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Non-parametric modeling of double-link flexible robot manipulator based on NNARX model structure 19th

Non-parametric modeling of double-link flexible robot manipu...

19th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines, CLAWAR 2016

作者： Jamali, Annisa Mat Darus, Intan Zaurah Abdulhussain, Ali Tokhi, M.O. Automation and Control Laboratory Faculty of Mechanical Engineering Universiti Teknologi Malaysia SkudaiJohor81300 Malaysia Department of Automatic Control and System Engineering University of Sheffield United Kingdom

ISBN: (纸本)9789813149120

The double-link flexible robot manipulator (DLFR) is a highly non-linear system. The development of existing linear models involves a lot of assumptions and approximations in order to reduce the complex calculation. Due to that, this paper presents a non-linear Auto Regressive model with eXogenous inputs (NARX) for DLFR and neural network is used to predict the non-linear segment. Thus, NNARX structure is used to develop four separate model of double link flexible manipulator from torque input to hub angle and from torque input to end point accelerations of each link. The performance of NNARX models are validated via One Step Ahead, Mean Squared Error and correlation tests. © 2016, World Scientific Publishing Co. Pte Ltd. All rights reserved.

关键词： Flexible manipulators

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On-line Monitoring for Coal Low Heating Value in Coal-fired Power Plant Boiler Based on CM-LSSVM-PLS 35

On-line Monitoring for Coal Low Heating Value in Coal-fired ...

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第35届中国控制会议

作者： Shi Yuanhao Wang Jingcheng Ren Yifeng School of Computer Science and Control Engineering North University of China Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

ISBN: (纸本)9781509009107

A novel comprehensive real-time on-line calculation model of coal's Low Heating Value(LHV) in coal-fired boiler is presented in this ***,the training operational data is partitioned into several subsets by means of C-Means cluster ***,the Least Squares Support Vector Machine(LS-SVM) method is used to training the sub-models in each ***,the sub-models are combined into one model based on Partial Least Squares algorithm(PLS).The models' effectiveness is illustrated by the validation of online simulation in which the real operation data is *** result shows that it is potential to considerably fulfill not only the accuracy of online monitoring of LHV of the coal into the boiler,but also the real-time computations that are supplied by using indirect heat balance approach.

关键词： Coal-fired Power Plant Boiler Thermal Efficiency Low Heating Value C-Means Cluster LS-SVM PLS

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Day-Ahead Probabilistic Load Flow Analysis Considering Wind Power Forecast Error Correlation

Day-Ahead Probabilistic Load Flow Analysis Considering Wind ...

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The 9th Asia-Pacific Power and Energy engineering Conference (APPEEC 2017)

作者： Qiang Ding Chuancheng Zhang Jingyang Zhou Sai Dai Dan Xu Zhiqiang Luo Chengwei Zhai Power Automation Department China Electric Power Research Institute National Electric Power Dispatch and Control Center State Grid Corporation of China Electrical and Electronic Engineering College Zhejiang University

Short-term power flow analysis has a significant influence on day-ahead generation *** paper proposes a time series model and prediction error distribution model of wind power *** the consideration of wind speed and wind power output forecast error’s correlation,the probabilistic distributions of transmission line flows during tomorrow’s 96 time intervals are obtained using cumulants combined Gram-Charlier expansion *** probability density function and cumulative distribution function of transmission lines on each time interval could provide scheduling planners with more accurate and comprehensive *** in IEEE 39-bus system demonstrates effectiveness of the proposed model and algorithm.

关键词： Wind Power Time Series Model Forecast Error Distribution Forecast Error Correlation Probabilistic Load Flow Gram-Charlier Expansion

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A unified leader-follower scheme for mobile robots with uncalibrated on-board camera

A unified leader-follower scheme for mobile robots with unca...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Dejun Guo Hesheng Wang Weidong Chen Ming Liu Zeyang Xia Kam K. Leang DARC (Design Automation Robotics & Control) Lab University of Utah Robotics Center Salt Lake City Utah USA State Key Laboratory of Robotics and System (HIT) Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai China Department of Electronics and Computer Engineering Hong Kong University of Science and Technology Hong Kong China Institute of Biomedical and Health Engineering Chinese Academy of Sciences Shenzhen China

This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitable for both omnidirectional and perspective cameras, is proposed. The proposed approach avoids the need for accurate calibration of the extrinsic parameters of the omnidirectional camera as well as the intrinsic and extrinsic parameters of perspective camera. Additionally, the coefficients of the plane where the feature point moves relative to the camera frame can be uncertain. These uncertain constant parameters are estimated using an adaptive estimator. Uniform Semi-global Practical Asymptotic Stability (USPAS) of the system is shown using the Lyapunov approach. Experimental results are presented to demonstrate the effectiveness of the proposed control scheme.

关键词： Cameras Robot vision systems Kinematics Mobile robots Calibration automation

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Self-Awareness for Autonomous systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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Corrections to “Multi-Sensor Kalman Filtering With Intermittent Measurements” [Mar 18 797-804]

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IEEE Transactions on Automatic control 2018年第5期63卷 1545-1545页

作者： Chao Yang Jianying Zheng Xiaoqiang Ren Wen Yang Hongbo Shi Ling Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes Department of Automation East China University of Science and Technology Shanghai China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong

In the above technical note [ibid., vol. 63, no. 3, pp. 797–804, Mar. 2018], one of the author's names in the byline was misspelled and should have read as follows. Chao Yang, Jianying Zheng, Xiaoqiang Ren, Wen Y... 详细信息

关键词： Kalman filters Stochastic processes Sensor fusion Estimation error

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Cooperative robust output regulation for second-order nonlinear multi-agent systems with an unknown exosystem

Cooperative robust output regulation for second-order nonlin...

