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Pole Placement Controller Design Based on Fuzzy Process Model

IFAC Proceedings Volumes 2000年第28期33卷 219-224页

作者： Robert Cupec Nedjeljko Perić Ivan Petrović Department of Control and Computer Engineering in Automation Faculty of Electrical Engineering and Computing university of Zagreb Unska 3 10000 Zagreb Croatia

An explicit self-tuning controller based on the Takagi-Sugeno fuzzy model of the process is proposed. The fuzzy model is represented as a linear regression model whose parameters are functions of some of the process variables. Such a model can be considered as a linear time-varying model whose parameter values are known at every moment. The pole placement design procedure modified for time-varying systems is applied to obtain the polynomial controller parameters that provide the desired closed-loop poles. The proposed algorithm is very simple, and thus suitable for on-line controller design in adaptive control systems.

关键词： fuzzy control fuzzy modeling adaptive control

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Model structure selection for nonlinear system identification using feedforward neural networks

Model structure selection for nonlinear system identificatio...

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International Joint Conference on Neural Networks (IJCNN)

作者： I. Petrovic M. Baotic N. Peric Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation University of Zagreb Zagreb Croatia

The majority of nonlinear models based on neural networks are of the black-box structure. A nonlinear system can be nonlinear in many different ways, thus the nonlinear black-box model structure must be very flexible. This means that it must have many parameters. A model offering many parameters usually creates problems, and the variance contribution to the error might be high. For a particular identification problem, only a subset of the parameters may be necessary, and the main topic in nonlinear system identification is how to select a model structure that describes the system dynamics with the minimum number of parameters. This paper discusses nonlinear input-output models that are suitable for implementation of feedforward neural networks. The proposed model structures were tested and compared using the identification procedure of a pH process. The results indicated that a simplest model structure can satisfactorily represent the investigated process.

关键词： Nonlinear systems Neural networks Feedforward neural networks Nonlinear dynamical systems Control engineering computing Computer networks Predictive models Automatic control Nonlinear control systems automation

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DLL's Simplify Process Tuning

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IFAC Proceedings Volumes 2000年第6期33卷 211-215页

作者： Andy Doonan Chris Cox Roger Morris School of Computing and Engineering Technology University of Sunderland Sunderland UK Automation Partnership Limited Peterlee Co. Durham SR8 2RJ UK

This paper describes the implementation of a robust tuning algorithm based on the Astrom- Hagglund autotuning algorithm. The development of the software from DOS through Windows95 to DLL is chronicled with screen shot... 详细信息

关键词： PID Control Autotuners Computer-aided design Implementation

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Using simulation for the design of semi-autonomous vehicle systems

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IFAC Proceedings Volumes 2000年第20期33卷 351-356页

作者： Sandor Ujvari Philip R. Moore Centre for Intelligent Automation Department of Engineering Science Högskolan Skövde SE-541 28 Skövde Sweden Faculty of Computing Sciences and Engineering De Montfort University Leicester LE1 9BH United Kingdom

The paper describes the development of Semi-Autonomous Vehicles (SAVS) in the context of Automated Guided Vehicle Systems (AGVS). During the design process of a complete material handling AGV-system many variables must be decided. A two-stage simulation approach of discrete event simulation and continuous path simulation, improves development and testing of SAVS. Decisions need to be made e. g. what main navigation sensor to use, how many vehicles are needed for the task. The interrelation of these parameters makes it difficult to find optimum or near-optimum values. Because of this, simulation is a very useful tool to design and evaluate AGV-systems.

关键词： Simulation Automated Guided Vehicles

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Application of a neural predictive controller in boost converter input current control

Application of a neural predictive controller in boost conve...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： I. Petrovic M. Baric A. Magzan N. Peric Fac. of Electr. Eng. Zagreb Univ. Croatia Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation University of Zagreb Zagreb Croatia College of Electrical Engineering Polytechnics College of Zagreb Zagreb Croatia

The application of a nonlinear predictive controller in the cascade control structure of a boost converter is investigated. The neuro-predictive controller is realized as a nonlinear optimizer, using the Levenberg-Marquardt unconstrained optimization procedure. For the prediction of future process responses, two MLP neural networks are used. One network is used for modeling the converter dynamics and the other for online estimation of the converter's input voltage. This structure ensures good system performance in all operating regions and inherent compensation of ripples in the converter's input current caused by variations of the input voltage. The advantages of the proposed control structure are demonstrated through experimental comparison with a linear GPC with manually adjusted feedforward compensator.

