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Asian control Conference

作者： Fang Gao Min Wu Jinhua She Mingxing Fang Youwu Du Fang Wang College of Physics and Electronic Information Anhui Normal University Wuhu Anhui China School of Automation China University of Geosciences Wuhan Hubei China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan School of Electrical and Information Engineering Zhengzhou University of Light Industry Zhenzhou Henan China

ISBN: (纸本)9781509015740;9781509015733

A new disturbance rejection method to achieves good control performance for a nonlinear time-delay system is presented in this paper. This method effectively reject any disturbances. First, the configuration of the control system is constructed based on the equivalent-input-disturbance method. Then, a sufficient condition for global uniform ultimate boundedness and feedback controller are developed using linear matrix inequality. Finally, the effectiveness of the method is proved by a numerical simulation.

关键词： Matrix decomposition Observers Symmetric matrices Adaptive control Closed loop systems Steady-state

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Application of Hilbert-Huang decomposition to reduce noise and characterize for NMR FID signal of proton precession magnetometer

arXiv

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arXiv 2017年

作者： Huan, Liu Haobin, Dong Liu, Zheng Ge, Jian Bai, Bingjie Zhang, Cheng School of Automation China University of Geosciences Hubei Wuhan430074 China School of Engineering University of British Columbia Okanagan Campus KelownaBCV1X 1V7 Canada Institute of Geophysics and Geomatics China University of Geosciences Hubei Wuhan430074 China Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Systems Hubei Wuhan430074

The parameters in a nuclear magnetic resonance (NMR) free induction decay (FID) signal contain information that is useful in magnetic field measurement, magnetic resonance sounding (MRS) and other related applications. A real time sampled FID signal is well modeled as a finite mixture of exponential sequences plus noise. We propose to use the Hilbert-Huang Transform (HHT) for noise reduction and characterization, where the generalized Hilbert-Huang represents a way to decompose a signal into so-called intrinsic mode function (IMF) along with a trend, and obtain instantaneous frequency data. Moreover, the HHT for an FID signal's feature analysis is applied for the first time. First, acquiring the actual untuned FID signal by a developed prototype of proton magnetometer, and then the empirical mode decomposition (EMD) is performed to decompose the noise and original FID. Finally, the HHT is applied to the obtained IMFs to extract the Hilbert energy spectrum, to indicate the energy distribution of the signal on the frequency axis. By theory analysis and the testing of an actual FID signal, the results show that, compared with general noise reduction methods such as auto correlation and singular value decomposition (SVD), combined with the proposed method can further suppress the interfered signals effectively, and can obtain different components of FID signal, which can use to identify the magnetic anomaly, the existence of groundwater etc. This is a very important property since it can be exploited to separate the FID signal from noise and to estimate exponential sequence parameters of FID signal. Copyright © 2017, The Authors. All rights reserved.

关键词： Singular value decomposition

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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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controllability of giant connected components in a directed network

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Physical Review E 2017年第4期95卷 042318-042318页

作者： Xueming Liu Linqiang Pan H. Eugene Stanley Jianxi Gao Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China Center for Polymer Studies and Department of Physics Boston University Boston Massachusetts 02215 USA School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou 450002 Henan China Center for Complex Network Research and Department of Physics Northeastern University Boston Massachusetts 02115 USA

When controlling a complex networked system it is not feasible to control the full network because many networks, including biological, technological, and social systems, are massive in size and complexity. But neither is it necessary to control the full network. In complex networks, the giant connected components provide the essential information about the entire system. How to control these giant connected components of a network remains an open question. We derive the mathematical expression of the degree distributions for four types of giant connected components and develop an analytic tool for studying the controllability of these giant connected components. We find that for both Erdős-Rényi (ER) networks and scale-free (SF) networks with p fraction of remaining nodes, the minimum driver node density to control the giant component first increases and then decreases as p increases from zero to one, showing a peak at a critical point p=pm. We find that, for ER networks, the peak value of the driver node density remains the same regardless of its average degree 〈k〉 and that it is determined by pm〈k〉. In addition, we find that for SF networks the minimum driver node densities needed to control the giant components of networks decrease as the degree distribution exponents increase. Comparing the controllability of the giant components of ER networks and SF networks, we find that when the fraction of remaining nodes p is low, the giant in-connected, out-connected, and strong-connected components in ER networks have lower controllability than those in SF networks.

关键词： Network structure

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Semantic Motion Segmentation for Urban Dynamic Scene Understanding

Semantic Motion Segmentation for Urban Dynamic Scene Underst...

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IEEE International Conference on automation Science and Engineering

作者： Qiu Fan Yang Yi Li Hao Fu Mengyin Wang Shunting School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

ISBN: (纸本)9781509024100

A mount of recent researches on scene parsing and semantic labeling, while few focus on obtaining joint semantic motion labeling. In this paper, we propose an approach to infer both the object class and motion status for each pixel of images. First, we extract and match sparse image features to estimate ego-motion between two consecutive stereo images, the result of feature points grouping is used to segment moving object in U-disparity map. Second, a Fully Convolutional Neural Network is employed for semantic segmentation. Moreover, semantic cues are utilized to remove pixels have no potential to be moved in motion mask. Finally, we use a fully connected CRF to integrate motion into semantic segmentation. To validate the effectiveness of the proposed algorithm, we present experimental results with KITTI stereo images that contain moving objects.

