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

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A Self-correcting Localization Approach for Automobile Robots Based on the Two Dimensional LADAR

A Self-correcting Localization Approach for Automobile Robot...

引用

第35届中国控制会议

作者： Jing Li Wenxue Liu Junzheng Wang Jianan Qiao Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

ISBN: (纸本)9781509009107

In this paper,a novel localization approach for autonomous mobile robots is *** can accomplish the all-terrain localization function with the laser radar(LADAR) and the inertial measurement unit(IMU).First of all,for the multiple-input nonlinear localization system,a fuzzy filter is built up to estimate the position of the mobile ***,an efficient evaluation index is raised to determine whether the landmarks extracted from the adjacent data frame are the same,which can help the mobile robot to realize the self-correction *** the final,the experiments in the real world are implemented to show the effectiveness of the proposed approach.

关键词： Localization SLAM Fuzzy filter Self-correcting Obstacle match

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Process Noise Estimator Based on Observation Sequence and its Application on Inertial Navigation system

Process Noise Estimator Based on Observation Sequence and it...

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2016 IEEE 13th International Conference on Signal Processing（ICSP2016）

作者： Xiao Xuan Huang Kun Yang Liming Liang Yuan Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

Kalman filter has been extensively applied in vast areas. However, it is widely acknowledged that the performance of Kalman filter depends on the accuracy of priori information such as model structure, statistics information of process and observation noise. Obtaining the covariance matrix of process noise is difficult in some application *** such background, this paper presents a process noise estimation algorithm based on the noise observation sequence. By constructing a transform matrix and removing the state variables from the observation, the noise observation sequence can be established, through which the covariance matrix of process noise can be estimated. Comparing to conventional adaptive filter, this algorithm needs less calculation. Moreover,the noise estimation process is separated from Kalman filter thus ensures Kalman Filters independence and optimality. The simulation results show that the new algorithm can effectively estimate the process noise covariance, and remain uninfluenced by the initial condition.

关键词： Adapt Kalman filter noise estimate

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Observer-based fault detection for affine nonlinear systems with disturbances and uncertainties 35

Observer-based fault detection for affine nonlinear systems ...

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第35届中国控制会议

作者： HAN Huayun YANG Ying LI Linlin Chen Yu State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of Engineering Peking University School of Automation and Electrical Engineering University of Science and Technology Beijing the Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen Beijing Institute of Astronautics System Engineering

ISBN: (纸本)9781509009107

This paper is concerned with the integrated design schemes of L observer-based fault detection（FD） systems for affine nonlinear processes with disturbances and uncertainties,*** this end,a so called L observer-based FD scheme is studied ***,the integrated design approaches for nonlinear systems with disturbances and uncertainties are addressed,*** the end,examples are given to illustrate the effectiveness of the proposed approaches.

关键词： Robust Fault Detection Observer Design Affine Nonlinear systems

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Consensus disturbance rejection control for second-order multi-agent systems via nonsingular terminal sliding-mode control

Consensus disturbance rejection control for second-order mul...

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International Workshop on Variable Structure systems, VSS

作者： Xiangyu Wang Shihua Li Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing PR China

In this paper, consensus disturbance rejection control problem for a class of second-order leader-follower multi-agent systems are investigated. Such systems not only contain unmeasurable states but also suffer from mismatched disturbances. By combining integral-type nonsingular terminal sliding-mode control technique and an extended-state observer technique together, finite-time consensus is achieved. Firstly, to obtain accurate information of the unmeasurable states and disturbances, an extended-state observer is designed for each follower. Secondly, the states and disturbances estimates are distributedly employed to design nonlinear terminal sliding-mode surfaces. Finally, based on these sliding-mode surfaces, sliding-mode consensus protocols are designed via output feedback. Simulations illustrate the effectiveness of the proposed distributed control scheme.

关键词： Observers Multi-agent systems Protocols Decentralized control Convergence Laplace equations Topology

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Cooperative robust output regulation for second-order nonlinear multi-agent systems with an unknown exosystem

Cooperative robust output regulation for second-order nonlin...

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IEEE Annual Conference on Decision and control

作者： Yi Dong Jie Chen Jie Huang Department of Automation Chinese University of Hong Kong Shatin N.T. Hong Kong State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Department of Mechanical and Automation Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong

The cooperative robust output regulation problem for a class of second-order nonlinear multi-agent systems with an exactly known exosystem has been studied recently. This paper further studies the same problem for a class of second-order nonlinear multi-agent systems subject to an unknown exosystem. We first show that the problem can be converted into the adaptive stabilization problem for a modified augmented system composed of the given multi-agent system and the distributed internal model. Due to the uncertain parameter in the exosystem, the augmented system is a nonlinear multi-input system with both dynamic and static uncertainties. By combining the adaptive control technique and the robust control technique, we solve our problem by a distributed adaptive robust state feedback controller.