关键词： Current control Voltage control Control systems Automatic control Pulse width modulation Switches Rail transportation Current measurement Electric current control Application software

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Application of direction constrained and bipolar waves for pattern recognition

Application of direction constrained and bipolar waves for p...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： I. Petras T. Roska Analogical and Neuml Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Ekctronicr Research Laboratory College of Engineering University of California Berkeley Berkeley CA USA

Direction constrained and bipolar waves are introduced. Their possible applications for direction selective curvature and concavity detection as well as region segmentation are shown. A cellular neural (CNN) algorithm frame for feature-based object decomposition is presented. Algorithms are tested on the 64/spl times/64 CNNUM (CNN Universal Machine) chip.

关键词： Pattern recognition Cellular neural networks Application software Computer networks Laboratories Testing Turing machines Spatiotemporal phenomena Logic Positron emission tomography

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Adaptive Fuzzy Ship Autopilot for Track-Keeping

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IFAC Proceedings Volumes 2000年第21期33卷 129-134页

作者： Jasmin Velagic Zoran Vukic Edin Omerdic University of Sarajevo Faculty of Electrical Engineering Skenderija 70 BH-71000 Sarajevo Bosnia and Herzegovina fax : (+387 71) 654 972 University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation Unska 3 HR-10000 Zagreb Croatia fax : (+385 1) 612 98 09 University of Tuzla Faculty of Electrical and Mechanical Engineering Franjevacka 2 BH-75000 Tuzla Bosnia and Herzegovina

We develop in this paper an adaptive fuzzy gain autopilot for ship track-keeping. This autopilot is composed of Sugeno fuzzy type autopilot in an ordinary feedback loop and adjustable scaling factors mechanism in an additional feedback loop. The adjustment mechanism represents a fuzzy controller that changes scaling factors of the base fuzzy autopilot. The control system for the track-keeping is completely described. For the track-keeping problem, the maneuver of way-point turning and ship guiding through a complex path (trajectory) are presented. The influence of sea current and wave disturbances on track-keeping performance was also considered. We first present simulation results obtained by the Sugeno fuzzy type autopilot. Then, we compare those results with ones obtained by an adaptive fuzzy autopilot.

关键词： Adaptive fuzzy control track-keeping fuzzy gain concept disturbance rejection ship control

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MD simulation of heterogeneous vapor nucleation on a solid surface

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AIP Conference Proceedings 2000年第1期534卷 253-256页

作者： K. T. Kholmurodov K. Yasuoka X. C. Zeng 1Computational Science Division Advanced Computing Center The Institute of Physical and Chemical Research (RIKEN) Hirosawa 2-1 Wako Saitama 351-0198 Japan 4Laboratory of Computing Techniques and Automation Joint Institute for Nuclear Research Dubna Moscow region 141980 Russia 2Department of Mechanical Engineering Keio University Yokohama 223-8522 Japan 3Department of Chemistry University of Nebraska-Lincoln Lincoln Nebraska 68588

Molecular dynamics simulations of nucleation of a supersaturated Lennard-Jones vapor confined between parallel solid walls have been performed. The walls in the system, unlike the structure-less one [K. Yasuoka, G. T. Gao, and X. C. Zeng, J. Chem. Phys. 112, pp. 4279–4285 (2000)], are simulated in a more realistic fashion. The particles in the vapor and the solid walls are exactly the same and are described by the same Lennard-Jones potential. The walls are fixed in place in an fcc lattice structure by a combination of the restoring tethering forces and constraint mechanism. The restoring potential confines wall atoms to their lattice sites at the equilibrium state. The walls during simulations are thermostatted, so the heat being dissipated through conduction to the walls, as it is in an experiment [S. T. Cui, P. T. Cummings, and H. D. Cochran, J. Chem. Phys. 111, pp. 1273–1280 (1999)]. Condensation of a supersaturated vapor on a solid surface is investigated with the increasing strength of the wall-vapor interaction. The wall surfaces are the same (100) surface, but with the different strengths of the attraction of vapor atoms: strongly adsorbing wall (with ε1=ε ) and weakly adsorbing wall (with ε2=0.1ε ). Transition from a metastable supersaturated vapor phase to a stable condensed state is studied by monitoring the molecular dynamics configurations of the system in real time and identifying the short-lived droplet nucleus.

