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American control Conference

作者： Xianlin Zeng Peng Yi Yiguang Hong Key Laboratory of Systems and Control Institute of Systems Science Chinese Academy of Sciences Beijing 100190 China Department of Electrical and Computer Engineering University of Toronto Canada

ISBN: (纸本)9781509045839

This paper proposes a novel distributed continuous-time algorithm for the resource allocation problem with uncertainty parameters, which is a robust optimization problem. The considered objective function is the sum of local convex functions assigned to agents in a multi-agent network, with private set constraints and global inequality constraint involving uncertain parameters. Each agent only knows its local objective function, local constraint set, and neighbor information. We propose a novel continuous-time distributed subgradient-based algorithm with projected output feedback to solve the optimization problem. Finally, we show that the algorithm is able to find the optimal solution under some mild conditions.

关键词： Output feedback Resource utilization inequality constraint algorithms management of resources Constraint Set Objective function NETWORKING AGENT Convex function Distribute Agents optimal solution

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On active decoupling control for horizontal-lateral direction of hypersonic flight based on HIFOO 21

On active decoupling control for horizontal-lateral directio...

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21st AIAA International Space Planes and Hypersonics Technologies Conference, Hypersonics 2017

作者： Ma, Shunjian Zhu, Kai Sun, Mingwei Wang, Zenghui Chen, Zengqiang Dept. of Automation and Intelligent Science Nankai University College of Computer and Control Engineering Tianjin300350 China Beijing Aerospace Technology Institute Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Beijing Aerospace Technology Institute Beijing100074 China Department of Electrical and Mining Engineering University of South Africa FL1710 South Africa

ISBN: (数字)9781624104633

ISBN: (纸本)9781624104633

Nowadays, hypersonic flight vehicles are widely studied. Since their high nonlinearity, strong coupling and uncertain factors, the conventional three-channel independent control design method is often unable to work well. In this paper, an active disturbance rejection controller (ADRC) is utilized to cancel internal uncertainties and exogenous disturbances for longitudinal dynamics. Then, the MIMO robust controller is obtained by choosing proper sensitivity functions and weighting functions to reduce horizontal-lateral direction coupling. The conventional H robust controllor is high-order, which is difficult for practitioners to implement. With frequency transformation, both ADRC for the longitudinal dynamics and MIMO robust controller for the horizontal-lateral dynamics are reformed into the static output feedback structure to reduce the high order of controller. Finally, all parameters in the controllers can be optimized by HIFOO (H-Infinity Fixed Order Optimization). The Winged-Cone, a 6-freedom NASA hypersonic vehicle model, is used as a benchmark, and Monte Carlo simulations demonstrate the effectiveness of the proposed method. © 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： controllers

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Data based reconstruction of complex multiplex networks

arXiv

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arXiv 2018年

作者： Ma, Chuang Chen, Han-Shuang Li, Xiang Lai, Ying-Cheng Zhang, Hai-Feng School of Mathematical Science Anhui University Hefei230601 China School of Physics and Material Science Anhui University Hefei230601 China Adaptive Networks and Control Laboratory Department of Electronic Engineering Center of Smart Networks and Systems School of Information Science and Engineering Fudan University Shanghai200433 China School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Department of Communication Engineering North University of China Taiyuan Shanxi030051 China

It has been recognized that many complex dynamical systems in the real world require a description in terms of multiplex networks, where a set of common, mutually connected nodes belong to distinct network layers and play a different role in each layer. In spite of recent progress towards data based inference of single-layer networks, to reconstruct complex systems with a multiplex structure remains largely open. We articulate a mean-field based maximum likelihood estimation framework to solve this outstanding and challenging problem. We demonstrate the power of the reconstruction framework and characterize its performance using binary time series from a class of prototypical duplex network systems that host two distinct types of spreading dynamics. In addition to validating the framework using synthetic and real-world multiplex networks, we carry out a detailed analysis to elucidate the impacts of structural and dynamical parameters as well as noise on the reconstruction accuracy and robustness. Copyright © 2018, The Authors. All rights reserved.

关键词： Network layers

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Fault diagnosis for multi-energy flows of energy internet: Framework and prospects

Fault diagnosis for multi-energy flows of energy internet: F...

