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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Zhang, Yinlong An, Haibo Ding, Xiaojian Liang, Wei Yuan, Mingze Ji, Chunyang Tan, Jindong Shenyang Institute of Automation Guangzhou Chinese Academy of Sciences Guangzhou511548 China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Fifth Electronic Instituteof MIIT Guangzhou510610 China Department of Mechanical Aerospace and Biomedical Engineering University of Tennessee KonxvilleTN37996 United States

ISBN: (纸本)9781728163215

Reliable fault detection of rotate vector (RV) reducer is of paramount importance for the long-term maintenance of high-precision industrial robots. This paper proposes a Hidden Markov Model (HMM) based RV reducer fault detection using Acoustic Emission (AE) measurements. Compared with the conventional faults from the common rotating machinery (such as bearings and gears), the fault from the RV reducer is more complicated and undetectable due to its inherent inline and two-stage meshing structure. To this end, this work modifies the HMM model by taking into account not only the current observations and previous states, but also the subsequent series of observations within the posteriori probability framework. Through this way, the random and unknown disturbance, which is common in the industrial scenarios, could be reduced. Besides, the HMM is also applied to separate the AE signal bulks within one cycle that has 39 subcycles, which is a critical step for AE signal pre-processings. The proposed method has been evaluated on our collected AE signal dataset from the RV reducer in the industrial robotic platform. The experimental results and analysis validate that the proposed HMM based RV Reducer fault detection model can reliably and accurately detect reducer faults. © 2019 IEEE.

关键词： Hidden Markov models

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A new modified repetitive control system design based on T-S fuzzy model 8

A new modified repetitive control system design based on T-S...

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8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Applications, ISCIIA and ITCA 2018

作者： Zhang, Manli Wu, Min Chen, Luefeng Yu, Pan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Department of Electrical and Electronic Engineering Chiba University Chiba263-8522 Japan

— A new modified repetitive control strategy based on the Takagi-Sugeno fuzzy model is presented for an affine nonlinear system to track a periodic reference and reject a periodic disturbance. Then, a parallel distributed compensation control strategy is developed for the fuzzy repetitive system. Further, taking advantage of the control action during a period and the learning action between periods, a two-dimensional model is established for the closed-loop control system. A sufficient condition in the form of a set of linear matrix inequalities is derived to guarantee the robust asymptotic stability of the closed-loop control system. Simulation results demonstrate the validity of the method. A comparison with conventional modified repetitive control also shows the superiority of the developed method. © ISCIIA and ITCA 2018 - 8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Application.

关键词： Linear matrix inequalities

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control of Wall Mounting Robot

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IFAC-PapersOnLine 2017年第1期50卷 5648-5653页

作者： Sloth C. Pedersen R. Department of Electronic Systems Automation and Control Aalborg University Denmark

This paper presents a method for designing controllers for trajectory tracking with actuator constraints. In particular, we consider a joystick-controlled wall mounting robot called WallMo. In contrast to previous works, a model-free approach is taken to the control problem, where the path parameter for the trajectory is adapted online. We demonstrate the method on a dynamic model of WallMo using predefined motion primitives, i.e. we consider path-constrained trajectory generation. It is seen that the control scheme results in improved trajectory tracking. © 2017

关键词： Motion control systems Robotics technology

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Industrial Robot Rotate Vector Reducer Fault Detection Based on Hidden Markov Models

Industrial Robot Rotate Vector Reducer Fault Detection Based...

