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Teacon--a simulator for computer-aided teaching of process control

Computer Applications in engineering Education 1993年第4期1卷 307-307页

作者： Feyo, de Azevedo, S. Oliveira, F. Cardoso, A.C. Departamento de Engenharia Química Faculdade de Engenharia Universidade do Porto Rua dos Bragas 4099 Porto Codex Portugal Sebastião Feyo de Azevedo:is an Associate Professor of Chemical Engineering at the University of Porto. He is a licenciate in chemical engineering from the University of Porto (1973) and earned his PhD in Chemical Engineering from the University of Wales (1982). His interests are in the areas of modeling optimization and process control. Departamento de Electrónica Industrial Universidade do Minho Largo do Paço 4700 Braga Portugal Filomena Oliveira:is a graduate of the Chemical Engineering Department University of Porto 1986. She earned an MSc degree in Electrical Engineering from the same University (1991). She is currently Assistant-Lecturer in the Department of Industial Electronics University of Minho and is working toward her PhD in the control of biological reactors. Departamento de Engenharia Electrotécnica e dos Computadores Faculdade de Engenharia Universidade do Porto Rua dos Bragas 4099 Porto Codex Portugal Artur Capelo Cardoso:is a Lecturer at the Department of Electrical and Computer Engineering of the University of Porto. He earned his PhD from Syracuse University in 1987. His interests are in the areas of electronics signal processing and control.

“TEACON—TEAching control” is a PC-based package for computer-aided teaching of digital control of Single Input-Single Output (SISO) systems. A large variety of processes and control actions is possible. The program simulates systems in “real time” or faster than “real time.” process and control parameters can be changed on-line during runs. Set-point and process load can also vary according to predefined functions. The program computes the ISE, IAE, and ITAE indexes, allowing studies of controller tuning and performance. Other characteristics which enhance the simulation of real systems are the saturation of sensors and controller at 0 and 100%, the ability to superimpose noises on the measurements, and the possibility of defining dead-times associated with the measurements and with the process.

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An approach to the direct analysis of transient stability

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European Transactions on electrical Power 1993年第3期3卷 241-248页

作者： Djukanovic, M.B. Sobajic, D.J. Pao, Y.‐H. Miodrag B. Djukanovic (1959) received his B.S. M.Sc. and Ph.D. degrees in Electrical Engineering from the University of Belgrade/Yugoslavia in 1982 1985 and 1992 respectively specializing in electric power systems. In 1984 he joined the Electrical Engineering Institute “Nikola Tesla” in Belgrade where he was working on the scientific studies in the field of power systems planning operation and control. In 1985 and 1990 he was appointed as a research scholar at the Royal Institute of Technology Stockholm and Case Western Reserve University Cleveland Ohio. His major in- terests are in the area of power system analysis steady-state and dynamic security and application of neural networks in electric power systems. (Electrical Engineering Institute “Nicola Tesla” ul. Koste Glavinica 8A YU-11000 Belgrad T +3811/2351-619 Fax + 3811/2351-823) Dejan J. Sobajic (1949) received the B.S.E.E. and the M.S.E.E. degrees from the University of Belgrade/Yugoslavia in 1972 and 1976 respectively and the Ph.D. degree from Case Western Reserve University Cleveland Ohio in 1988. At present he is with the Department of Electrical Engineering and Applied Physics Case Western Reserve University Cleveland. He is also the Engineering Manager of A1 WARE Inc. Cleveland. His current research interests include power system operation and control neuralnet systems and adaptive control. He is a member of the IEEE Task Force on Neural-Network Applications in Power Systems and of the IEEE Intelligent Controls Committee. He is the Chairman of the International Neural-Networks Society Special Interest Group on Power Engineering. (Case Western Reserve University Department of Electrial Engineering and Computer Sciences Glennan Building Ohio 44 106 USA T + 1216/421-2380 Fax +1216/368-8776) Yoh-Han Pao (1922) has been a Professor of Electrical Engineering and Computer Science at Case Westem Reserve University (CWRU) Cleveland Ohio since 1967. He has served as chairman of the University's Electrical Engineering Department

The Transient Energy Function (TEF) method has been intensely investigated over the last decade as a reliable and accurate tool for transient stability assessment of multimachine power systems. In this paper we propose the Potential Energy Boundary Surface (PEBS) based method for direct analysis of transient stability. The critical value of transient energy and the Critical Clearing Time (T_CCT) are evaluated without the need for successive calculation and memorization of the system kinetic and potential energy values along the sustained fault trajectory. The method is used for determination of output features in the training phase of the neural‐net based transient security assessment. The proposed approach is tested on the well‐known ten‐generator New England test system demonstrating the validity and accuracy of obtained results. Copyright © 1993 John Wiley & Sons, Ltd.

