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IEEE International Conference on robotics and automation (ICRA)

作者： Daniel J. Gonzalez H. Harry Asada Robotics Research Center in the Department of Electrical Engineering and Computer Science United States Military Academy West Point NY USA d’Arbeloff Laboratory for Information Systems and Technology in the Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA USA

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

The Extra Robotic Legs (XRL) system is a robotic augmentation worn by a human operator consisting of two articulated robot legs that walk with the operator and help bear a heavy backpack payload. It is desirable for the Human-XRL quadruped system to walk with the rear legs lead the front by 25% of the gait period, minimizing the energy lost from foot impacts while maximizing balance stability. Unlike quadrupedal robots, the XRL cannot command the human's limbs to coordinate quadrupedal locomotion. Using a pair of Rimless Wheel models, it is shown that the systems coupled with a spring and damper converge to the desired 25% phase difference. A Poincaré return map was generated using numerical simulation to examine the convergence properties to different coupler design parameters, and initial conditions. The Dynamically Coupled Double Rimless Wheel system was physically realized with a spring and dashpot chosen from the theoretical results, and initial experiments indicate that the desired synchronization properties may be achieved within several steps using this set of passive components alone.

关键词： Legged locomotion Wheels Synchronization Couplers Robot kinematics

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Diagnosis of Oscillatory Transients Generated by Switching of Capacitor Banks using MPA

Diagnosis of Oscillatory Transients Generated by Switching o...

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2019 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT Latin America 2019

作者： Hoffmann, Alessandra B. G. Beuter, Carlos H. Pessoa, André L. S. Oleskovicz, Mario Alvarez Ferreira, Liz R. Department of Electrical and Computer Engineering EESC University of São Paulo São Carlos SP Brazil Itaipu Technological Park PTI Automation and Simulation of Electrical Systems Laboratory Lasse Foz do Iguaçu PR Brazil

ISBN: (纸本)9781538695678

An Oscillatory Transient (OT) can occur in any part of an Electric Power System (EPS), and its basic characteristics are short duration and considerable variances of the amplitude of the voltage and frequencies involved. Focusing on a medium voltage distribution system, one of the main causes of the OT is the capacitor bank switching, which should be differentiated from other situations that may occur. In this research, we present the diagnostic (identification and extraction of characteristics) of OTs generated by the switching of capacitor banks by applying the Matching Pursuit Algorithm (MPA), that is based on a structured data dictionary. The Golden Search (GS) was used to find the characteristic parameters of the OT. The adopted methodology provided a sensible improvement in the search of the parameters, where the number of iterations was reduced and the estimations were stable. Sensitivity tests of the obtained parameters indicated their relevance for the data dictionary that was used. Based on this approach, it was possible to identify the amplitude (instantaneous value) of the OT as well as its duration. The use of the MPA enables researches with diverse signals, where the concern may be linked to the need to identify the origin of the OT observed on a particular EPS. This analysis, for example, can support areas related to power quality and also protection of electrical power systems. © 2019 IEEE.

关键词： Electric power system protection

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Analysis of Harmonic and Interharmonic Components by Using an Improved Recursive Algorithm

Analysis of Harmonic and Interharmonic Components by Using a...

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2019 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT Latin America 2019

作者： Alvarez Ferreira, Liz R. Beuter, Carlos H. Hoffmann, Alessandra B. G. Pessoa, André L. S. Oleskovicz, Mário Itaipu Technological Park PTI Automation and Simulation of Electrical Systems Laboratory Lasse Foz do Iguaçu PR Brazil Department of Electrical and Computer Engineering EESC University of São Paulo São Carlos SP Brazil

ISBN: (纸本)9781538695678

Spectral leakage is a phenomenon that is considered a problem and occurs when Discrete Fourier Transform (DFT) is used as a tool to identify harmonic components in a frequency spectrum of electric signals, which contains asynchronous sampling or interharmonic components. It may cause errors in presented results that may affect signal analysis. Therefore, application of a technique or combination of techniques is necessary, in order to better characterize harmonic and interharmonic components and enable extraction of their representative factors. In this context, this research aims at estimating frequencies and amplitudes interharmonic present in a signal. This paper proposes a new approach method, based on Group-harmonic Power Minimizing (GPM) and Recursive Group-harmonic Power Minimizing (RGPM) algorithms. The new proposal establishes an identification threshold and is more accurate when compared to the IEC 61000-4-7 standard, recommended for this kind of problem as it detects not only the 5 Hz minimal spectral resolution, but also frequency components of intermediate location with noise. Results indicate a satisfactory characterization of predominant interharmonic components, with low deviation level, both in range and in associated frequency. © 2019 IEEE.

关键词： Discrete Fourier transforms

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Blockchain Technology Based Decentralized Energy Trading for Multiple-Microgrid systems 3

Blockchain Technology Based Decentralized Energy Trading for...

