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IEEE International Conference on Fuzzy Systems

作者： Engin Yesil M. Furkan Dodurka Leon Urbas Control and Automation Engineering Department Istanbul Technical University Istanbul Turkey Chair of Process Control Systems Engineering Technology University of Dresden Germany

In this paper, the conventional Fuzzy Cognitive Maps (FCMs), which has already achieved success in many fields, are extended by using triangular fuzzy numbers (TFNs). The advantage of FCMs is that they are relatively easy to construct and parameterize and are capable of handling the full range of system feedback structure, including density-dependent effects. However, it is a well-known fact that there are some limitations inherent in FCM, such as lack of adequate capability to handle uncertain information and lack of enough ability to aggregate the information from different sources. Triangular fuzzy numbers which are represented by a triplet has the capacity to represent the uncertain relations between the concepts. In this context, the weight matrix representing the causal relations are enhanced to a fuzzy weight matrix that has TFNs as element. As a result of this improvement, the dynamic reasoning algorithm of the conventional FCM is improved for the use of the proposed novel FCM. The proposed FCM is presented via four simulations and the results are discussed. The results of the simulation study shows how easily the uncertain information can be represented and interpreted by the proposed FCM design methodology.

关键词： Uncertainty Vectors Cognition Fuzzy sets Pragmatics Fuzzy cognitive maps Modeling

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MATLAB case-based reasoning GUI application for control engineering education

MATLAB case-based reasoning GUI application for control engi...

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International Conference on Information Technology Based Higher Education and Training, ITHET

作者： Engin Yesil Cihan Ozturk Berk Cosardemir Leon Urbas Faculty of Electrical and Electronics Engineering Control Engineering Department Istanbul Technical University Maslak Istanbul Turkey Chair of Distributed Control Systems Engineering Institute of Automation Dresden University of Technology Dresden Germany

This paper represents using Case-Based Reasoning (CBR) in order to support undergraduate control engineering students for learning nonlinear systems and control applications. CBR is an experience-based problem solving methodology; thus, it is used for helping control engineering students to design conventional PID controllers for nonlinear systems. For this purpose, GUNT pH neutralization process is used as the experimental setup and a GUI is designed for cased-based reasoning in MATLAB. It is observed that undergraduate students can learn and increase their experience on nonlinear systems using the proposed new CBR-GUI.

关键词： Process control control engineering Cognition MATLAB Databases Libraries

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Towards context adaptive HMIs in process industries

Towards context adaptive HMIs in process industries

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Leon Urbas Stefan Hennig Henning Hager Falk Doherr Annerose Braune Chair of Distributed Control Systems Engineering Technische Universität Dresden Germany Chair of Automation Systems Technische Universität Dresden Germany

This paper presents the combination of two distinct model driven HMI engineering approaches. Together they setup a complete toolchain that lays the basis for the model driven (semi)automatic generation of flexible, multi-platform HMIs for process industries. The two approaches are autoHMI which derives a concrete UI design from Computer Aided engineering Data, and XVCML which allows to generate final UIs for different web implementation paradigms like XHTML or Java on top of OPC UA. This tool integration provides a complete model driven software engineering architecture that cuts down the manual efforts in HMI engineering close to zero. This is a prerequisite to handle the complexity of context adaptive interfaces.

关键词： Process control automation Concrete Instruments Context Data models

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Robustness of Prediction Based Delay Compensation for Nonlinear Systems

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IFAC Proceedings Volumes 2011年第1期44卷 203-208页

作者： Rolf Findeisen Lars Grüne Jürgen Pannek Paolo Varutti Otto–von–Guericke–Universität Magdeburg Institute for Automation Engineering Chair for Systems Theory and Automatic Control University of Bayreuth Institute of Mathematics Chair of Applied Math Curtin University of Technology Perth Australia