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2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017

作者： Wang, Tao Wang, Jun Fan, Zhennan Wei, Xiaoguang Zang, Tianlei Pérez-Jiménez, Mario J. Huang, Tao School of Electrical Engineering and Electronic Information Sichuan Province Key Laboratory of Power Electronics Energy-saving Technologies and Equipment Key Laboratory of Fluid and Power Machinery Ministry of Education Xihua University Chengdu China School of Electrical Engineering Southwest Jiaotong University Chengdu China State Key Laboratory of Security Control and Simulation of Power Systems and Large Scale Generation Department of Electrical Engineering Tsinghua University Beijing China Research Groupon Natural Computing Department of Computer Science and Artificial Intelligence University of Sevilla Sevilla Spain Department of Energy Politecnico di Torino Torino Italy

ISBN: (纸本)9781538614273

Energy Internet (EI) is an inevitable development trend of energy systems under the background of technology development, environmental pressure and energy transition. Multi-energy flow coupling is one of the key characteristics of the EI, which enhances the interoperability of different types of energy flows while consequently increases the probability of cascading failures. Therefore it is of great significance to study the multi-energy flow fault diagnosis of the EI to ensure its safe and stable operation as well as the continuous energy supply. This paper introduces the concept of multi-energy flow cascading fault of the EI for the first time. The energy internet framework for multi-energy flow cascading fault diagnosis is firstly proposed, and then characteristics of various energy networks in the EI are analyzed from the perspective of fault diagnosis. Finally, future research prospects are discussed. © 2017 IEEE.

关键词： Failure analysis

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Deep EndoVO: A recurrent convolutional neural network (RCNN) based visual odometry approach for endoscopic capsule robots

arXiv

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arXiv 2017年

作者： Turan, Mehmet Almalioglu, Yasin Araujo, Helder Konukoglu, Ender Sitti, Metin Physical Intelligence Department Max Planck Institute for Intelligent Systems Germany Computer Engineering Department Bogazici Univesity Turkey Institute for Systems and Robotics Universidade de Coimbra Portugal Computer Vision Laboratory Department of Information Technology and Electrical Engineering ETH Zurich Switzerland

Ingestible wireless capsule endoscopy is an emerging minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies. Medical device companies and many research groups have recently made substantial progresses in converting passive capsule endoscopes to active capsule robots, enabling more accurate, precise, and intuitive detection of the location and size of the diseased areas. Since a reliable real time pose estimation functionality is crucial for actively controlled endoscopic capsule robots, in this study, we propose a monocular visual odometry (VO) method for endoscopic capsule robot operations. Our method lies on the application of the deep Recurrent Convolutional Neural Networks (RCNNs) for the visual odometry task, where Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are used for the feature extraction and inference of dynamics across the frames, respectively. Detailed analyses and evaluations made on a real pig stomach dataset proves that our system achieves high translational and rotational accuracies for different types of endoscopic capsule robot trajectories. Copyright © 2017, The Authors. All rights reserved.

关键词： Vision

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Full body human motion estimation on lie groups using 3D marker position measurements 16

Full body human motion estimation on lie groups using 3D mar...

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16th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2016

作者： Ćesić, Josip Joukov, Vladimir Petrović, Ivan Kulić, Dana University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Autonomous Systems and Mobile Robotics Croatia University of Waterloo Department of Electrical and Computer Engineering Adaptive Systems Laboratory Canada

ISBN: (纸本)9781509047185

This paper proposes a new algorithm for full body human motion estimation using 3D marker position measurements. The joints are represented with Lie group members, including special orthogonal groups SO(2) and SO(3), and a special euclidean group SE(3). We employ the Lie Group Extended Kalman Filter (LG-EKF) for stochastic inference on groups, thus explicitly accounting for the non-euclidean geometry of the state space, and provide the derivation of the LG-EKF recursion for articulated motion estimation. We evaluate the performance of the proposed algorithm in both simulation and on real-world motion capture data, comparing it with the Euler angles based EKF. The results show that the proposed filter significantly outperforms the Euler angles based EKF, since it estimates human motion more accurately and is not affected by gimbal lock. © 2016 IEEE.

