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International Workshop on Advanced Motion control (AMC)

作者： M. Fischer M. Tomizuka Institute of Automatic Control Laboratory of Control Systems and Process Automation Technical University of Darmstadt Darmstadt Germany Department of Mechanical Engineering University of California Berkeley Berkeley CA USA

High-accuracy positioning is applied in a variety of modern computer-controlled machines. The achievable precision is not only determined by the mechanical properties of the systems but strongly depends on the utilized control algorithms and the quality of the sensor signals. The objective of this paper is to demonstrate how alternative position sensors influence the performance of a robust digital tracking controller consisting of a disturbance observer in the velocity loop, a feedback controller in the position loop, and a zero phase error tracking controller as feedforward controller. Two different sensor systems for an x-y positioning table are considered. While a digital encoder is attached to the actuating motor, a laser interferometer with a significantly higher resolution directly measures the position of the compliantly coupled table. The latter case represents a noncollocated system. After introducing the hardware setup, both the system identification and the controller design are briefly reviewed. The impact of the measurement device on the control performance and the optimal choice of the controller parameters are investigated in extensive experiments.

关键词： Mechanical sensors Velocity control control systems Sensor systems Tracking loops Optimal control Application software Mechanical factors Robust control Digital control

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Extended Horizon Predictive control of Non-Linear Systems - Multi-Dimensional Optimisation and Suboptimal Solution

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IFAC Proceedings Volumes 1996年第8期29卷 57-62页

作者： Robert Haber Ruth Bars Department of Process Engineering Laboratory of Process Control Cologne Institute of Technology (Fachhochschule Köln) D-50679 Köln Betzdorfer Str. 2 Germany Department of Automation Technical University of Budapest H-1111 Budapest Goldmann Gy. tér 3 Hungary

Predictive control strategies have been proved effective and robust in practice. These algorithms were developed mainly for linear processes. The main idea is to determine the control signal minimising the deviation between a reference signal and the predicted process output in a given prediction horizon. A simplified version is one-step-ahead predictive control, where prediction horizon is restricted to one future point. Extended horizon control proposed by Ydstie (1984) is enlengthened one-step-ahead control which lets more time for the settling process than the dead time. Extended horizon predictive control strategy is derived here for a class of nonlinear systems. Some simulation results show the effect of the tuning parameters for the reference signal tracking performance of the nonlinear system.

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Adaptive Predictive control of Nonlinear Dynamic processes

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IFAC Proceedings Volumes 1995年第13期28卷 401-406页

作者： Robert Haber Ruth Bars Cologne Institute of Technology (Fachhochschule Köln) Department of Process Engineering Laboratory of Process Control D-50679 Köln Betzdorfer Str. 2 Germany. Department of Automation Technical University of Budapest H-1111 Budapest Goldmann Gy. tér 3 Hungary.

Predictive control algorithms determine a series of the control signal minimizing the deviation between the reference and the output signal in a given future horizon. The output of the plant to be controlled is predicted on the basis of a model, which can be linear or nonlinear, parametric or nonparametric. In adaptive control these process parameters are identified and the control signal is calculated taking the identified values into consideration. In the paper simulation results present some properties of adaptive predictive control. Robustness of the control algorithm is illustrated through control of a simple Wiener model . The relationship between the plant order and the prediction horizon is also mentioned. The promising results indicate that further systematic analysis is worthwhile.

关键词： nonlinear control predictive control adaptive control control algorithms parametric nonparametric models Volterra series

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Steady‐state security evaluation of electrical power systems by means of artificial neural network

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European Transactions on Electrical Power 1995年第2期5卷 91-97页