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Iterative Learning Identification and Design of Industrial Furnace Process Control

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IFAC Proceedings Volumes 2000年第28期33卷 57-64页

作者： G.M. Dimirovski K. Schlacher M.J. Stankovski T.D. Kolemisevska-Gugulovska N.E. Gough Dept. of Automation & Systems Engineering at Faculty of Electrical Engineering St. Cyril and St. Methodius University P.O.B.574 MK-91000 Skopje Rep. of Macedonia FAX#++389-91-36-42-62 Inst. für Regelungstechnik und elektr. Antriebe Technisch-Naturwiessenschftliche Fakultät Johannes Kepler Universität Altenberger Straße 69 A-4040 Linz Austria School of Computing and Information Technology University of Wolverhampton Wulfurna Str. WV1 1SB Wolverhampton UK

An applications oriented control systems engineering approach for a class of well- posed thermal systems, e.g. industrial furnaces and ovens, that is consistent with most of theoretical results in systems and control sciences has been elaborated and tested in designing controls for several industrial-scale furnaces. It provides a methodology for iterative learning and resolving process identification and control design for multi-variable systems within a discrete convolution framework and using truncated k-time sequence matrices of characteristic input-output modes as well as their characteristic patterns and singular characteristic patterns, starting with standard non-parametric process time-domain models identified under operating conditions. Within computer process control environment and for practical engineering and maintenance reasons, digital implementations are sought in terms of partial steady-state decoupling and two-term laws or combination of certain MIMO and SISO controls. The pusher furnace in Skopje Steelworks is used to illustrate this methodological approach

关键词： Industrial control pseudo-impulse responses time sequences fuzzy-Petri-net supervisor natural input-output operating modes discrete-time convolution

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Automatic contingency selection based on a pattern analysis approach

Automatic contingency selection based on a pattern analysis ...

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1999 International Conference on Electric Power engineering, PowerTech Budapest 1999

作者： Rodrigues, M.S. Souza, J.C.S. Filho, M.B. Do Coutto Schilling, M.Th. Department of Electrical Engineering Applied Computing and Automation Fluminense Federal University - UFF Brazil

ISBN: (纸本)0780358368

During power system operation, it is important that load demands be met without violations of system operational constraints. Besides, for a given operating condition, the system should be capable of resisting the loss of any component, with no operational problems. Thus, contingency analysis plays an important role in real-Time power system security evaluation. Contingency analysis comprises the simulation of a set of contingencies in which the system behavior is observed. Each post- contingency scenario is evaluated in order to detect operational problems and the severity of violations. The most common operational problems are transmission equipment overloads and inadequate voltage levels at system buses. In static security analysis the identification of operational constraints violation involves the solution of an AC load flow problem, described by a set of nonlinear equations, that has to be solved for each post-contingency scenario. This procedure leads to a high computational effort, which is not desirable for real-Time applications. Some approximate models have been proposed for realtime power system static security evaluation [1J. These models reduce computational effort, but they may not classify system contingencies accurately. It is not possible to analyze system performance considering all contingencies. It is necessary to reduce the number of contingencies to only those that are more likely to occur. These form the critical contingencies set, which is in general defined based on system operation past experience and/or off-line simulations. The need for computational efficiency in real-Time contingency analysis can make not possible the analysis even for the critical contingencies set. Then, it becomes necessary to select in the critical set the contingencies that can really lead the system to an emergency state, with operational constraints violations. It is important to note that, as system operating conditions change, the harmful contingencies may als

关键词： Neural networks

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