关键词： Extended Kalman filters

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On ADRC for non-minimum phase systems： canonical form selection and stability conditions

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control Theory and Technology 2016年第3期14卷 199-208页

作者： Wenchao XUE Yi HUANG Zhiqiang GAO Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China Department of Electrical and Computer Engineering Cleveland State University Cleveland Ohio 44175 U.S.A.

Active disturbance rejection control （ADRC）, as proposed by Prof. Jingqing Han, reduces first the plant dynamics to its canonical form, normally in the form of cascade integrators, for which the standard controller can be employed to meet the design specifications. This paper concerns with the selection of the canonical form for non-minimum phase systems. In particular, it is shown that, by employing the well known controllable canonical form, the uncertainties of such systems can be divided into two terms in the state space model, one in the control channel and the other in the output channel. The necessary and sufficient condition is obtained for the stability of the closed-loop system with the proposed canonical form and ADRC. Also, by showing the necessity of the detectability of the extended system as well as certain information of the system-s ＂zeros＂, we present the fundamental guidelines of design ADRC for non-minimum phase uncertain systems.

关键词： Active disturbance rejection control （ADRC） extended state observer （ESO） rejector uncertain systems non-minimum phase

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Emotional metaheuristics for in-situ foraging using sensor constrained robot swarms

arXiv

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arXiv 2017年

作者： Kumar, Eshwaran Vijaya Ghose, Debasish Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States Guidance Control and Decision Systems Laboratory Department of Aerospace Engineering Indian Institute of Science Bangalore560012 India

We present a new social animal inspired emotional swarm intelligence technique. This technique is used to solve a variant of the popular collective robots problem called foraging. We show with a simulation study how simple interaction rules based on sensations like hunger and loneliness can lead to globally coherent emergent behavior which allows sensor constrained robots to solve the given problem. Copyright © 2017, The Authors. All rights reserved.

关键词： Intelligent robots

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Adaptive Dynamic Programming and Optimal Stabilization for Linear systems with Time-varying Uncertainty

Adaptive Dynamic Programming and Optimal Stabilization for L...

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Asian control Conference

作者： Meng Zhang Ming-Gang Gan Jie Chen Zhong-Ping Jiang State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China Department of Electrical and Computer Engineering New York University Brooklyn NY

ISBN: (纸本)9781509015740;9781509015733

This paper focuses on the optimal control of continuous-time linear time-varying uncertain systems with completely unknown internal dynamics and proposes a novel approach which leads to an optimal controller with guaranteed stability. A model-free algorithm of adaptive dynamic programming is employed to deal with the uncertainty of system parameters, yielding an optimal feedback controller for the system subject to a predefined cost. Then the stability of the system in time-varying uncertain situation which may undergo parameter changes or jumps is analyzed from the perspective of finite-time stability. On the basis of these results, a switching control strategy is presented to ensure the stability of the time-varying uncertain system with desired optimality properties in the long run. The effectiveness of the strategy is verified by simulations on a DC torque motor servo system.

关键词： Time-varying systems Stability analysis Symmetric matrices Asymptotic stability Uncertainty Optimal control

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Rewinding strategy aided by FEA as a solution to increase efficiency of industrial motors 22

Rewinding strategy aided by FEA as a solution to increase ef...

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22nd International Conference on electrical Machines, ICEM 2016

作者： Aguiar, V.P.B. Pontes, R.S.T. Neto, T. R. Fernandes Ferreira, F.J.T.E. Motor Driven Systems Laboratory Department of Electrical Engineering Federal University of Ceará Fortaleza CE60440554 Brazil Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Coimbra Portugal

ISBN: (纸本)9781509025381

This paper presents a proper model and methodology to improve the efficiency class of a squirrel-cage induction motor during rewinding. The modeling approach is based on the finite element model, i.e. two-dimensional model coupled with the rotor equivalent circuit (first stage) and the stator equivalent circuit (second stage). Results obtained with finite element analysis are compared with those obtained with analytical calculations. It is demonstrated that, during rewinding, if an improved winding configuration is used, efficiency gains can be obtained, allowing to improve the efficiency class of the motor, from IE2 to IE3, respecting the specified limits of NEMA & IEC performance indicators, namely, breakdown torque, locked-rotor torque, and locked-rotor current. In 79% of the simulated cases the efficiency gain allowed the studied motor to reach the IE3 class. © 2016 IEEE.

关键词： Frequency domain analysis

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