作者： Chiodo, E. Menniti, D. Testa, A. Picardi, C. Elio Chiodo (1959) received the degree in Electronics Engineering in 1985 and the Ph.D. degree in Computational Statistics both from the University of Naplefltaly. He is a Researcher at the Department of Electrical Engineering of the University of Naples and a member of the Italian Statistical Society. His areas of interest include probabilistic methods applied to electric power systems analysis. (University of Naples Fedrrico 11. Electrical Engineering Dept.via Claudio 21 1-80125 Naplefltaly T +3981/7683226 Fax+3981/2396897) Daniele Menniti (1958) received the degree in Electrical Engineering from the University of Calabria. Cosenzataly and the Ph.D. degree in Electrical Engineering from the University of NapleslItaly in 1984 and 1989 respectively. He is a researcher at the Electronic. Computer and Systems Science Department of the University of Calabria. Italy. Hiscurrent research interests concern electric power system analysis real-time control and automation. (University of Calabria Electronic Computer and Systems Science Dep. Arcavacataji Rende (CS). 1-87036 CosenzdItaly T +39984/494707. Fax +39984/4947 13) Alfredo Testa (1950) received the degree in Electrical Engineering from the University of Naples/Italy in 1975. He is an Associate Professor in Electrical Power Systems at the Department of Electrical Engineering of the University of Naples. He is engaged in researches on electrical power systems reliability and harmonic analysis. (University of Naples Federico 11. Electrical Engineering Dep. via Claudio '2 1 1-80 I25 NapleslItaly T + 39 8 I/7 68 3'2 11. Fax+3981/2396897) Ciro Picardi (1949) received the degree in Electronics Engineering from the University of Naples/Italy in 1975. He is currently Associate Professor in Process Control at the Department of Electronic Computer and System Science of the University of Calabria. Italy. His current research interests are in the area of electrical drives robotics neural networks and fuzzy control. (University of Calabria Electronic. Compu

An artificial‐neural‐network (ANN) application for steady‐state security evaluation of electrical power systems is presented. Such application is based upon a combined use of a multilayer back‐propagation neural network and of an opportune electrical system model, previously proposed by some of the authors. In the paper, the definition of steady‐state security and the problems arising from its on‐line evaluation are briefly recalled. Then, the ANN utilized is described with particular reference to the solutions adopted by the authors. Afterwards, some remarks on the system model utilized are reported. Finally, numerical applications on the AEP‐14 bus system are presented and the results obtained with different ANN configurations are analyzed. Copyright © 1995 John Wiley & Sons, Ltd.

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Permissive control of Boolean condition/event systems: Synthesis and limits

Permissive control of Boolean condition/event systems: Synth...

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IEEE International Symposium on Intelligent control (ISIC)

作者： S. Kowalewski H.-M. Hanisch Process Control Group (AST) Chemical Engineering Department University of Dortmund Dortmund Germany Automation Institute (INFAUT) Electrical Engineering Department Technical University Magdeburg Magdeburg Germany

This paper presents a synthesis method for logic controllers based on a discrete state model of the plant and a formal specification of the desired behavior in form of forbidden state sequences. We use Boolean condition/event systems as the basic modeling paradigm. The synthesis algorithm is specified with the help of Boolean differential calculus operators and realized using the Boolean analysis software XBOOLE. The resulting controller is permissive in the sense that it does not force state transitions in the plant. The approach is applied to a simple hatch process example which exhibits limits of a purely permissive control concept.< >

关键词： control system synthesis Force control control systems Programmable control Automatic control Logic Calculus automation process control Chemical engineering

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Multivariable Constrained Predictive control (With Application to High Performance Distillation)

Multivariable Constrained Predictive Control (With Applicati...

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American control Conference (ACC)

作者： D.J. Wilkinson M.T. Tham A.J. Morris Automation & Control Group Manufacturing Services Division Shell International Petroleum Company Limited The Hague Netherlands Department of Chemical and Process Engineering University of Newcastle Newcastle-Upon-Tyne UK

A multivariable constrained predictive controller is briefly described. Its objective function is solved via Singular Value Decomposition (SVD). Apart from being a numerically robust solution technique, the approach also provides useful on-line information which can be used to enhance the stability of the closed loop system. The performance characteristics of the algorithm are illustrated by applications to nonlinear simulations of two high purity distillation columns.

关键词： Predictive control Manufacturing automation Robust stability Cost function Automatic control Petroleum Chemical processes Chemical engineering Feedback control PROM

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Interactive power system data preparation and verification using a pc‐editor

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European Transactions on Electrical Power 1991年第3期1卷 149-152页

作者： Linke, K. Rumpel, D. Dip1.-Ing. Klaus Linke (1939) VDEis the director of the department "load dispatching and network operation" of Vereinigte Elektrizitatswerke Westfalen AG (VEW). DortmundGermany. After the study of electrical engineering at the Technical University of KarlsruhdGermany he started his professional career in an engineering-concern where he was responsible among others for investigations concerning the installation of process-computers in chemical plants. In 1968 he changed to VEW. Here in 1984 he took over his present position in which he is mainly engaged with the tasks of the management of the HV and EHV network and the power system control together with the problems concerning network automation incident to it. (Vereinigte Elektrizitatswerke Westfalen AG Hauptverwaltung Rheinlanddamm 24 W-4600 Dortmund 1 T +49 23 114 38-42 41) Dr.-Ing. Dieter Rumpel (1932) VDE is full professor and since 1978 head of the Power Systems Institute of Duisburg University Germany. He got his DiplAng. degree from the Technical University Munich and his Dr.-Ing. degree from the Technical University Berlin. Before his call to Duisburg he worked at Siemens AG for 23 years. (Universiiit-GHDuisburg Fachbereich Elektrotechnik PF 10 15 03 W-4100 Duisburg T 4 9 20 313 79-34 37)