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ACCURACY REQUIREMENTS FOR MEASUREMENT SYSTEMS WITH UNIFORM AND NORMAL ERRORS

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NAVAL ENGINEERS JOURNAL 1993年第1期105卷 66-69页

作者： SNOW, JM STUCKMAN, BE USHER, JS Jeffrey M. Snow:received his B.S. degree in mechanical engineering from the University of Washington in 1977. He has worked at Boeing Commercial Aircraft Company and Puget Sound Naval Shipyard. Since 1985 he has been at Naval Surface Warfare Center Crane Division (NSWCC). From 1987 to 1990 he was in charge of quality assurance configuration management and reliability for Aegis (SPY-1 and Mk-99) microwave tubes. He currently is in the Radar System Branch at NSWCC. He is a member of ASQC and ASME. His areas of interest include the use of statistics in process improvement efforts and objectively rating and rewarding suppliers for better quality. Bruce E. Stuckman:holds a Ph.D. degree in systems engineering from Oakland University where he also obtained M.S. and B.S. degrees in electrical and computer engineering. In 1992 Dr. Stuckman obtained his J.D. from the University of Louisville where he graduated cum laude. He is currently an associate in the patent and computer law department of Brooks & Kushman a law firm specializing in intellectual property and technology related causes. Prior to this he was an associate professor of both electrical engineering at the University of Louisville and a member of the Research Advisory Board of the South Central Bell Telecommunications Research Center. Dr. Stuckman is the author of over 75 published works in a variety of research areas including global optimization algorithms control systems communication and telecommunication systems and instrumentation electronics. He has served as a technical consultant to such organizations as Control Data Corporation General Electric General Motors Research Laboratories Gulf & Western AT&T Bell Laboratories ARCO Research and Technical Services and the U.S. Government and has been a frequent lecturer at national and international symposia. He is a senior member of IEEE and a member of ASNE Eta Kappa Nu Tau Beta Pi Sigma Xi and Phi Kappa Phi. John S. Usher Ph.D. P.E.:is an assistant professor of industrial engineering

Accuracy requirements are usually determined as a percentage of the specification range of the measured part or process. Setting accuracy requirements in this manner results in a wide and unpredictable range of false rejection and acceptance probabilities. This causes extra costs due to either: 1) over specification of measurement systems accuracy requirements;2) time, effort, retesting, and resolution of false rejections;or 3) system degradation caused by false acceptance of out-of-specification parts. Achieving a consistent and known risk of false acceptance is only possible by considering the measured process C(pk), the process's mean in relation to the center of the specification range, and the measurement system error distribution. This paper presents a method for calculating the probabilities of false rejection and false acceptance for a normal process which is measured with, alternately, uniform and normally distributed error. It is shown that under most conditions uniform error causes 20% to 30% higher false rejection and acceptance probabilities. Thus, knowledge of measurement error distribution could provide lower total production cost.

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NEURAL-NETWORK APPROACH TO SENSOR DESIGN

NEURAL-NETWORK APPROACH TO SENSOR DESIGN

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IEEE 1992 ULTRASONIC SYMP

作者： LEC, RM MUSAVI, MT PENDSE, HP AHMED, W Department of Electrical Engineering Industrial Process Control Sensor Systems(IPCoSS) Program University of Maine Orono 04469 United States Department of Chemical Engineering Industrial Process Control Sensor Systems(IPCoSS) Program University of Maine Orono 04469 United States

ISBN: (纸本)0780305620

One of the important tasks in sensor design is the development of a model for a sensing phenomena. Artificial neural networks are ideal for such a task because of their capability for representation of the mapping functions describing the processes and phenomena which are mathematically difficult or even intractable. We examined a radial basis function (RBF) neural network for modeling of acoustical properties of colloidal TiO₂ slurry. The colloidal slurry is a very complex multiphase medium. The RBF network with a set of local Gaussian functions was trained using the data from the earlier developed physical model of TiO₂ slurry. Next the TiO₂ neural model was used for a prediction of the TiO₂ particle size distribution. The resulting prediction accuracies of the RBF network was 99.8% for the data used in the training process and 88% for the data not used in the training. Compared to other available techniques neural networks can offer an effective and time efficient approach for the modeling of complex materials. © 1992 IEEE.