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IEEE International Conference on Robotics and Biomimetics

作者： Yinlong Zhang Haibo An Xiaojian Ding Wei Liang Mingze Yuan Chunyang Ji Jindong Tan Chinese Academy of Sciences Shenyang Institute of Automation Guangzhou Guangzhou China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Fifth Electronic Instituteof MIIT Guangzhou China Department of Mechanical University of Tennessee Konxville TN USA

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Model reduction of linear hybrid systems

arXiv

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arXiv 2020年

作者： Gosea, Ion Victor Petreczky, Mihaly Leth, John Wisniewski, Rafael Antoulas, Athanasios C. Group Max Planck Institute for Dynamics of Complex Technical Systems Sandtorstrasse 1 Magdeburg39106 Germany UMR CNRS 9189 CNRS Ecole Centrale de Lille France Department of Electronic Systems Automation and Control Aalborg University Fredrik Bajers Vej 7C Aalborg Denmark Department of Electrical and Computer Engineering Rice University 6100 Main St MS-366 HoustonTX77005 United States DRI Group Max Planck Institute for Dynamics of Complex Technical Systems Sandtorstrasse 1 Magdeburg39106 Germany Baylor College of Medicine 1 Baylor Plaza HoustonTX77030 United States

The paper proposes a model reduction algorithm for linear hybrid systems, i.e., hybrid systems with externally induced discrete events, with linear continuous subsystems, and linear reset maps. The model reduction algorithm is based on balanced truncation. Moreover, the paper also proves an analytical error bound for the difference between the input-output behaviors of the original and the reduced order model. This error bound is formulated in terms of singular values of the Gramians used for model reduction. Copyright © 2020, The Authors. All rights reserved.

关键词： Linear systems

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A study on rotate vector reducer performance degradation based on acoustic emission techniques

A study on rotate vector reducer performance degradation bas...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： An, Haibo Liang, Wei Ding, Xiaojian Zhang, Yinlong Tan, Jindong State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Shenyang Institute of Automation Guangzhou Chinese Academy of Sciences Guangzhou511548 China Fifth Electronic Institute of MIIT Guangzhou510610 China Department of Mechanical Aerospace and Biomedical Engineering University of Tennessee KonxvilleTN37996 United States

ISBN: (纸本)9781728163215

This paper presents a performance degradation analysis for rotate vector (RV) reducer using acoustic emission (AE) techniques. Unlike the AE signals from fixed gear reducer that are steady and have unchanged route, the AE signals from RV reducer have variant propagation paths and strengths. This work investigates the kinematics model using AE techniques to solve the inherent issues of RV reducer performance degradation analysis, such as signal variabilities and inappropriate thresholds. Firstly, the propagation path of AE signals within the crankshaft is developed. Secondly, the attenuation trend of AE signals is exponentially formulated based on the corresponding propagation curve. The proposed method has been evaluated on the developed RV reducer platform. AE signals were collected under various working conditions, i.e., four abrasion states with eight types of loads and five rotation speeds. The experimental analysis on typical parameters (e.g., signal energies) proves the effectiveness and accuracy of the developed method based on AE techniques. © 2019 IEEE.

关键词： Crankshafts

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An Online Approach to Physical Watermark Design

arXiv

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arXiv 2019年

作者： Liu, Hanxiao Mo, Yilin Yan, Jiaqi Xie, Lihua Johansson, Karl H. School of Electrical and Electronic Engineering Nanyang Technological University Singapore Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Department of Automation and BNRist Tsinghua University China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

This paper considers the problem of designing physical watermark signals in order to optimally detect possible replay attack in a linear time-invariant system, under the assumption that the system parameters are unknown and need to be identified online. We first provide a replay attack model, where an adversary replays the previous sensor data in order to fool the system. A physical watermarking scheme, which leverages a random control input as a watermark to detect the replay attack, is then introduced. The optimal watermark signal design problem is cast as an optimization problem, which aims to achieve the optimal trade-off between control performance and intrusion detection. An online watermarking design and system identification algorithm is provided to deal with systems with unknown parameters. We prove that the proposed algorithm converges to the optimal one and characterize the almost sure convergence rate. A numerical example and an industrial process example are provided to illustrate the effectiveness of the proposed strategy. Copyright © 2019, The Authors. All rights reserved.

关键词： Intrusion detection

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The Robust Exact Differentiator Toolbox: Improved Discrete-Time Realization 15

The Robust Exact Differentiator Toolbox: Improved Discrete-T...