Abstract control of systems where the information between the controller, actuator, and sensor can be lost or delayed can be challenging with respect to stability and performance. One way to overcome the resulting problems is the use of prediction based compensation schemes. Instead of a single input, a sequence of (predicted) future controls is submitted and implemented at the actuator. If suitable, so-called prediction consistent compensation and control schemes, such as certain predictive control approaches, are used, stability of the closed loop in the presence of delays and packet losses can be guaranteed. In this paper, we show that control schemes employing prediction based delay compensation approaches do posses inherent robustness properties. Specifically, if the nominal closed loop system without delay compensation is ISS with respect to perturbation and measurement errors, then the closed loop system employing prediction based delay compensation techniques is robustly stable. We analyze the influence of the prediction horizon on the robustness gains and illustrate the results in simulation.

关键词： Delay information loss nonlinear stability ISS robustness predictive control

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control of an Overhead Crane with the controlled Lagrangian Method

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IFAC Proceedings Volumes 2010年第14期43卷 131-136页

作者： Daniel Poljak Dominik Schindele Felix Antritter Harald Aschemann Claus Hillermeier Chair of Automation and Control Engineering University of the Bundeswehr Munich Germany Chair of Mechatronics University of Rostock Germany

A nonlinear controller structure for an overhead crane is designed and implemented on a crane plant. The energy based stabilizing controller part is derived by the method of controlled Lagrangians. In that framework, kinetic and potential shaping is performed and so-called general matching conditions are employed. control parameters well suited for the practical implementation are found by optimization using the linearization of the closed loop system. Nonlinear damping effects are counteracted in the overall controller structure by feedforward compensation and a reduced nonlinear disturbance observer.

关键词： energy based control underactuated mechanical systems controlled Lagrangians

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Motion planning and feedback control of a planar robotic unicycle model

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IFAC Proceedings Volumes 2009年第13期42卷 501-506页

作者： Matthias Franke Joachim Rudolph Frank Woittennek Fraunhofer Institut Integrierte Schaltungen Design Automation Division Zeunerstraße 38 01069 Dresden Germany Chair of systems theory and control engineering Saarland University 66123 Saarbrücken Germany Institut für Regelungs- und Steuerungstheorie Technische Universität Dresden 01062 Dresden Germany

Abstract Open and closed loop control design for the planar motion of a unicycle model consisting of a double pendulum mounted on a rolling wheel is considered. The motion planning problem is solved by prescribing trajectories to the two pendulum angles, the wheel angle is then obtained by integrating twice. A feedforward control trajectory directly follows from this parametrization. A feedback stabilizing the planned motion is designed after linearization of the relevant subsystem about the planned trajectories. Simulation results show the usefulness of the result.

关键词： Underactuated system motion planning feedback control trajectory tracking

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Fixed point transformations in the adaptive control of fractional-order MIMO systems

Lecture Notes in Control and Information Sciences

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Lecture Notes in control and Information Sciences 2009年 396卷 103-112页

作者： Tar, József K. Rudas, Imre J. Nádai, László Kozlowski, Krzysztof R. MacHado, José A. Tenreiro Institute of Intelligent Engineering Systems John von Neumann Faculty of Informatics Budapest Tech Bécsi út 96/B Budapest H-1034 Hungary Computer and Automation Research Institute Hungarian Academy of Sciences Kende u. 13-17 Budapest H-1111 Hungary Chair of Control and Systems Engineering Poznań University of Technology ul. Piotrowo 3a Poznań 60-965 Poland Department of Electrotechnical Engineering Institute of Engineering of Porto Rua Dr. Antonio Bernardino de Almeida Porto 4200-072 Portugal

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MODELING AND control OF ELEVATORS BY STATECHARTS

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Asian Journal of control 2008年第2期6卷