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IEEE Annual Conference on Decision and control

作者： Yi Dong Jie Chen Jie Huang Department of Automation Chinese University of Hong Kong Shatin N.T. Hong Kong State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Department of Mechanical and Automation Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong

The cooperative robust output regulation problem for a class of second-order nonlinear multi-agent systems with an exactly known exosystem has been studied recently. This paper further studies the same problem for a class of second-order nonlinear multi-agent systems subject to an unknown exosystem. We first show that the problem can be converted into the adaptive stabilization problem for a modified augmented system composed of the given multi-agent system and the distributed internal model. Due to the uncertain parameter in the exosystem, the augmented system is a nonlinear multi-input system with both dynamic and static uncertainties. By combining the adaptive control technique and the robust control technique, we solve our problem by a distributed adaptive robust state feedback controller.

关键词： Multi-agent systems Mathematical model Robustness Robust control automation electronic mail Nickel

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A Novel Adaptive Iterative Learning control via Data-driven Approach 35

A Novel Adaptive Iterative Learning Control via Data-driven ...

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第35届中国控制会议

作者： CHI Ronghu LIU Xiaohe HOU Zhongsheng CHIEN Chiang-Ju School of Automation & Electrical Engineering Qingdao University of Science & Technology Advanced Control Systems Lab School of Electronics & Information EngineeringBeijing Jiaotong University Department of Electronic Engineering Huafan University

ISBN: (纸本)9781509009107

A novel adaptive ILC approach is proposed for the control tasks of tracking iteration-varying desired trajectory. The output the controlled system is reformulated as a function of initial states and control inputs only. Then, an iteration-dynamical linearization is proposed for the controlled system. With the identical initial conditions, the system output is finally formulated by the input series only. Then, a learning control law is designed according to the iteration dynamical linearization, where the unknown system parameter is estimated by an iterative updating law. Simulation study confirms the efficiency and application of the proposed method.

关键词： Adaptive ILC Iteration-varying reference trajectory Dynamical linearization Data-driven control

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Modular Fault Diagnosis in Fixed-Block Railway Signaling systems

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IFAC-PapersOnLine 2016年第3期49卷 459-464页

作者： Durmus, Mustafa S. Ustoglu, lker Tsarev, Roman Y. Schwarz, Michael Electrical and Electronics Engineering Department Pamukkale University Denizli Turkey Control and Automation Engineering Department Yildiz Technical University Istanbul Turkey Institute of Space and Information Technology Siberian Federal University Krasnoyarsk Russia Computer Architecture and System Programming Kassel University Kassel Germany

The diagnosis of possible faults in railway signaling systems is an important issue to provide safe travel and transportation in railways. Signaling system designers have to consider the possible faults which may occur in railway field components both on the requirements preparation phase and on the development phase of the signaling system software or namely, the interlocking system. Although the diagnosis of different unobservable faults is relatively hard, especially for large scale railway fields, this complexity can be overcome by using the Discrete Event system (DES) based modular diagnosis approach which is explained in this paper. The main advantage of using such modular approach for fault diagnosis in fixed-block signaling systems is the inspection of the diagnosability of the whole system with respect to its subsystems (railway field components). In this study, the diagnosability of the railway field equipment and the whole system is also explained with a case study. © 2016

关键词： Fault detection Discrete event simulation Failure analysis Railroad signal systems Railroads Signaling Development phase Field components Field equipment Fixed block signaling Interlocking systems Modular approach Railway signaling systems Signaling systems

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Cracked Insulator Detection Based on R-FCN

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Journal of Physics: Conference Series 2018年第1期1069卷

作者： Shanjun Li Haomiao Zhou Guoyou Wang Xiuhong Zhu Lanfang Kong Zhaoyang Hu Department of Automation Huazhong University of Science and Technology Pattern recognition and Intelligent system 1037 Luoyu Road Wuhan 430074 China Department of Mechanical Science and Engineering Huazhong University of Science and Technology Mechanical and Electronic Engineering 1037 Luoyu Road Wuhan 430074 China

The insulator is an important component of the high voltage transmission line. Inspecting the defects of the insulator plays an important role in ensuring the normal operation of the transmission line. The cracked insulator is the most common type of insulator defects. The traditional cracked insulator detection method is to use image denoising, single insulator disk segmentation, and the adjacent European distance to locate and identify cracked insulators. Experiments show that the robustness of these methods is poor and their ability to adapt to the environment is not good. Image denoising and image segmentation with the complex environment in images are very difficult tasks. Based on the extracted insulator strings, we change the problem to cracked insulators detection under complex conditions with deep learning. Region-based Fully Convolutional Networks (R-FCN), a deep learning algorithm, is adopted. Firstly, we apply image correction and cropping to images with different sample sizes and directions. Secondly, we use image enhancement technology to expand the dataset of samples. Finally, sliding window and coordinate mapping method are used when testing samples. The experimental results after the algorithm being applied to UVA dataset show an average accuracy rate of 90.5%. The inspection time of a single image is less than 1 second, and the model proposed in this paper has strong robustness and environmental adaptability.

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