For computerized power system operation, all objects of the network must be mapped in a data‐model. For this task, the „Grid Data Language” (GDL) does not apply format‐bound source data, but describes the objects using a format‐free source text. To handle such texts, an editing‐ and verification‐system was implemented. This paper reports its application when describing an extra‐high voltage network for use in a training simulator. In that way, the full content of a dispatcher EHV data‐model could be converted to GDL, requiring a work of 15 to 20 man‐days. Copyright © 1991 John Wiley & Sons, Ltd.

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Long-Range Predictive control of Nonlinear Systems on the Basis of the Hammerstein Model

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IFAC Proceedings Volumes 1990年第1期23卷 165-169页

作者： R. Bars R. Haber Department of Automation Technical University of Budapest Goldmann Gy. tér 3 Budapest Hungary Fachhochschule Köln Faculty of Plant and Process Engineering Köln FRG and Ruhr-University Faculty of Mechanical Engineering Department of Control Systems Bochum FRG

The unknown nonlinear process is approximated by the Hammerstein model, which is one of the natural expansions of the discrete convolution model to nonlinear systems· Because of the large number of the parameters an identification procedure with scalar convergence coefficients is recommended. The control task is to follow a reference model output predicted ahead in a given horizon· The present and future control activities during the prediction horizon are determined minimizing a functional of the error signal between the predicted values of the reference model and the system output. The control signal is assumed constant during the control horizon and the calculation is repeated in each control interval. Simulation results represent the robust behaviour of the control algorithms.

关键词： Nonlinear control systems predictive control nonparametric models adaptive control control theory

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MPCS - THE MANUFACTURING process-control SYSTEM

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AT&T TECHNICAL JOURNAL 1986年第4期65卷 35-45页

作者： DUNIETZ, IS HSU, JLC MCEACHERN, MT STOCKING, JH SWARTZ, MA TROMBLY, RM The authors Irwin S. Dunietz John L.C. Hsu Michael T. McEachern James H. Stocking Mark A. Swartz andRodney M. Tromblyare responsible for design and development of the Manufacturing Process Control System. Mr. Dunietz joined AT&T in 1980. He is a member of the technical staff in the Manufacturing Information Automation department at AT&T Engineering Research Center Princeton New Jersey. He received an A.B. in mathematics from Cornell University and an M.S.E. in computer science from Princeton University. Mr. Hsu who joined AT&T in 1970 is a department head in the Manufacturing Information Automation department at the Engineering Research Center. He received an M.S. in electrical engineering from the University of Missouri. Mr. McEachern joined AT&T in 1962 and is a supervisor in the 5ESS™ Line Unit Manufacturing department at AT&T Technologies in Oklahoma City Oklahoma. He is responsible for the manufacturing process control center in Oklahoma City which provides computerized support for all circuit pack manufacturing. Mr. Stocking who joined AT&T in 1975 is a supervisor in the Manufacturing Information Automation department at the Engineering Research Center. He received a B.S. in chemical engineering from Rensselaer Polytechnic Institute and a Ph.D. in chemical engineering from the University of California Berkeley. Mr. Swartz joined AT&T in 1980 and is a member of the technical staff in the Manufacturing Information Automation department at the Engineering Research Center. He received an A.B. in computer science from Cornell University and an M.S. in computer science from Rutgers—The State University. Mr. Trombly who joined AT&T in 19 78 is an assistant manager at the AT&T Merrimack Valley Works in Massachusetts. Previously he was a supervisor at the Engineering Research Center. He holds a B.S. in computers and systems engineering and an M.S.E.E. from Rensselaer Polytechnic Institute.

The central challenge of all manufacturing is making products to the right standards and delivering them at the right time. AT&T is upgrading its corporate and factory resource planning systems to improve control of day-to-day manufacturing. The Manufacturing process control System (MPCS), developed at the AT&T engineering Research Center (ERC), provides this support. MPCS connects the shop floor with production scheduling, accounting, product data archive, and engineering support systems.

关键词： PRODUCTION control

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