作者： Yi-Sheng Huang Sheng-Luen Chung Mu-Der Jeng Department of Aeronautical Engineering Chung Cheng Institute of Technology National Defense University Tashi Taoyuan 335 Taiwan R.O.C. Department of Electrical Engineering National Taiwan University of Science and Technology Taipei 106 Taiwan R.O.C. Department of Electrical Engineering National Taiwan Ocean University Kellung 202 Taiwan R.O.C. MuDer Jeng received the Ph.D. degree in computer and systems engineering from Rensselaer Polytechnic Institute Troy NY in 1992. Since August 1992 Dr. Jeng has been with National Taiwan Ocean University Keelung Taiwan where he is currently a full Professor at the Department of Electrical Engineering. His current research interests include Petri nets discrete event systems computer integrated manufacturing semiconductor factory automation embedded systems. Dr. Jeng is the author/co-author of over 120 book chapters journal papers and conference papers. Dr. Jeng received the Franklin V. Taylor Outstanding Paper Award from the IEEE Systems Man and Cybernetics Society in 1993. He was granted the Research Award by the National Science Council of Taiwan annually from 1994 to 2000. He is an Associate Editor for IEEE Transactions on Systems Man and Cybernetics-Part A IEEE Transactions on Robotics and Automation IEEE Transactions on Robotics and serves on the Editorial Board of International Journal of Computer Integrated Manufacturing. He has been a Guest Editor for eight leading journals. Dr. Jeng is the Chair of the Technical Committee on Discrete Event Systems of the IEEE SMC Society and the Founding Chair of the Technical Committee on Semiconductor Factory Automation of the IEEE Robotics and Automation Society. He served as the Exhibitions Chair of 2003 IEEE International Conference on Robotics and Automation and the Special Sessions Chair of 2004 IEEE International Conference on Networking Sensing and Control. He serves as a Program Co-Chair of 2005 IEEE International Conference on Networking Sensing and Control and the Organization Commit

Statechart has been utilized as a visual formalism for the modeling of complex and interactive systems for its illuminating features on describing properties of causality, concurrency, and synchronization. This paper presents the application of satechart to the modeling, design and implementation of an elevator system, whose system behavior involves aggregating complexity of state descriptions, and imposition of underlying control policy. Based on the operational flow of an elevator, we derive the associated statechart model by looking into the inherent hierarchical structure of the elevator. The advantage of the proposed approach is the clear presentation of system behavior in terms of conditions and events that cause the transitions in system dynamics. Implementation of the controlled elevator based on the modeled statechart is also presented.

关键词： Statechart interactive systems elevator

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NONLINEAR NETWORK STRUCTURES FOR FEEDBACK control

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Asian Journal of control 2008年第4期1卷

作者： F.L. Lewis Dept. of Electical Engineering The University of Texas at Arlington U.S.A. F. L. Lewis was born in Wärzburg. Germany subsequently studyning in Chile and Goruonstoun School in Scotland. He obtained the Bachelor's Degree in Physics/Electrical Engineering and the Master's of Electrical Engineering Degree at Rice University in 1971. He spent six years in the U.S. navy serving as Navigator aboard the frigate USS Trippe (FF-1075) and Executive Officer and Acting Commanding Officer aboard USS Salinan (ATF-161). In 1977 he received the Master's of Science in Aeronautical Engineering from the University of West Florida. In 1981 he obtained the Ph.D. degree at The Georgia Institute of Technology in Atlanta where he was employed as a professor from 1981 to 1990 and is currently an Adjunct Professor. He is a Professor of Electrical Engineering at The University of Texas at Arlington where he was awarded the Moncrief-O'Donnell Endowed Chair in 1990 at the Automation and Robotics Research Institute. Dr. Lewis has studied the geometric analytic and structural properties of dynamical systems and feedback control automation. His current interests include robotics intelligent control neural and fuzzy systes nonlinear systems and manufacturing process control. He is the author/co-author of 2 U.S. patents 124 journal papers 20 chapters and encyclopedia articles 210 refereed conference papers seven books: Optimal Control Optimal Estimation Applied Optimal Control and Estimation Aircraft Control and Simulation Control of Robot Manipulators Neural Network Control High-Level Feedback Control with Neural Networks and the IEEE reprint volume Robot Control. Dr. Lewis is a registered Professional Engineer in the State of Texas and was selected to the Editorial Boards of International Journal of Control Neural Computing and Applications and Int. J. Intelligent Control Systems. He is the recipient of an NSF Research Initiation Grant and has been continuously funded by NSF since 1982. Since 1991 he has received $1.8 m

