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第37届中国控制会议

作者： Han Li Jian Ge Haobin Dong Xiangyu Qiu Wang Luo Huan Liu Zhiwen Yuan Jun Zhu Haiyang Zhang School of Automation China University of Geosciences School of Automation China University of Geosciences Wuhan Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Institute of Geophysics & Geomatics China University of GeosciencesWuhan

Aeromagnetic survey is widely used in geophysical exploration because of large exploration range and little limitations on geographical environment. Aiming at the problem using manned aircraft in aeromagnetic survey, an aeromagnetic system of rotor unmanned aerial vehicle(UAV) based on Overhauser sensor is established. It can carry out high-precision geomagnetic measurement with small magnetic interference and omidirection. Firstly, the magnetic interference of rotor UAV is analyzed and the mathematical model is established for software compensation. Next, aeromagnetic magnetometer based on Overhauser sensor is developed. Finally, the least squares is used to estimate the coefficients. The necessity and superiority of allowing for the eddy-current magnetic field is verified by comparing the fitting results. Moreover, the flight test was carried out and the results showed that the improvement ratio was 6.86. The compensation effect of magnetic interference is verified and magnetic anomaly signal is extracted successfully.

关键词： aeromagnetic compensation Overhauser sensor rotor unmanned aerial vehicle

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An Improved Equivalent-Input-Disturbance Approach for Disturbance-Rejection Using High-Gain Observer

An Improved Equivalent-Input-Disturbance Approach for Distur...

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第37届中国控制会议

作者： Youwu Du Weihua Cao Jinhua She Mingxing Fang Zibao Lu School of Automation China University of Geosciences College of Physics and Electronic Information Anhui Normal University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

An improved equivalent-input-disturbance(EID) approach is presented in this paper to promote the transient performance of disturbance rejection in the control system. A high-gain observer(HGO) is introduced to the conventional EID method to accelerate the convergence of state error. This makes the estimated disturbance tracking the exogenous disturbance more quickly and more precisely. First, the configuration of an improved EID-based control system is described. Then, a sufficient stability condition is derived in terms of a linear matrix inequality(LMI). The resulting LMI is used to find the gains of state observer and state feedback controller. Finally, the validity of the devised method and its superiority over a conventional EID method is demonstrated through the simulation of a numerical example.

关键词： Disturbance rejection disturbance estimation equivalent input disturbance（EID） high-gain observer linear matrix inequality（LMI）

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A Multi-model Estimation of Distribution Algorithm for Agent Routing Problem in Multi-point Dynamic Task

A Multi-model Estimation of Distribution Algorithm for Agent...

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第37届中国控制会议

作者： Sai Lu Bin Xin Lihua Dou Ling Wang School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Department of Automation Tsinghua University

The agent routing problem in multi-point dynamic task（ARP-MPDT） is a multi-task routing problem of a mobile agent. In this problem, there are multiple tasks to be carried out in different locations. As time goes on, the state of each task will change nonlinearly. The agent must go to the task points in turn to perform the tasks, and the execution time of each task is related to the state of the task point when the agent arrives at the point. ARP-MPDT is a typical NP-hard optimization problem. In this paper, we establish the nonlinear ARP-MPDT model. A multi-model estimation of distribution algorithm（EDA） employing node histogram models（NHM） and edge histogram models（EHM） in probability modeling is used to solve the ARP-MPDT. The selection ratio of NHM and EHM probability models is adjusted adaptively. Finally, performance of the algorithm for solving the ARP-MPDT problem is verified by the computational experiments.

关键词： Estimation of distribution algorithm Multi-model Routing Multi-point dynamic task

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ICB-MOEA/D: An interactive classification-based multi-objective optimization algorithm

ICB-MOEA/D: An interactive classification-based multi-object...

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第37届中国控制会议

作者： Bin Xin Hepeng Li Ling Wang School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Department of Automation Tsinghua University

Interactive multi-objective optimization algorithms have developed rapidly in recent years. In this paper, we propose a new classification-based interactive multi-objective optimization algorithm named ICB-MOEA/D to solve the formulated multiobjective optimization problem. ICB-MOEA/D provides several solutions for the decision maker to choose. The decision maker chooses his/her most preferred solution from these solutions and the historical solutions which have been chosen as the current most preferred solution. ICB-MOEA/D records this solution and classifies the objectives according to the updated preference information into four categories: 1) objectives which are expected to be improved;2) objectives which can be sacrificed;3) objectives which are expected to remain basically unchanged;4) objectives which do not matter currently. Accoding to the number of the objectives in the first category, a new single-objective opitimization model or multi-objective optimization model will be built. The single-objective optimization model will be optimized by a classic variant of differential evolution DE/rand/1/bin, and the multi-objective optimization model will be optimized by a popular docomposition-based multi-objective optimizer MOEA/*** the classifications are done automatically by the algorithm, reducing the burden of the decision maker. ICB-MOEA/D was tested on the two-objective instance ZDT1, and the experiment results show the effectiveness of ICB-MOEA/D.

