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arXiv 2019年

作者： Gou, Chao Shen, Tianyu Zheng, Wenbo Xue, Huadan Yu, Hui Ji, Qiang Jin, Zhengyu Wang, Fei-Yue School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou510275 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Radiology Peking Union Medical College Hospital Chinese Academy of Medical Sciences Peking Union Medical College Beijing100730 China School of Creative Technologies University of Portsmouth PortsmouthPO1 2DJ United Kingdom Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Qingdao Academy of Intelligent Industries Qingdao266000 China

Data-driven artificial intelligence technologies have made much progress in medical image analysis in the last decades. However, it still remains challenging due to its distinctive complexity of acquiring and annotating image data, extracting medical domain knowledge, and explaining the diagnostic decision for medical image analysis. In this paper, we propose a data-knowledge-driven framework termed as Parallel Medical Imaging (PMI) for intelligent medical image analysis based on the methodology of interactive ACP-based parallel intelligence. In the PMI framework, computational experiments with predictive learning in a data-driven way are conducted to extract medical knowledge for diagnostic decision support. Artificial imaging systems are introduced to select and prescriptively generate medical image data in a knowledge-driven way to utilize medical domain knowledge. Through the closed-loop optimization based on parallel execution, our proposed PMI framework can boost the generalization ability and alleviate the limitation of medical interpretation for diagnostic decisions. Furthermore, we illustrate the preliminary implementation of PMI method through the case studies of mammogram analysis and skin lesion image analysis. Experimental results on several public medical image datasets demonstrate the effectiveness of proposed PMI. © 2019, CC BY.

关键词： Medical imaging

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Stable walking of quadruped robot on unknown rough terrain

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Journal of Beijing Institute of Technology 2016年第4期25卷 463-472页

作者：何玉东王军政柯贤锋汪首坤 Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

Quadruped robot is considered to be the most practical locomotion machine to negotiate uneven terrain, and shows superb stability during static walking. To improve the ability to go over rough terrain, this paper is focused on the stable walking and balance control of quadruped robots. 24 kinds of walking gaits are analyzed in order to derive the most stable and smoothest walking gait. Considering the inefficiency to model a terrain by its specified appearance, a uniform terrain model is established and by means of kinematic analysis, a method to adjust the body posture and center of gravity （COG） height is presented. Simulations demonstrate the effectiveness of the proposed meth- od and the improvement of the adaptation of quadruped robots on rough terrain.

关键词： quadruped robot unknown rough terrain walking gait body posture body center ofgravity （COG）

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Dynamic state Estimation Using Event-Trigger Master-Slave Nonlinear Filter for WAMS Applications

Dynamic State Estimation Using Event-Trigger Master-Slave No...

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Data Driven control and Learning systems (DDCLS)

作者： Qing Yuan Fengdi Zhang Hengheng Gong Luyu Li Sen Li Xiaozhong Liao Zhen Li Xiangdong Liu School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing P. R. China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing P. R. China Beijing Institute of Radio Measurement Beijing P. R. China

ISBN: (纸本)9781538626191

The real-time state estimation becomes greatly important with the wide application of phasor measurement unit (PMU) in distributed generation (DG) for wide-area measurement systems (WAMS). In view of estimation, particle filter (PF) is capable of providing the best performance but at the cost of heavy computation burden. Besides, the growing grid size sustainably boosts the amount of data communication from PMU, causing the congestion. An event-trigger master-slave nonlinear filter (ET-MSNF) is proposed to guarantee the estimation accuracy and get the communication bandwidth relieved. The local slave filter at the generator node carries out the local estimation and event-trigger strategy using unscented transformation, which is identical to the center slave. The master filter at the center is designed using Monte Carlo method to improve the center's estimation accuracy by the cooperation with the center slave. Such master-slave filtering structure can fully utilize the computation capability both at the center and node. Simulation on the standard IEEE 39-bus system verify the performance of ET-MSNF.

关键词： Generators Monte Carlo methods Phasor measurement units Master-slave Wide area measurements state estimation

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Adaptive robust controller for electric cylinder with fast parameter estimation based on modified lugre model

Adaptive robust controller for electric cylinder with fast p...

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第36届中国控制会议

作者： Duo yang Li Jun Zheng Wang Ren Jian Hao Shou Kun Wang Wei Shen Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

In this paper,the adaptive robust control（ARC） algorithm is proposed for tracking control of the electric cylinder *** to the analysis of the working principle of the electric cylinder servo system,the model of the system is established on the modified Lugre friction model,and single observer is designed for calculating friction as *** the ARC controller and adaptive law are designed for on-line parameters estimation,frictional compensation and the suppression external *** the Lyapunov approach,the stability of this system can be obtained in this *** simulation result shows that ARC can suppresses external disturbances effectively and realize real-time online parameter estimation.

关键词： adaptive robust control Lugre model parameter estimation

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Automatic design of hybrid optimizers based on particle swarm optimization and differential evolution 5

Automatic design of hybrid optimizers based on particle swar...

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

作者： Wang, Yipeng Xin, Bin School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing100081 China

Hybridization is termed as an efficient strategy to improve the performance of many optimizers, and the design of efficient hybrids for difficult optimization problems remains a challenging field. In this study, an automatic method is proposed to generate various hybrid optimizers based on particle swarm optimization and differential evolution for a given problem. Based on the unified framework for hybridization proposed in our recent work, the proposed method can provide plenty of hybrid optimizers for a specific problem with given parent optimizers. Besides, an approach which can provide the unified representation of different kinds of hybridization levels is developed. Moreover, all the generated hybrids are evaluated on the CEC2017 benchmark problems, and the results of the statistic analysis and the Wilcoxon's rank-sum tests demonstrate that the hybrid optimizer utilizing the hybridization strategy performs obviously better than the others on the test functions.

