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H∞ state estimation for discrete time-delayed stochastic genetic regulatory networks with known sojourn probabilities 23

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H∞ state estimation for discrete time-delayed stochastic ge...

23rd IEEE International Conference on automation and Computing, ICAC 2017

作者： Wan, Xiongbo Wang, Zidong Ren, Chuanyu School of Automation China University of Geosciences Wuhan Hubei430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China Department of Computer Science Brunel University London Uxbridge MiddlesexUB8 3PH United Kingdom

ISBN: (纸本)9780701702618

This paper investigates the problem of H∞ state estimation for discrete-time stochastic genetic regulatory networks (GRNs) with switching parameters, time-varying delays, and exogenous disturbances. A new discrete-time stochastic GRN model with switching parameters is proposed by assuming that the sojourn probability of each subsystem of the GRN under consideration is known. By using the stochastic analysis approach, sufficient conditions are derived under which the augmented estimation error system is stochastically stable and satisfies a prescribed H∞ disturbance attenuation level γ. The gain matrices of the desired state estimator can be obtained by solving a matrix inequality. A numerical example is given to illustrate the effectiveness of the designed state estimator. © 2017 Chinese automation and Computing Society in the UK - CACSUK.

关键词： State estimation

Pid2018 benchmark challenge: Multi-objective stochastic optimization algorithm

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arXiv 2018年

作者： Ates, Abdullah Yuan, Jie Dehghan, Sina Zhao, Yang Yeroglu, Celaleddin Chen, YangQuan Inonu University Computer Engineering Department Malatya44280 Turkey School of Automation Southeast University Nanjing210096 China UC Merced Mechanical Engineering Departments MESA Lab MercedCA95301 United States School of Control Science and Engineering Shandong University Jinan250061 China

This paper presents a multi-objective stochastic optimization method for tuning of the controller parameters of Refrigeration Systems based on Vapour Compression. Stochastic Multi Parameter Divergence Optimization (SMDO) algorithm is modified for minimization of the Multi Objective function for optimization process. System control performance is improved by tuning of the PI controller parameters according to discrete time model of the refrigeration system with multi objective function by adding conditional integral structure that is preferred to reduce the steady state error of the system. Simulations are compared with existing results via many graphical and numerical solutions. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

A Novel Line Feature Description and Matching Method for Visual-Aided Inertial Navigation System

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Journal of Physics: Conference Series 2019年第1期1267卷

作者： Xingxing Guang Yanbin Gao Pan Liu Guangchun Li College of Automation Harbin Engineering University Harbin 150001 China Department of Electrical and Computer Engineering University of Calgary Calgary AB T2N1N4 Canada Beijing Institute of Control and Electronic Technology Beijing 100032 China

With the rapid development of machine vision technology, more and more attention has been paid to the visual-aided inertial navigation system. It is important that to extract and track the line features at the dynamic situation in the visual-aided inertial navigation system which is based on visual line feature information to compensate attitude errors. A novel line feature description is proposed that use the SURF points to mark the LSD lines. Then, through coarse matching and fine matching, the function of continuously tracking the one line features in different images was realized. These line feature description and tracking method are applied in the visual-aided inertial navigation system, and its effectiveness is verified by the vehicle experiment.

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PID2018 benchmark challenge: Learning feedforward control

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arXiv 2018年

作者： Zhao, Yang Dehghan, Sina Ates, Abdullah School of Control Science and Engineering Center for Robotics Shandong University Jinan Shandong250061 China University of California Merced MercedCA95340 United States School of Automation Southeast University Nanjing210096 China Engineering Faculty Computer Engineering Department Inonu University Malatya44280 Turkey

