numerical example is given to show the feasibility and effectiveness of the presented algorithm.

关键词： state estimation sequential fusion correlated noise unreliable measurements

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Optimized model reference adaptive motion control of robot arms with finite time tracking

Optimized model reference adaptive motion control of robot a...

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Chinese control Conference (CCC)

作者： Chenguang Yang Hongbin Ma Mengyin Fu Alex M. Smith School of Computing and Mathematics University of Plymouth Plymouth UK Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institution of Technology BIT Beijing China

ISBN: (纸本)9781467325813

In this paper, we study motion control of general n degrees of freedom (DOFs) rigid robot arms. Aiming at shaping the controlled closed-loop dynamics to be of minimized motion tracking errors and as well as angular accelerations, we employ the linear quadratic regulation (LQR) optimization technique to obtain an optimal reference model. Adaptive control is then developed to ensure that the reference model can be matched in finite time, in the presence of various uncertainties. The stability and optimal tracking performance have been rigorously established by theoretic analysis.

关键词： Adaptation models Tracking Impedance Manipulators Adaptive control Force

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Image Matching Based on Multiscale Increment Sign Correlation and Iterative Correction

Image Matching Based on Multiscale Increment Sign Correlatio...

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第35届中国控制会议

作者： Liping Yan Sai Yang Shuo Li Yuanqing Xia Bo Xiao Yang Liu Mengyin Fu Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781509009107

By combining wavelet transform and increment sign correlation with iterative correction,we present a robust image matching method,which effectively reduced ***,by decomposing the sensed image and the reference image with wavelet,smooth images are generated in coarse *** the use of increment and decrement information of adjacent pixels,smooth images are encoded into binary images,and the matching position can be found by use of the cross correlation *** decomposition can effectively remove noise and greatly improve the real-time performance of matching algorithm while increment sign correlation method is not sensitive to the gray level of *** combination of wavelet transform and increment sign correlation can deal with noise,shadow and occlusion as well as improve the matching speed compared with traditional matching *** the condition of heavy noise and occlusion that the matching method mentioned above can not find the correct position in condition of heavy noise and occlusion,we present an iterative correction image matching method,*** the above matching result as prior knowledge and achieve the correct matching position by correcting matching results *** analysis shows the feasibility of the presented method,and our experiments show its validity.

关键词： Image Matching Wavelet Decomposition Increment Sign Correlation Iterative Correction

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Sequential Fusion and State Estimation for Asynchronous Multirate Multisensor Dynamic systems

Sequential Fusion and State Estimation for Asynchronous Mult...

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第三十三届中国控制会议

作者： Lu Jiang Liping Yan Bo Xiao Yuanqing Xia Mengyin Fu School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

A sequential fusion and state estimation algorithm for an asynchronous multirate multisensor dynamic system is presented in this *** dynamic system at the finest scale is *** are multiple sensors observing a single target independently with different sampling rates,and the observations are obtained *** present algorithm is shown to be more effective and efficient than the existed *** on a radar tracking system with three sensors are done and show the effectiveness of the present algorithm.

关键词： state estimation,sequential fusion,asynchronous,multirate multisensor,Kalman filter

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A Quantitative Performance Evaluation Index for Image Fusion: Normalized Perception Mutual Information

A Quantitative Performance Evaluation Index for Image Fusion...

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Chinese control Conference

作者： Liping Yan Yulei Liu Bo Xiao Yuanqing Xia Mengyin Fu School of Automation Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781467325813

Information entropy based criteria are analyzed and the Normalized Mutual Information(NMI) that is presented in the field of image registration is revised to Normalized Mutual Information Entropy (NMIE) to meet the need of the evaluation of image fusion algorithms, Then, through analysis to NMIE and some human perception based criteria, and by analyzing the essence of image fusion techniques systematically, a new index, Normalized Perception Mutual Information (NPMI), is defined in view of information transmission as well as edge preservation, and is used to evaluate the performance of image fusion algorithms, The experiments are done to three groups of images, namely, the remote sensing images corrupted by noises, the multifocus images and the medical images obtained by CT and MRI, respectively. Compared with other indices including the root mean square error (RMSE), space frequncy (SF), space visibility (SV), entropy, the collective cross entropy (CCE), information deviation (ID), and the edge information preservation value (EIPV), etc., NPMI is shown to be the only one that is effective in all the eases in the evaluation of the performances of the fused images or the image fusion algorithms, which illustrates the feasibility and effectiveness of the presented algorithm.

关键词： Image fusion Performance evaluation Mutual information Human perception Normalized perception mutual intonation

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