关键词： Particle swarm optimization (PSO)

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Algebraic Connectivity Estimation Based on Decentralized Inverse Power Iteration

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Asian Journal of control 2017年第2期19卷 805-812页

作者： Wei, Yue Fang, Hao Chen, Jie Xin, Bin School of Automation Beijing Institute of Technology Beijing 100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 China

In this work, we propose a new scheme to estimate the algebraic connectivity of the graph describing the network topology of a multi-agent system. We consider network topologies modeled by undirected graphs. The main idea is to propose a new decentralized conjugate gradient algorithm and a decentralized compound inverse power iteration scheme. The matrix inversion computation in this scheme is replaced by solving the non-homogeneous linear equations relying on the proposed decentralized conjugate gradient algorithm. With this scheme, we can achieve a fast convergence rate in estimating the algebraic connectivity by setting the parameter μ properly. Simulation results demonstrate the effectiveness of the proposed scheme. © 2016 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd

关键词： Network topology

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A full-dq based adaptive virtual impedance compensation in virtual power frame for droop-controlled parallel inverters under unbalanced conditions

A full-dq based adaptive virtual impedance compensation in v...

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Annual Conference of Industrial Electronics Society

作者： Yuan Cao Zhen Li Zelun Lu Zhen Chen Xiangdong Liu School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing China

Distributed generation (DG) is connected through three-phase inverter to the microgrid. The virtual power based droop control can guarantee the pure decoupling between active and reactive power irrespective of low-voltage or high-voltage microgrid application if the line-impedance information is known in advance. However, unbalances are commonly existent in practice so that this conventional control fails in application due to the significant coupling between active and reactive power. To overcome this problem and further extend virtual power based method into unbalanced conditions, this paper proposes an improved virtual power decoupling technique using full-dq transformation, which is utilized to identify arbitrary unbalanced components under unbalanced conditions. The identified unbalances are further compensated as an virtual impedance so as to ensure the pure decoupling of active and reactive power in the virtual power frame. Finally, simulation results are provided to verify the effectiveness of the proposed method under unbalanced conditions.

关键词： Impedance Reactive power Inverters Microgrids Voltage control Frequency control Couplings

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Joint task management of sensor and weapon based on distributed management system

Joint task management of sensor and weapon based on distribu...

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Chinese control Conference (CCC)

作者： Zhang Mingyang Chen Chen Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing School of Automation Beijing Institute of Technology Beijing

ISBN: (纸本)9781538629185

In the modern war, many combat units combat collectively has become the main form. In the task management of the combat units, the calculation is large and the real-time requirement is high. To solve the problem better, a joint task management method of sensor and weapon based on distributed management system is proposed. Firstly, the distributed management system is constructed according to the target trajectory and the distribution of combat units. In the system, all the combat units are divided into several combinations, which only consist of a few combat units. As a result, the problem scale is reduced, and the real-time requirement of battlefield is met. Secondly, joint task management model of sensor and weapon is established. We consider time constraints and resource constraints to ensure the feasibility of the attack scheme, and consider the impact between sensor and weapon to achieve better combat effect. A discrete particle swarm optimization algorithm based on crossover strategy (CDPSO) is proposed to solve the model. The results show that the performance of the proposed algorithm is satisfactory in joint task management of sensor and weapon.

关键词： Weapons Distributed management Command and control systems Time factors Mathematical model Data processing Real-time systems

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A Modified System Model and its Application on SINS/GPS Integrated System

A Modified System Model and its Application on SINS/GPS Inte...

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IEEE International Conference on Cyber Technology in automation, control, and intelligent systems

作者： Xuan Xiao Xiang Guo Yuan Liang Chao Shi Songtian Shang Hong Hu School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

ISBN: (纸本)9781538604915

Kalman filter has been extensively applied in vast areas. However, the performance of Kalman filter rests on the accuracy of prior information such as model construction. In the integrated system of Strapdown Inertial Navigation System (SINS)/Global Positioning System (GPS), the model construction is affected by a certain error sources. The most significant one is computational errors, which are caused by improper reference frame and the absence of true values. To solve the problem, this paper presents a modified system model which reduce the impact of computational errors by selecting computational frame as reference coordinate frame and removing all true values. Simulation results have demonstrated that modified system model effectively improves the performance of Kalman filter in SINS/GPS integrated system.

关键词： Kalman filters systems modelling Integrated system strapdown inertial navigation system Error Sources Modified

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Small-scale intersection scan model for UGV in urban environment

Small-scale intersection scan model for UGV in urban environ...

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American control Conference (ACC)

作者： Yi Yang Hao Li Hao Zhu Ningyi Lyu Wenjie Song School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing Beijing CN School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

Intersection detection is a critical capacity for an Unmanned Ground Vehicle (UGV) to drive safely in structured urban environment. Large-scale intersections stamped on maps have plenty of features for detection while some unmapped small-scale urban intersections are hard to be identified. In this paper, we propose a novel intersection detection method conducted on the basis of Hidden Markov Model (HMM). This method is based on the intersection scan model to obtain the traversable directions to classify the intersection. The scan model is effective in dealing with both LIDAR and visual data. Combination of the scan model and the HMM can accurately estimate the traversable directions in consideration of both real-time and historic data. Results from simulations and real-world experiments have shown the functionality of the presented approach.

关键词： Hidden Markov models Roads Global Positioning System Three-dimensional displays Urban areas Laser radar Autonomous vehicles

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