The design and application of learning feedforward controllers (LFFC) for the one-staged refrigeration cycle model described in the PID2018 Benchmark Challenge is presented, and its effectiveness is evaluated. The control system consists of two components: 1) a preset PID component and 2) a learning feedforward component which is a function approximator that is adapted on the basis of the feedback signal. A B-spline network based LFFC and a low-pass filter based LFFC are designed to track the desired outlet temperature of evaporator secondary flux and the superheating degree of refrigerant at evaporator outlet. Encouraging simulation results are included. Qualitative and quantitative comparison results evaluations show that, with little effort, a high-performance control system can be obtained with this approach. Our initial simple attempt of low-pass filter based LFFC and B-spline network based LFFC give J=0.4902 and J=0.6536 relative to the decentralized PID controller, respectively. Besides, the initial attempt of a combination controller of our optimized PI controller and low-pass filter LFFC gives J=0.6947 relative to the multi-variable PID controller. Copyright © 2018, The Authors. All rights reserved.

关键词： Feedforward control

Arc-support line segments revisited: An efficient high-quality ellipse detection

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arXiv 2018年

作者： Lu, Changsheng Xia, Siyu Shao, Ming Fu, Yun Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai200240 China School of Automation Southeast University Nanjing210096 China Department of Computer and Information Science University of Massachusetts DartmouthMA02747 United States Department of ECE Northeastern University BostonMA02115 United States

Over the years many ellipse detection algorithms spring up and are studied broadly, while the critical issue of detecting ellipses accurately and efficiently in real-world images remains a challenge. In this paper, we propose a valuable industry-oriented ellipse detector by arc-support line segments, which simultaneously reaches high detection accuracy and efficiency. To simplify the complicated curves in an image while retaining the general properties including convexity and polarity, the arc-support line segments are extracted, which grounds the successful detection of ellipses. The arc-support groups are formed by iteratively and robustly linking the arc-support line segments that latently belong to a common ellipse. Afterward, two complementary approaches, namely, locally selecting the arc-support group with higher saliency and globally searching all the valid paired groups, are adopted to fit the initial ellipses in a fast way. Then, the ellipse candidate set can be formulated by hierarchical clustering of 5D parameter space of initial ellipses. Finally, the salient ellipse candidates are selected and refined as detections subject to the stringent and effective verification. Extensive experiments on three public datasets are implemented and our method achieves the best F-measure scores compared to the state-of-the-art methods. The source code is available at https://***/AlanLuSun/High-quality-ellipse-detection. Copyright © 2018, The Authors. All rights reserved.

关键词： Geometry

Trends in animal welfare and veterinary informatics

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AIP Conference Proceedings 2019年第1期2140卷

作者： D. I. Kaplun A. M. Sinitca S. A. Romanov A. Zamansky S. Bleuer-Elsner D. van der Linden 1Department of Automation and Control Processes Saint Petersburg Electrotechnical University “LETI” 197376 Saint Petersburg Russia 2Department of Information Systems University of Haifa 3498838 Haifa Israel 3Department of Computer Science University of Bristol Bristol BS8 1QU UK

The field of veterinary healthcare informatics is still in its infancy, and state of the art solutions from human healthcare are not easily adapted. Internet of Things and wearable technologies, as well as recent developments in telehealth legislation may be bringing a wind of change, making it a timely moment to initiate a discussion on the possibilities for cross-fertilization between the worlds of human and animal health informatics. In this paper, we review recent developments in animal welfare and veterinary informatics and highlight some challenges and opportunities.

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Multi-view hybrid embedding: A divide-and-conquer approach

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arXiv 2018年

作者： Xu, Jiamiao Yu, Shujian You, Xinge Leng, Mengjun Jing, Xiao-Yuan Chen, C. L. Philip School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States Department of Computer Science University of Houston HoustonTX77204 United States 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 Macau99999 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