A framework is given for controller design using Nonlinear Network Structures, which include both neural networks and fuzzy logic systems. These structures possess a universal approximation property that allows them to be used in feedback control of unknown systems without requirements for linearity in the system parameters or finding a regression matrix. Nonlinear nets can be linear or nonlinear in the tunable weight parameters. In the latter case weight tuning algorithms are not straightforward to obtain. Feedback control topologies and weight tuning algorithms are given here that guarantee closed-loop stability and bounded weights. Extensions are discussed to force control, backstepping control, and output feedback control, where dynamic nonlinear nets are required.

关键词： Intelligent feedback control neural networks neural network structures basis function networks fuzzy control fuzzy-neural networks universal approximation adaptive nonparametric control learning control systems

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SUPER-HEURISTICS AND THEIR APPLICATIONS TO COMBINATORIAL PROBLEMS

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Asian Journal of control 2008年第1期1卷

作者： Tak Wing Edward Lau Yu-Chi Ho Division of Engineering and Applied Sciences Harvard University Cambridge MA02138 U.S.A. Yu-Chi (Larry) Ho received his S.B. and S.M. degrees in Electrical Engineering from M.I.T. and his Ph.D. in Applied Mathematics from Harvard University. Except for three years of full time industrial work he has been on the Harvard Faculty. Since 1969 he has been Gordon McKay Professor of Engineering and Applied Mathematics. In 1988 he was appointed to the T. Jefferson Coolidge Chair in Applied Mathematics and Gordon McKay Yu-Chi (Larry) Ho received his S.B. and S.M. degrees in Electrical Engineering from M.I.T. and his Ph.D. in Applied Mathematics from Harvard University. Except for three years of full time industrial work he has been on the Harvard Faculty. Since 1969 he has been Gordon McKay Professor of Engineering and Applied Mathematics. In 1988 he was appointed to the T. Jefferson Coolidge Chair in Applied Mathematics and Gordon McKay Professor of Engineering at Harvard and as visiting professor to the Cockrell Family Regent's Chair in Engineering at the University of Texas Austin. He has published over 120 articles and three books one of which (co-authored with A.E. Bryson Jr.) has been translated into both Russian and Chinese and made the list of Citation Classics as one of the most referenced works on the subject of optimal control. He is on the editorial boards of several international journals and is the editor-in-chief of the new international Journal on Discrete Event Dynamic Systems. He is the recipient of various fellowships and awards including the Guggenheim (1970) and the IEEE Field Award for Control Engineering and Science (1989) the Chiang Technology Achievement Award (1993). He is a fellow of IEEE a Distinguished Member of the Control Systems Society and a member of the U.S. National Academy of Engineering. In addition to serving on various governmental and industrial panels and professional society administrative bodies he was the President of the IEEE Robotics & Automation Society in 1988

Combinatorial problems are known to be difficult because of the shear size of the solution space and the lack of polynomial time algorithms to “solve” them. Heuristics are often devised to produce acceptable solutions in an affordable time. In this paper, we propose a method called super-heuristic that expands the capabilities of heuristics using randomization and sampling techniques. We submit that heuristics are in general strategies that map from available information of a problem instance to decisions in solution constructions/improvement. We show that it is important to utilize the information effectively in the randomization process. More importantly, the possibility of randomization around a heuristic spells out the demarcation between the roles of human and machines in complex optimization problems.

关键词： Combinatorial problems heuristics randomization and sampling techniques man-machine interactions

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