关键词： Motion segmentation Semantics Image segmentation Computer vision Labeling Feature extraction Dynamics

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Force-feedback based active compliant position control strategy for a hydraulic quadruped robot

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Journal of Beijing Institute of Technology 2015年第4期24卷 546-552页

作者：王立鹏王军政马立玲陈光荣杨超峰 Key Laboratory of Intelligent Control and Decision of Complex System School of AutomationBeijing Institute of Technology

Most existing legged robots are developed under laboratory environments and, corre- spondingly, have good performance of locomotion. The robots＇ ability of walking on rough terrain is of great importance but is seldom achieved. Being compliant to external unperceived impacts is cru- cial since it is unavoidable that the slip, modeling errors and imprecise information of terrain will make planned trajectories to be followed with errors and unpredictable contacts. The impedance control gives an inspiration to realize an active compliance which allows the legged robots to follow reference trajectories and overcome external disturbances. In this paper, a novel impedance force/ position control scheme is presented, which is based on Cartesian force measurement of leg＇ s end effector for our hydraulic quadruped robot The simulation verifies the efficiency of the impedance model, and the experimental results at the end demonstrate the feasibility of the proposed control scheme.

关键词： active compliance impedance control force feedback contact force constrains space

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Analysis of underwater locomotion and improvement of FroBot

Analysis of underwater locomotion and improvement of FroBot

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2016 IEEE International Conference on advanced intelligent Mechatronics, AIM 2016

作者： Yi, Yang Jianqing, Zhang Han, Xu Maokuan, Chen Lu, Zhang Zhongjing, Zhu School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Department of Electronic Engineering School of Information Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781509020652

The main characteristic of FroBot is the dual-swing-legs propulsion mechanism, and it is necessary for us to conduct a series of experiments to study its propulsion model, both on land and underwater. As the propulsion of FroBot comes from the interaction force between caudal fins and water when it locomotes underwater, this paper presents an analysis about the propulsion and control of angle Θ. Then a number of underwater hydrodynamic simulations and analysis are also conducted to get a better control in reality. Finally, on the basis of propulsion model and experiments, we present the latest mechanical structure designs and further improvements to eliminate the limitations exposed in the previous generations of FroBot. © 2016 IEEE.

关键词： Propulsion

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Solving the uncertain multi-objective multi-stage weapon target assignment problem via MOEA/D-AWA

Solving the uncertain multi-objective multi-stage weapon tar...

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Congress on Evolutionary Computation

作者： Juan Li Jie Chen Bin Xin Lihua Dou Zhihong Peng School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing P.R.China

ISBN: (纸本)9781509006243

The weapon target assignment (WTA) problem is a fundamental problem arising in defense-related applications of operations research. And the multi-stage weapon target assignment (MWTA) problem is the basis of dynamic weapon target assignment (DWTA) problems which commonly exist in practice. The MWTA problem considered in this paper is with uncertainties, namely the uncertain MWTA (UMWTA) problem, and is formulated into a multi-objective constrained combinatorial optimization problem with two competing objectives. Apart from maximizing damage to hostile targets, this paper follows the principle of minimizing ammunition consumption under the assumption that each element of the kill probability matrix follows four different probability distributions. In order to tackle the two challenges, i.e., multi-objective and the uncertainty, the multi-objective evolutionary algorithm based on decomposition with adaptive weight adjustment (MOEA/D-AWA) and the Max-Min robust operator are adopted to solve the problem efficiently. Then comparison studies between the MOEA/D-AWA and a single objective solver used for a relaxed formulation on solving both certain and uncertain instances of two different scaled MWTA problems which include four uncertain scenarios are conducted. Numerical results show that MOEA/D-AWA outperforms the single objective solver on solving both certain and uncertain multi-objective MWTA problems discussed in this paper. Comparisons between the results of the certain and uncertain formulation also indicate the necessity of the robust formulation of practical problems.

关键词： Weapons Uncertainty Discrete wavelet transforms Optimization Robustness Decision making Evolutionary computation

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Adaptive key SURF feature extraction and application in unmanned vehicle dynamic object recognition

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Journal of Beijing Institute of Technology 2015年第1期24卷 83-90页

作者：杜明芳王军政李静李楠李多扬 Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Automation School Beijing Union University

A new method based on adaptive Hessian matrix threshold of finding key SRUF （ speeded up robust features） features is proposed and is applied to an unmanned vehicle for its dynamic object recognition and guided navigation. First, the object recognition algorithm based on SURF feature matching for unmanned vehicle guided navigation is introduced. Then, the standard local invariant feature extraction algorithm SRUF is analyzed, the Hessian Metrix is especially discussed, and a method of adaptive Hessian threshold is proposed which is based on correct matching point pairs threshold feedback under a close loop frame. At last, different dynamic object recognition experi- ments under different weather light conditions are discussed. The experimental result shows that the key SURF feature abstract algorithm and the dynamic object recognition method can be used for un- manned vehicle systems.

关键词： dynamic object recognition key SURF feature feature matching adaptive Hessianthreshold unmanned vehicle

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