关键词： interactive multi-objective optimization decomposition classification virtual decision maker

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Correction to: A method of VR‑EEG scene cognitive rehabilitation training

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Health information science and systems 2021年第1期9卷 7页

作者： Wenjun Tan Yang Xu Pan Liu Chunyan Liu Yujin Li Yanrui Du Chao Chen Yuping Wang Yanchun Zhang Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang 110189 China. Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou 510006 China. Department of Neurology Xuanwu Hospital Capital Medical University Beijing 100053 China. Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin 300384 China. Institute for Sustainable Industries and Liveable Cities Victoria University Melbourne VIC 8001 Australia.

[This corrects the article DOI: 10.1007/s13755-020-00132-6.].

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Coke quality prediction based on Gaussian model feature extraction and xgboost feature selection algorithm 5

Coke quality prediction based on Gaussian model feature extr...

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5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Li, Zezhong Cao, Weihua Chen, Luefeng Wu, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

This paper focuses on extracting effective vitrinite reflectance features, and selecting the most important features to predict coke quality. Feature extraction method based on Gaussian model is proposed, which can extract vitrinite reflectance features, the vitrinite reflectance features and traditional features are fused together to excavate the relationship between coal and coke quality. Then Xgboost is used as a new feature selection method to measure features importance and remove the redundant features. Finally, high correlation features are selected as input variables to predict coke quality, which can enhance prediction performance and stability. Experimental results show that the proposal outperforms prediction model based on traditional indicators.

关键词： Feature Selection

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New constructing method of Lyapunov-Krasovskii functionals for stability of time-varying delay systems 43

New constructing method of Lyapunov-Krasovskii functionals f...

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43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017

作者： Zhenman, Gao Yong, He Min, Wu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9781538611272

This paper investigates the stability of linear systems with a time-varying delay. We propose a new approach to construct Lyapunuv-Krasovskii functional (LKF). Compared with other traditional approach, the proposed one can provide a higher time-delay upper bound and lower computation complexity. Six stability criteria by linear matrix inequalities (LMIs) are established by proposed two novel LKFs in this paper. Based on one numerical example, the advantages of the proposed approach are illustrated. © 2017 IEEE.

关键词： Stability criteria

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ANFIS control for photovoltaic systems with DC-DC converters 2017

ANFIS control for photovoltaic systems with DC-DC converters

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2017 International Conference on automation, control and Robots, ICACR 2017

作者： Sarhan, Mohammad Abu Ding, Min Chen, Xin Ou, Yingxiong Wu, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9781450363501

This paper presents a maximum power point tracking controller for a PV solar system. The PV solar system is connected to the load through a DC-DC boost converter which is controlled by Adaptive Neuro-Fuzzy Inference system (ANFIS) MPPT controller. The ANFIS controller is modeled by selecting the irradiation and temperature as an input for the controller while the duty cycle is the output of the controller. To demonstrate that the performance of ANFIS MPPT controller gives more accurate results and more efficiency with respect to the measured results, it is compared with Fuzzy Logic (FL) MPPT controller and Neural Network (NN) MPPT controller. The analyzed results and the comparison have been obtained through MATLAB/Simulink Environment. © 2017 Copyright is held by the owner/author(s).

关键词： controllers

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A CUDA-based iterative segmentary parallel Gaussian-kernel function adaptive dynamic programming algorithm 5

A CUDA-based iterative segmentary parallel Gaussian-kernel f...

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5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Li, Lu Chen, Xin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

Adaptive Dynamic Programming (ADP) with critic-actor structure is a useful way to achieve online learning control. The Gaussian-Kernel Function Adaptive Dynamic Programming (GK-ADP) algorithm does not need to preset the value function model which greatly enhances the applicability of ADP method in continuous space. However, when the complexity of the system increases in practice, the scale of sample set will increase which will induce a high computation cost. In order to speed up computation, a CUDA-Based Iterative Segmentary Gaussian-Kernel Function Adaptive Dynamic Programming algorithm( cuISGK-ADP) is presented in this paper. The algorithm uses singular value decomposition to decompose the large-scale matrix and uses CUDA with multi-threaded structure in order to enhance the performance. The comparison result illustrates that the computation burden which hinders the GK-ADP's application is reduced when the cuISGK-ADP algorithm is introduced. The proposed approach enhances the efficiency of the computation to a large extent.

关键词： Singular value decomposition

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A scale transform and deformation target tracking algorithm based on correlation filtering

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IOP Conference Series: Materials Science and Engineering 2019年第5期569卷

作者： Cong Hu Wei Xia Peng Chen Shun Huang Hui Guo Xing Jin School of Automation China University of Geosciences Wuhan 430074 China Hubeikey laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan 430074 China

In order to improve the robustness of the correlation filtering (CF) tracking algorithm and overcome the problem that the traditional correlation filtering method can not deal with the target's scale and deformation change, a feature-adaptive scale adaptive correlation filter tracking algorithm is proposed. Firstly, the target is characterized; then the output filter is calculated by using the correlation filter; finally, the image blocks of different scales are intercepted from the target position of the current frame, and the optimal estimation of the target scale is obtained by the adaptive scale pool model. The experiment selects multiple video sequences for testing and compares the proposed algorithm with other target tracking methods. The experimental results show that the average performance is better than the comparison method.

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