关键词： Titanium dioxide

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control Algorithms for Saturating Systems

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IFAC Proceedings Volumes 1992年第25期25卷 165-170页

作者： M. Huba P. Bisták M. Molnár Department of Automation and Control Faculty of Electrical Engineering STU CS-812 19 Bratislava Czechoslovakia

New type of predictive controllers for saturating systems is described. It relies on an analytical approximation of the controlled process by the I 2 -model. The closed-loop behavior may be prescribed by means of reference trajectories defined as optimal braking trajectories of the actual model as well as by choosing a time horizon for matching with these trajectories. The method essentially improves features of classical relay minimum time systems. It enables to modify their behavior in a similar way as using the pole assignment method and so to achieve a desired degree of robustness against structural and state perturbation. Taking into account saturation limits and parasitic time lags makes the task of tuning controller transparent and reliable which is illustrated by the example of positional servo control

关键词： Minimum time control linearization techniques saturation robustness d.c. motors position control

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Self-Organizing Fuzzy controller with Neural Network

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IFAC Proceedings Volumes 1992年第25期25卷 239-244页

作者： L. Jurišica M. Sedláček Department of Automation and Control Faculty of Electrical Engineering 3 Ilkovičova St. Bratislava 812 19 Czechoslovakia

The method for adjustment of fuzzy controller parameters is presented. In fuzzy control to he control signal s are generated by an appropriate inference mechanism from the linguistically expressedrule base. To refine the parameters of the rules it is necessary to have either a thorough insight into the dynamics of the overall system or to develop an appropriate adaptation mechanism. Such mechanism with Kohonen neural network like structure is presented and documented on the example of motion control system.

关键词： Fuzzy control Neural networks Learning systems Motor control Servomechanisms

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Implementation of Fuzzy controlled DC Servosystem

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IFAC Proceedings Volumes 1992年第29期25卷 107-112页

作者： L. Jurisica M. Sedlacek Silesian Technical University Faculty of Electrical Engineering Department of Automation and Control Ilkovjcova Street 3 CS 812 19 Bratislava Czechoslovakia

The fuzzy logic controller for the velocity d.c. servo system was designed. It was shown, that the system can successfully deal with the nonstationary moment of inertia and load torque and with the influence of flexible gearbox. The practical concept of implementation using the unique transfer function and a look-up-table of coefficients was introduced. Such method is simple and has low computational requirements.

关键词： Fuzzy control Motor control Robust control Robots control applications

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Parametric characterization of the spectrum of the electromyographic signal of the biceps during voluntary isometric contraction 35

Parametric characterization of the spectrum of the electromy...

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35th Midwest Symposium on Circuits and Systems, MWSCAS 1992

作者： Ele, Pierre Kwankam, S. Yunkap Souquet, J. Laboratoire d'Electronique et de Traitement du Signal Department of Electrical Engineering Ecole Nationale Superieure Polytechnique University of Yaounde B.P. 8390 Yaounde Cameroon Automation and Control Laboratory Department of Electrical Engineering Ecole Nationale Superieure Polytechnique University of Yaounde B.P. 8390 Yaounde Cameroon Laboratoire d'Electronique Mesure et Instrumentation Universite Claude Bernard LYON 1 43 Bd 11 nov. 1918 Villeurbanne69622 France

ISBN: (纸本)0780305108

The electromyographic (EMG) signal, which is used for exploration of neuromuscular functions, is often quantitatively characterized by the stricture of its spectrum. This stricture correlates with variations in the metabolic state of a muscle which lead to fatigue. In this paper, a quantitative measure is proposed for characterizing this stricture and thus the EMG spectrum. © 1992 IEEE.

关键词： Muscle

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A comparative study of neural vs. conventional methods for modeling and prediction

A comparative study of neural vs. conventional methods for m...

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IEEE International Symposium on Intelligent control (ISIC)

作者： J.D. Donne U. Ozguner Drive Control Systems Division AEG Automation Systems Corporation Pittsburgh PA USA Department of Electrical Engineering Ohio State Uinversity Columbus OH USA

Neural network and conventional methods for system modeling and prediction are discussed in a unified way. Both linear and nonlinear examples are used to show that by using a black-box approach, the methods are equivalent with the exception of the parametrization process. A comparison of neural network methods with an extended Kalman filter for the case of a nonlinear system demonstrates that neural methods require very few a priori assumptions about the underlying model structure. It is shown, using a flexible space structure example, that neural networks can more readily handle the problem of underparametrization than conventional techniques. In all cases, the neural implementations provide results that are at least as accurate as the conventional methods, where the figure of merit is the variance of the output error signal.< >

关键词： Predictive models Neural networks Finite impulse response filter Nonhomogeneous media Sun Supercomputers

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A Comparison of Three Nonlinear controller Designs Applied to a Non-Adiabatic First-Order Exothermic Reaction in a CSTR

A Comparison of Three Nonlinear Controller Designs Applied t...

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American control Conference (ACC)

作者： M. J. Piovoso K. A. Kosanovich V. Rokhlenko A. Guez Corporate Process Control Techinical Engineering E. l. Du Pont de Nemours and Company Inc. Wilmington DE USA Department of Electrical and Computer Engineering Drexel University Philadelphia PA USA

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