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State-based control of process services within modular process plants

Procedia CIRP 2018年 72卷 1088-1093页

作者： Henry Bloch Stephan Hensel Mario Hoernicke Katharina Stark Anna Menschner (neé Hahn) Alexander Fay Leon Urbas Torsten Knohl Jens Bernshausen Institute of Automation Technology Helmut-Schmidt-University Holstenhofweg 85 22043 Hamburg Germany Chair of Process Control Systems and Process Systems Engineering Group Technische Universität Dresden 01062 Dresden Germany ABB Corporate Research Opertions Management Wallstadter Straße 59 68526 Bayer AG 51386 Leverkusen Germany INVITE GmbH 51386 Leverkusen Germany

The modularization of process plants is an approach to cope with the changing requirements of the process industry, such as highly volatile markets and shorter product lifecycles. Each module offers services as encapsulated process functions to the superior control system for the orchestration. These services are controlled in a state-based way. The encapsulation of these services in a reasonable way is a difficult task, because aspects of process and automation engineering must be considered. This contribution introduces an approach for the encapsulation of process functions in services from an automation point of view. Furthermore, the operation modes of modules, services and field devices are discussed. Additionally, possible solutions for the orchestration based on recipe models are introduced. The developed concepts have been tested within a simulation environment.

关键词： Modular process automation Microservices Orchestration State-based control Operating modes Service-oriented architectures

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Systems biology modelling of sirs epidemic spread: Computational cybernetic issues

Systems biology modelling of sirs epidemic spread: Computati...

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2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017

作者： Jing, Yuanwei Dimirovski, Georgi M. Tökel, Dilek Bilgin Özen, Figen College of Information Science and Engineering Northeastern University Shenyang Liaoning110004 China Faculty of Engineering Dogus University Acibadem IstanbulTR-34722 Turkey FEEIT St Cyril and St Methodius University Karpos 2 BB SkopjeMKD-1000 Macedonia Department of Control and Automation Faculty of Engineering Dogus University Acibadem Istanbul34722 Turkey Department of Electrical and Electronics Engineering Faculty of Engineering Haliç University Sötlöce Beyog lu IstanbulTR-34000 Turkey

ISBN: (纸本)9781538616451

The estimation of the domain of attraction of a class of susceptible-infectious-removed-susceptible immigration is investigated. On assumption the disease-free equilibrium and the endemic equilibrium existences, hence a Lyapunov function too, the domain of attraction of the epidemic model is estimated by means of LF-LMI-moment and SOS optimization approaches. An invariant subset of the domain of attraction, along with certain enlargement, has been achieved. Simulation results, given in a comparison presentation, demonstrate feasibility and validity of the proposed technique as well as reveal that this algorithm outperforms other ones in applications to epidemic models. © 2017 IEEE.

关键词： Lyapunov functions

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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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Flatness of a class of linear Volterra partial integro–differential equations

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IFAC-PapersOnLine 2016年第8期49卷 174-179页

作者： Meurer, T. Chair of Automatic Control Faculty of Engineering Christian–Albrechts–University Kiel Kiel24143 Germany

Flatness–based trajectory planning is addressed for a parabolic–like linear Volterra partial integro–differential equation (PIDE) with boundary control. For this purpose the PIDE is formally integrated which results in an implicit state and input parametrization. Successive approximation is used to explicitly resolve the implicit result in terms of a recursion scheme. Absolute and uniform convergence is verified by restricting the flat output trajectory to Gevrey class functions of a particular order. Simulation results confirm the applicability and illustrate the tracking behavior for finite time transitions between operating points along predefined transition paths. © 2016

关键词： Distributed parameter control systems Differential equations Feedforward control Trajectories Boundary controls Distributed parameter systems Flatness Recursion schemes Successive approximations Tracking behavior Trajectory Planning Uniform convergence

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The impact of vocabulary size and language model order on the polish whispery speech recognition

The impact of vocabulary size and language model order on th...

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International Conference on Methods and Models in automation and Robotics (MMAR)

作者： Piotr Kozierski Talar Sadalla Szymon Drgas Adam Dąbrowski Joanna Zietkiewicz Poznan University of Technology Pozuan Faculty of Computing Institute of Automation and Robotics Faculty of Electrical Engineering Institute of Control

The article presents studies on the automatic whispery speech recognition. In the performed research a new corpus with whispery speech has been used. The aim of studies presented in this paper was to check, how the vocabulary size and the language model order influence on the speech recognition quality. It has been concluded that even using recordings with 5,000 different words only it is possible to prepare large vocabulary continuous speech recognition (LVCSR) model. It has been also found that the third order of language model is the best choice. The difference between normal and whispery speech is negligible and is manifested only in higher word error rate index (about 1.5 times higher for whispery speech).

关键词： Speech Speech recognition Vocabulary Training Hidden Markov models Error analysis

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The family house control system based on Raspberry Pi 21

The family house control system based on Raspberry Pi

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21st International Conference on Circuits, Systems, Communications and Computers, CSCC 2017

作者： Sysala, Tomas Fogl, David Neumann, Petr TBU in Zlin Dept. of Automation and Control Engineering Faculty of Appl. Informatics Nad Stranemi Zlin4511 Czech Republic TBU in Zlin Dept. of Electronics and Measurements Faculty of Applied Informatics Nad Stranemi 4511 Zlin Czech Republic

The article deals with the design and implementation of a smart household based on simple wireless modules, which are monitoring (collecting data) and controlling smart household supporting devices. The central unit processes measured parameters, and in relation to resulting values, a pre-set action is performed. Those actions variety can be configured by user via the user interface so that a set of smart rules for reaction on by household devices generated stimuli or problems can be created. That all together composes a control system based on Raspberry Pi, which manages indoor and outdoor temperature measurement, the lighting control, RF transmitter, jalousie, motion sensor control etc. There is a GUI for a PC and for a mobile phone as a part of that system. © The Authors, published by EDP Sciences, 2017.