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15th International Workshop on Variable Structure systems, VSS 2018

作者： Reichhartinger, M. Koch, S. Niederwieser, H. Spurgeon, S.K. Graz University of Technology Institute of Automation and Control Graz Austria Institute of Automation and Control Graz University of Technology Christian Doppler Laboratory for Model Based Control of Complex Test Bed Systems Graz Austria Information and Computer Engineering Graz University of Technology Graz Austria University College London Department of Electronic Electrical Engineering London United Kingdom

ISBN: (纸本)9781538664391

This paper presents a new release of A Robust Exact Differentiator Toolbox for Matlab®/Simulink® proposed in [1]. This release features a new discrete-time realization of the continuous-time robust exact differentiator. The implemented discretization scheme is less sensitive to gain overestimation and does not suffer from the discretization chattering effect. Hence, the single tuning parameter of the new version of the implemented differentiator is more intuitive to tune. Furthermore, it shows superior estimation performance in the case of large sampling times in comparison to the previous release. This is confirmed by the presented results obtained by numerical simulations and a real world application. © 2018 IEEE.

关键词： Simulink

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Incentivizing Strategy for Demand Response Aggregator Considering Market Entry Criterion: A Game Theoretical Approach

Incentivizing Strategy for Demand Response Aggregator Consid...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Mengmeng Yu Seung Ho Hong Xiongfeng Zhang Junhui Jiang Xuefei Huang Min Wei Kai Wang Wei Liang Department of Electronic Engineering Hanyang University Ansan Korea National Industrial IoT International Cooperation Base Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

This paper presents a novel incentivizing strategy for a demand response (DR) aggregator to participate in an intra-day market organized by the grid operator (GO). By taking the market entry criterion into consideration, the proposed incentivizing strategy is able to help the aggregator determine the optimal incentive for each customer based on their identified characteristics or preferences. The hierarchical decision making procedure between the aggregator and customers is casted into a Stackelberg game. In accordance, an optimal incentivizing strategy can be ascertained for the aggregator, which further helps the aggregator elicit optimal load reductions from enrolled customers meanwhile maximizing its potential profit. Simulation results show that the proposed incentivizing strategy is effective in helping the aggregator determine optimal incentive for each customer in face of different external factors.

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Modal regression based structured low-rank matrix recovery for multi-view learning

arXiv

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arXiv 2020年

作者： Xu, Jiamiao Wang, Fangzhao Peng, Qinmu You, Xinge Wang, Shuo Jing, Xiao-Yuan Philip Chen, C.L. School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute China State Key Laboratory of Software Engineering School of Computer Wuhan University China Department of Computer and Information Science Faculty of Science and Technology University of Macau 99999 China Dalian Maritime University Dalian116026 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Low-rank Multi-view Subspace Learning (LMvSL) has shown great potential in cross-view classification in recent years. Despite their empirical success, existing LMvSL based methods are incapable of well handling view discrepancy and discriminancy simultaneously, which thus leads to the performance degradation when there is a large discrepancy among multi-view data. To circumvent this drawback, motivated by the block-diagonal representation learning, we propose Structured Low-rank Matrix Recovery (SLMR), a unique method of effectively removing view discrepancy and improving discriminancy through the recovery of structured low-rank matrix. Furthermore, recent low-rank modeling provides a satisfactory solution to address data contaminated by predefined assumptions of noise distribution, such as Gaussian or Laplacian distribution. However, these models are not practical since complicated noise in practice may violate those assumptions and the distribution is generally unknown in advance. To alleviate such limitation, modal regression is elegantly incorporated into the framework of SLMR (term it MR-SLMR). Different from previous LMvSL based methods, our MR-SLMR can handle any zero-mode noise variable that contains a wide range of noise, such as Gaussian noise, random noise and outliers. The alternating direction method of multipliers (ADMM) framework and half-quadratic theory are used to efficiently optimize MR-SLMR. Experimental results on four public databases demonstrate the superiority of MR-SLMR and its robustness to complicated noise. Copyright © 2020, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

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