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3rd IEEE Conference on Energy Internet and Energy System Integration, EI2 2019

作者： Li, Ting Zhang, Wei Chen, Ning Qian, Minhui Xu, Ying School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China State Key Laboratory of Operation and Control of Renewable Energy Storage Systems China EPRI Nanjing China University of Central Florida Department of Electrical Engineering Computer Science Orlando United States

ISBN: (纸本)9781728131375

With the emerging technology for distributed generation and urge of improving quality of service of power supply for energy users, more and more Microgrids (MGs) are integrated into the distributed networks to serve the energy users. These Microgrids are gradually formulating a Multi-Microgrid System (MMGS, Multi-Microgrid System), which will play an important role for the future energy supply. Building a centralized control center not only increases the expense of investment, but also brings the issues of maintaining fairness among energy users. To address these problems, this paper proposes a peer-to-peer method for energy trading of MMGS, based on the idea of decentralized trading. An auction-based trading mechanism suitable for peer-to-peer energy trading is proposed first. For this mechanism, the MGs firstly declare their energy buying bids or selling quotations. Then, the market-clearing price is determined by using a unified weight clearing algorithm in a decentralized manner. By applying the edge technology of Blockchain, the implementation of the proposed peer-to-peer energy trading method, including the architecture, procedures, security check, etc., is also discussed. The proposed Blockchain-based energy trading platform can realize the decentralized and autonomous energy trading of MGs within an MMGS. A case study with an MMGS with 10 MG units is provided to demonstrate the effectiveness of the proposed approach. © 2019 IEEE.

关键词： Blockchain

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A Filtering Approach Based on MMAE for a SINS/CNS Integrated Navigation System

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IEEE/CAA Journal of Automatica Sinica 2018年第6期5卷 1113-1120页

作者： Fangfang Zhao Cuiqiao Chen Wei He Shuzhi Sam Ge School of Computer Science and Engineering and Center for RoboticsUniversity of Electronic Science and Technology of ChinaChengdu 611731China School of Automation and Electrical Engineering University of Science and Technology of BeijingBeijing 100083China Social Robotics Laboratory Interactive Digital Media Instituteand Department of Electrical and Computer EngineeringNational University of SingaporeSingapore 117576Singapore Singapore 117576 Singapore

This paper explores multiple model adaptive estimation(MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter— multiple model adaptive estimation unscented Kalman filter(MMAE-UKF) rather than conventional Kalman filter methods,like the extended Kalman filter(EKF) and the unscented Kalman filter(UKF). UKF is used as a subfilter to obtain the system state estimate in the MMAE method. Single model filter has poor adaptability with uncertain or unknown system parameters,which the improved filtering method can overcome. Meanwhile,this algorithm is used for integrated navigation system of strapdown inertial navigation system(SINS) and celestial navigation system(CNS) by a ballistic missile's motion. The simulation results indicate that the proposed filtering algorithm has better navigation precision, can achieve optimal estimation of system state, and can be more flexible at the cost of increased computational burden.

关键词： Celestial navigation integrated navigation multiple model adaptive estimation unscented Kalman filter （MMAEUKF） strap-down inertial navigation

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Learning data-adaptive non-parametric kernels

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2020年第1期21卷 8590-8628页

作者： Fanghui Liu Xiaolin Huang Chen Gong Jie Yang Li Li Department of Electrical Engineering ESAT-STADIUS KU Leuven Belgium Institute of Image Processing and Pattern Recognition Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China PCA Lab Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology China and Department of Computing Hong Kong Polytechnic University Hong Kong SAR China Department of Automation BNRist Tsinghua University China

In this paper, we propose a data-adaptive non-parametric kernel learning framework in margin based kernel methods. In model formulation, given an initial kernel matrix, a data-adaptive matrix with two constraints is imposed in an entry-wise scheme. Learning this data-adaptive matrix in a formulation-free strategy enlarges the margin between classes and thus improves the model flexibility. The introduced two constraints are imposed either exactly (on small data sets) or approximately (on large data sets) in our model, which provides a controllable trade-off between model flexibility and complexity with theoretical demonstration. In algorithm optimization, the objective function of our learning framework is proven to be gradient-Lipschitz continuous. Thereby, kernel and classifier/regressor learning can be efficiently optimized in a unified framework via Nesterov's acceleration. For the scalability issue, we study a decomposition-based approach to our model in the large sample case. The effectiveness of this approximation is illustrated by both empirical studies and theoretical guarantees. Experimental results on various classification and regression benchmark data sets demonstrate that our non-parametric kernel learning framework achieves good performance when compared with other representative kernel learning based algorithms.

关键词： support vector machines non-parametric kernel learning gradient-Lipschitz continuous

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Performance Evaluation of Faults in a Photovoltaic Array Based on V-I and V-P Characteristic Curve

Performance Evaluation of Faults in a Photovoltaic Array Bas...