We present a novel cross-view classification algorithm where the gallery and probe data come from different views. A popular approach to tackle this problem is the multiview subspace learning (MvSL) that aims to learn a latent subspace shared by multi-view data. Despite promising results obtained on some applications, the performance of existing methods deteriorates dramatically when the multi-view data is sampled from nonlinear manifolds or suffers from heavy outliers. To circumvent this drawback, motivated by the Divideand-Conquer strategy, we propose Multi-view Hybrid Embedding (MvHE), a unique method of dividing the problem of cross-view classification into three subproblems and building one model for each subproblem. Specifically, the first model is designed to remove view discrepancy, whereas the second and third models attempt to discover the intrinsic nonlinear structure and to increase discriminability in intra-view and interview samples respectively. The kernel extension is conducted to further boost the representation power of MvHE. Extensive experiments are conducted on four benchmark datasets. Our methods demonstrate overwhelming advantages against the stateof-the-art MvSL based cross-view classification approaches in terms of classification accuracy and robustness. Copyright © 2018, The Authors. All rights reserved.

关键词： Embeddings

The Design and Realization of Smart Energy Management System based on Supply-Demand Coordination

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IFAC-PapersOnLine 2017年第1期50卷 195-200页

作者： Okae J. Du J. Akowuah E.K. Appiah G. Anto E.K. School of Automation Science and Control Engineering South China University of Technology China Department of Computer Engineering Kwame Nkrumah University of Science and Technology Ghana The Energy Center College of Engineering Kwame Nkrumah University of Science and Technology Ghana Department of Electrical and Electronic Engineering Kwame Nkrumah University of Science and Technology Ghana

Sub-Saharan Africa in recent years have been faced with many power challenges including limited and unreliable power supply, high cost of power supply and underdeveloped power infrastructures with serious negative impacts on the socio-economic development. This paper presents the development of Smart Energy Management Solution (SEMS) for buildings. The work seeks to propose a generic algorithm that supports existing wiring infrastructure of buildings in Africa to provide 24/7 reliable power supply and efficient management of limited power supply in buildings. SEMS focuses on the use of robust, distributed and heterogeneous power sources connected in islanding phenomenon to ensure reliability and also using a dynamic approach with energy efficiency measures to provide a balance between power supply and demand in buildings. A demonstration of SEMS for buildings was performed in MATLAB Simulink using actual data obtained from selected buildings at Kwame Nkrumah University of Science and Technology (KNUST), Ghana. SEMS revealed higher power reliability and efficiency in energy usage. © 2017

关键词： building automation energy efficiency Smart Energy Management Solution (SEMS)

Human intention estimation based on hidden Markov model motion validation for safe flexible robotized warehouses

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arXiv 2018年

作者： Petković, Tomislav Puljiz, David Marković, Ivan Hein, Björn University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Laboratory for Autonomous Systems and Mobile Robotics Unska 3 ZagrebHR-10000 Croatia Karlsruhe Institute of Technology Institute for Anthropomatics and Robotics Intelligent Process Automation and Robotics Lab Kaiserstraße 12 Deutschland KarlsruheDE-76131

With the substantial growth of logistics businesses the need for larger warehouses and their automation arises, thus using robots as assistants to human workers is becoming a priority. In order to operate efficiently and safely, robot assistants or the supervising system should recognize human intentions in real-time. Theory of mind (ToM) is an intuitive human conception of other humans' mental state, i.e., beliefs and desires, and how they cause behavior. In this paper we propose a ToM based human intention estimation algorithm for flexible robotized warehouses. We observe human's, i.e., worker's motion and validate it with respect to the goal locations using generalized Voronoi diagram based path planning. These observations are then processed by the proposed hidden Markov model framework which estimates worker intentions in an online manner, capable of handling changing environments. To test the proposed intention estimation we ran experiments in a real-world laboratory warehouse with a worker wearing Microsoft Hololens augmented reality glasses. Furthermore, in order to demonstrate the scalability of the approach to larger warehouses, we propose to use virtual reality digital warehouse twins in order to realistically simulate worker behavior. We conducted intention estimation experiments in the larger warehouse digital twin with up to 24 running robots. We demonstrate that the proposed framework estimates warehouse worker intentions precisely and in the end we discuss the experimental results. Copyright © 2018, The Authors. All rights reserved.

关键词： Virtual reality