关键词： control systems

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Verifying the accuracy of interlocking tables for railway signalling systems using abstract state machines

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Journal of Modern Transportation 2016年第4期24卷 277-283页

作者： Basri Tugcan Celebi Ozgur Turay Kaymakci Department of Control and Automation Engineering Faculty of Electrical and Electronics Engineering Yildiz Technical University

Railway transportation system is a critical sector where design methods and techniques are defined by international standards in order to reduce possible risks to an acceptable minimum level. CENELEC 50128 strongly recommends the utilization of finite state machines during system modelling stage and formal proof methods during the verifi- cation and testing stages of control algorithms. Due to the high importance of interlocking table at the design state of a sig- nalization system, the modelling and verification of inter- locking tables are examined in this work. For this purpose, abstract state machines are used as a modelling tool. The developed models have been performed in a generalized structure such that the model control can be done automatically for the interlocking systems. In this study, NuSMV is used at the verification state. Also, the consistency of the developed models has been supervised through fault injection. The developed models and software components are applied on a real railway station operated by Metro Istanbul Co.

关键词： Model checking - Abstract state machines Interlocking

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Reinforcement Learning-Based Predictive control for Autonomous Electrified Vehicles

Reinforcement Learning-Based Predictive Control for Autonomo...

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IEEE Symposium on Intelligent Vehicle

作者： Teng Liu Chao Yang Chuanzheng Hu Hong Wang Li Li Dongpu Cao Fei-Yue Wang Vehicle Intelligence Pioneers Inc. Qingdao Shandong China Jiangsu XCMG Construction Machinery Research Institute Ltd. Xuzhou Jiangsu China Mechanical and Mechatronics Engineering Department Waterloo University Canada Faculty of Department of Automation Tsinghua University China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

This paper proposes a learning-based predictive control technique for self-driving hybrid electric vehicle (HEV). This approach is a hierarchical framework. The higher-level is a human-like driver model, which is applied to predict accelerations in the car following situation to replicate a human driver's demonstrations. The lower-level is a reinforcement learning (RL)-based controller, which enforces the battery and fuel consumption constraints to improve energy efficiency of HEV. In addition, we present induced matrix norm (IMN) to handle cases that the training data cannot provide sufficient information on how to operate in current driving situation. Simulation results illustrate that the proposed method can reproduce human driver's driving style and promote fuel economy.

关键词： Acceleration Hybrid electric vehicles Trajectory Hidden Markov models Predictive control Energy efficiency

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A Lyapunov based model reference adaptive control of a quadrotor

A Lyapunov based model reference adaptive control of a quadr...

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International Conference on Electrical and Electronics engineering, ELECO

作者： Onur Akgün Evren Subaşı Türker Türker Faculty of Engineering Turkish-German University Istanbul Turkey Dept. of Control & Automation Engineering Yildiz Technical University Istanbul Turkey

Model reference adaptive controller is proposed to control the position of a quadrotor with uncertain model parameters. The controller design procedure is provided considering position and attitude dynamics as outer and inner loops respectively. Reference signals for roll and pitch angles are obtained from the outer loop controller while the inner loop controller drives the tracking error of roll and pitch angle dynamics to zero. Stability analysis for both inner and outer loop error dynamics are performed and the adaptation laws are derived based on Lyapunov stability theory. Since the reference models can also be assigned separately for inner and outer loops, the speed of the responses of position and attitude dynamics are adjusted independently improving the control performance. The viability and the success of the proposed controller are tested through simulations studies performed for different tracking scenarios.

关键词： Adaptation models Attitude control Vehicle dynamics Lyapunov methods Helicopters Dynamics Position control

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3D Environment Modeling with Height Dimension Reduction and Path Planning for UAV

3D Environment Modeling with Height Dimension Reduction and ...

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2017 9th International Conference on Modelling, Identification and control (ICMIC 2017)

作者： Zhe Lv Liying Yang Yuqing He Zhong Liu Zhonghua Han the State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of Sciences the Faculty of Information and Control Engineering Shenyang Jianzhu University Faculty of Information and Control Engineering Shenyang Jianzhu University Shenyang Institute of Automation Chinese Academy of Sciences

In this paper,an environment modeling method with height dimension reduction for unmanned aerial vehicle(UAV) path planning is *** on the traditional grid method,a plane being vertical to yz-plane and including the start point and end point is considered in this *** the height of this plane and obstacles,the environment model could be set up through re-dividing the plane by grid *** idea reduces the dimension of the 3 D environment model and ignores the obstacles which are lower than the flying height of *** this way,the accuracy of the proposed environment model method could be increased,and the efficiency of the path planning algorithm could be ensured *** experiment shows the effectiveness of this environment modeling method by applying A* algorithm for path planning.

关键词： Environment modeling Path planning Grid method A* algorithm

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