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检索条件"机构=Key Laboratory of Complex System Intelligent Control and Decision"

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Multipath error analysis of carrier tracking loop in GPS receiver

Multipath error analysis of carrier tracking loop in GPS rec...

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作者： Cheng, Lan Chen, Jie Gan, Ming-Gang School of Automation Beijing Institute of Technology Beijing 100081 China Education Ministry Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9787894631046

The error of Code Tracking Loop(CTL) of GPS receiver influences the error of carrier tracking loop in the presence of multipath. The error models of carrier tracking loop are established in the multipath environment when the non-coherent Early Minus Late(EML) power mode CTL and the non-coherent Dot-product(DOT) power mode CTL are used. The impacts of multipath parameters and correlator spacing on the error of carrier tracking loop are analyzed by simulation. The simulation results show that the two non-coherent CTLs have little difference in affecting the carrier tracking error. Furthermore, the narrow correlator technology cannot reduce the error of carrier tracking loop.

关键词： Global positioning system

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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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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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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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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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Relative Localization for UAV-UGV Based on Correlation of Bearing and Distance

Relative Localization for UAV-UGV Based on Correlation of Be...

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IEEE International Conference on Mechatronics and Automation

作者： Jia Guo Kang Hu Jinting Liu State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology No.5 Zhongguancun South Street Beijing China

To ensure reliable localization for Unmanned Aerial Vehicles(UAVs) in the presence of uncertain speed of the Unmanned Ground Vehicle (UGV), this study examines the relative localization problem of UAV-UGV using distance and bearing measurements. A Correlation of Bearing and Distance-based Relative Localization (CBDRL) algorithm is proposed in this paper under this scenario. The estimation of altitude, distance, and angle are simplified into a representation of the relative positioning between the UAV and UGV. The relative height difference is measured using the barometer in the algorithm. To determine the relative distance, Time of Arrival (TOA) ranging and Ultra Wide Band (UWB) communication are utilized. The relative direction measurement is then determined using the correlations of bearing and distance. We integrate these observations with height, direction, and distance data in an Extended Kalman Filter(EKF) to provide accurate and reliable relative position estimates that allow the UAV to track the target. The simulation results indicate that the CBDRL method developed in this study is superior to previous relative localization algorithms that rely on multi-sensor fusion, and can significantly enhance the accuracy of UAV positioning provided that range and angle measurements are precise enough.

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Automatic target tracking algorithm based on NMI feature matching with Position Prediction and its DSP realization

Automatic target tracking algorithm based on NMI feature mat...

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作者： Chen, Wenjie Liu, Jin Gan, Ming-Gang School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9787894631046

Algorithm based on NMI feature matching and Position Prediction for automatic target tracking are develop for realize an DSP based real-time target tracking system. The target is firstly detected with a improved frame-difference method, and then the target area is segmented based on threshold segmentation and region growth. The NMI feature is used for matching. Finally a combining forecast algorithm is used in the tracking system. This tracking system is implemented with a DSP controller and software is accomplished on DSP/BIOS operation system. It is proved that it can be meet the needs of real-time stably tracking and overcome the disturbance brought by attitude variances and short time occlusion.

关键词： Target tracking

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Denoising of fiber optic gyroscope signal by unsupervised adaptive filtering

Denoising of fiber optic gyroscope signal by unsupervised ad...

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作者： Ma, Tao Chen, Jie Chen, Wenjie Zhang, Bo School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9787894631046

Angle random walk (ARW) is the noise component at the output of a fiber optic gyroscope (FOG) and it affects the FOG short-term accuracy. Using only the noise property described by random walk coefficient, we developed an unsupervised adaptive filter (UAF) for suppressing the noise. Theoretical analysis illuminates that UAF performs as good as the best FIR filter in the sense of means square. Experimental results both in stationary and non-stationary cases show that UAF is more effective than wavelet denoising and that based on fast fourier transform.

关键词： Adaptive filters

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Application of an improved independent component analysis to artifacts removal from EEG

Application of an improved independent component analysis to...

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作者： Peng, Zhihong Luo, Junping School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9787894631046

EEG data can be easily influenced by other components in the process of recording, which would thus interfere the analysis. Independent Component Analysis (ICA) is a valid method for blind source separation. It can estimate original signals' independent components from observed signals even the original signals and mixing model are unknown. Considering the shortcomings of the application of two ICA algorithms, FastICA and extended Infomax, to EEG artifacts removal, we propose a novel InfastICA algorithm by combing FastICA and extended Infomax. By appling to removal of the EOG artifacts from EEG, test results show that this new algorithm has no special requests to the matrix W's default values and study steps, and has a fast convergence speed, with simple operation and practical application.

关键词： Independent component analysis

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