关键词： Multi-agent systems Mathematical model Robustness Robust control Automation Electronic mail Nickel

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Sensor Fault Diagnosis based on On-line Random Forests

Sensor Fault Diagnosis based on On-line Random Forests

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第35届中国控制会议

作者： Li Yang Zhang Jia Deng Fang Chen Jie School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control of Complex System

ISBN: (纸本)9781509009107

In order to reduce the memory requirement,and obtain real-time status of equipment,the paper proposed to use the the on-line random forests(ORFs) algorithm to identify sensor *** sample set is derived from Tennessee Eastman(TE)*** models are updated by a group of sensor data,which are collected in each *** models are real-time and dynamic,the equipment could be tested at any ***,the samples obtained at previous intervals are not need to *** results of experiments show that the accuracies of ORFs and Random Forests(RFs) are similar in sensor fault diagnosis *** in some fast changing process,ORFs distinguishes fault types with higher accuracy,better adaptable and faster than RFs.

关键词： On-line Random Forests Sensor fault Tennessee Eastman process

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Optimal data integrity attack on actuators in Cyber-Physical systems

Optimal data integrity attack on actuators in Cyber-Physical...

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American control Conference

作者： Guangyu Wu Jian Sun The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology China

ISBN: (纸本)9781467386838

The security issues are of prime importance for Cyber-Physical systems (CPSs). Most existing works mainly investigate the secure control schemes against malicious attackers. This article analyzes how to design an data integrity attack scheme from the viewpoint of an attacker. The formulation of our approach is basically similar to the one of conventional optimal control method, with different prerequisites and solutions. An output feedback control system under data integrity attacks on actuators is considered in this article. Our work is aimed at constructing an optimal feedback attack law to maximize the error between the attacked system's output and the healthy system's output. Numerical examples are presented to demonstrate the effectiveness of the proposed method.

关键词： Actuators Cyber-physical systems Optimal control Computer crime Jamming actuators Computer crime Cyber-physical systems jamming Data Quality Optimal control Feedback control systems

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A two-column Convolutional Neural Network for Facial Point Detection

A two-column Convolutional Neural Network for Facial Point D...

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2016 IEEE International Conference on Progress in Informatics and Computing

作者： Wei Wang Xiaobo Lu Jiaji Song Cong Chen School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

This paper proposes a two-column convolutional neural network algorithm for face point detection, which proves better performance than single-column. Because of the deep level structure, global texture features are extracted at higher layers of the network, and the results of keypoint location remains high accuracy. In the first column, we take the channel component of original image as input to train the neural network respectively and calculate the average location results. In the second one, we use Sobel operator to extract first-order derivative feature of original image and regard it as the input to train another convolutional network. The location results of two columns above are fused with appropriate proportion to ensure better results. Experimental result on LFW dataset shows the performance of the proposed parallel structure better than single convolutional network, and it stays robust due to occlusions, large pose variations and extreme lighting.

关键词： facial point detection convolutional neural network Sobel information fusion

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A Robust Traffic Driver Face Detection Method

A Robust Traffic Driver Face Detection Method

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2016 IEEE International Conference on Progress in Informatics and Computing

作者： Dechao Luo Xiaobo Lu Changhui Hu Xiang Peng Wei Wang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

Face detection technology is a hot topic in the past recent years. It has been maturely applied to many practical areas. However, the driver face detection is still an open problem to solve. In this paper, we proposed an improved method to promote the face detection rate and apply it to the images from the monitoring videos. The first step is to detect the car from the images according to an off-line learning method. Then the method based on additional off-line learning method is the front level for skin color feature in order to correctly detect the driver face. The proposed systems are implemented on the various complicated road environment. The results show that the proposed method improves the efficiency of the driver face detection and is of strong robustness on having glasses, driver head rotation, and lighting change.

关键词： car detection driver face detection skin color feature Haar-like feature Adaboost

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Intelligent Video Analysis-based Forest Fires Smoke Detection Algorithms

Intelligent Video Analysis-based Forest Fires Smoke Detectio...

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International Conference on Natural Computation, Fuzzy systems and Knowledge Discovery

作者： Min Cai Xiaobo Lu Xuehui Wu Yifei Feng School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (纸本)9781509040940

In order to discover forest fire as early as possible, forest fire detection should focus on the smoke in early fire. This paper focuses on three key issues: motion segmentation, feature extraction and classifier design. Background subtraction based on visual background extractor (Vibe) is chosen to divide suspected smoke area when taking into account the accuracy and time consumption. And then do some corresponding morphological processing. Later on, various static and dynamic characteristics of smoke were extracted and different tests were done based on different feature combinations in forest fire smoke detection system. Lots of smoke detecting system only think about static features which will result in a certain degree of misjudgment. Analyzing the false positive rate and recognition rate of these experiments' results, the combination of movement direction, high-frequency energy based on wavelet transformation and compactness is selected to constitute the final recognition vectors. In addition, the continuity which is not mentioned in other researches won't be ignored in this paper. The final experimental results showed that the accuracy rate of this method for smoke detection could reach 92.7%.

关键词： Smoke detection Vibe Feature extraction Support vector machine

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