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International Conference on Measuring Technology and Mechatronics automation, ICMTMA

作者： Ehtisham Lodhi Wang Lina Yang Pu M. Yaqoob Javed Zeeshan Lodhi Jiao Zhijie Usman Javed School of Automation Science and Electrical Engineering Beihang University Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering COMSATS University Islamabad Lahore Pakistan Department of Electrical and Computer Engineering COMSATS University Islamabad Abbottabad Pakistan The Guo China-US photonics Lab Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences Changchun China

ISBN: (数字)9781728170817

ISBN: (纸本)9781728170824

The prediction and forecasting of faults occurring in photovoltaic (PV) system is one of the important aspect to escalate the reliability, output power generation, proficiency, lifetime and effectiveness of overall system. In this article, the behavior of PV array is studied under various faulty circumstances and new approach has offered for the better performance assessment of PV array. This approach is established on the analysis of peculiarities displayed by voltage power (V-P) and voltage-current (V-I) characteristics curves of PV array under different faulty conditions. The proposed technique can be used to identify and classify the five common faults in PV system. These progressive faults (includes open circuit, line-to-line, partial shading, degradation and bridging faults) have been occurred at the basic components of PV cell and at the connection point between PV modules. The characteristic curves under normal and faulty conditions have been compared by utilizing Matlab/Simulink environment. Hence, the suggested method can be utilized to determine the important fact about the health PV array.

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In-flight positional and energy use data set of a DJI matrice 100 quadcopter for small package delivery

arXiv

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arXiv 2021年

作者： Rodrigues, Thiago A. Patrikar, Jay Choudhry, Arnav Feldgoise, Jacob Arcot, Vaibhav Gahlaut, Aradhana Lau, Sophia Moon, Brady Wagner, Bastian Matthews, H. Scott Scherer, Sebastian Samaras, Constantine Department of Civil and Environmental Engineering Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213 United States Robotics Institute Carnegie Mellon University 5000 Forbes Avenue Pittsburgh15213 United States Dietrich College of Humanities and Social Sciences Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213 United States General Robotics Automation Sensing and Perception Laboratory University of Pennsylvania PhiladelphiaPA19104 United States Department of Electrical and Computer Engineering Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213 United States Ravensburg Germany

We autonomously direct a small quadcopter package delivery Uncrewed Aerial Vehicle (UAV) or "drone" to take off, fly a specified route, and land for a total of 209 flights while varying a set of operational parameters. The vehicle was equipped with onboard sensors, including GPS, IMU, voltage and current sensors, and an ultrasonic anemometer, to collect high-resolution data on the inertial states, wind speed, and power consumption. Operational parameters, such as commanded ground speed, payload, and cruise altitude, are varied for each flight. This large data set has a total flight time of 10 hours and 45 minutes and was collected from April to October of 2019 covering a total distance of approximately 65 kilometers. The data collected were validated by comparing flights with similar operational parameters. We believe these data will be of great interest to the research and industrial communities, who can use the data to improve UAV designs, safety, and energy efficiency, as well as advance the physical understanding of in-flight operations for package delivery drones. Copyright © 2021, The Authors. All rights reserved.

关键词： Industrial research

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Preface

Synthesis Lectures on Computer Vision

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Synthesis Lectures on computer Vision 2023年 Part F825卷 v-vi页

作者： Wan, Jun Escalera, Sergio Li, Stan Z. Guo, Guodong Escalante, Hugo Jair State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Mathematics and Informatics University of Barcelona and Computer Vision Center Barcelona Spain AI Lab Westlake University Hangzhou China Department of Computer Science and Electrical Engineering West Virginia University Morgantown China Department of Computer Science Instituto Nacional de Astrofísica Optica y Electrónica Puebla Mexico

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Passive Quadrupedal Gait Synchronization for Extra Robotic Legs Using a Dynamically Coupled Double Rimless Wheel Model

arXiv

引用

arXiv 2020年

作者： Gonzalez, Daniel J. Harry Asada, H. Robotics Research Center Department of Electrical Engineering and Computer Science United States Military Academy West PointNY10996 United States d’Arbeloff Laboratory for Information Systems and Technology Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States

The Extra Robotic Legs (XRL) system is a robotic augmentation worn by a human operator consisting of two articulated robot legs that walk with the operator and help bear a heavy backpack payload. It is desirable for the Human-XRL quadruped system to walk with the rear legs lead the front by 25% of the gait period, minimizing the energy lost from foot impacts while maximizing balance stability. Unlike quadrupedal robots, the XRL cannot command the human’s limbs to coordinate quadrupedal locomotion. Using a pair of Rimless Wheel models, it is shown that the systems coupled with a spring and damper converge to the desired 25% phase difference. A Poincaré return map was generated using numerical simulation to examine the convergence properties to different coupler design parameters, and initial conditions. The Dynamically Coupled Double Rimless Wheel system was physically realized with a spring and dashpot chosen from the theoretical results, and initial experiments indicate that the desired synchronization properties may be achieved within several steps using this set of passive components alone. Copyright © 2020, The Authors. All rights reserved.

关键词： Exoskeleton (robotics)

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