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IEEE International Conference on Electronics, Circuits and Systems (ICECS)

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

This work presents dominant pole design (DPD) methodology, one MATLAB implementation of DPD and its usage. DPD for PI and PID controllers is derived, and on this basis MATLAB toolkit for three-pole method (3PM) has been developed. The least squares procedure for finding functional dependence of PID controller parameters on process parameters is described. This least squares procedure has been applied to the first order process with dead time (FODT) obtained functional dependence, expressed through tuning formulas, is presented. Performance of PID controller tuned with 3PM tuning formulas is compared to the performance of PID controller tuned with integral criteria derived tuning formulas. Observed characteristics of DPD method are given at the end of the paper.

关键词： Three-term control control systems Design methodology MATLAB Equations Automatic control Least squares methods Process control Industrial control State feedback

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Milestone report coordinating committee on computer control 15th

Milestone report coordinating committee on computer control

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15th World Congress of the International Federation of Automatic control, 2002

作者： Verbruggen, Henk B. Park, Jaehyun Halang, Wolfgang Irwin, George Zalewski, Janusz Faculty of Information Technology and Systems Delft University of Technology Delft Netherlands Department of Automation Engineering Inha University Incheon Korea Republic of Faculty of Electrical Engineering Fern Universität Hagen Germany Intelligent Control and Systems Group School of Electrical and Electronic Engineering Queen's University Belfast United Kingdom Department of Electrical and Computing Engineering University of Central Florida Orlando United States

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Neurofuzzy model based l/sub /spl infin// predictive control of nonlinear CSTR system

Neurofuzzy model based l/sub /spl infin// predictive control...

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IEEE Conference on control Technology and Applications (CCTA)

作者： Q. Wu Y.J. Wang Q.M. Zhu K. Warwick Department of Control Science and Engineering CNCS Huazhong University of Science and Technology Wuhan China Faculty of Engineering Computing and Mathematics University of Western England Bristol UK Department of Cybernetics University of Reading Reading UK

In this paper the nonlinear dynamics of a continuously stirred tank reactor (CSTR) are modelled with a neuro-fuzzy network, so that a predictive control strategy is developed based on the l/sub /spl infin// norm performance. Stability of the closed loop system is proved that the system is stable if each local linear control system is closed loop stable. The pH control in neutralisation process within the CSTR was simulated to indicate that the control performance is superior to that from quadratic predictive control.

关键词： Continuous-stirred tank reactor Predictive models Predictive control Nonlinear dynamical systems Inductors Fuzzy neural networks Stability Closed loop systems control systems Process control

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Complexity reduction in MPC for stochastic max-plus-linear systems by variability expansion

Complexity reduction in MPC for stochastic max-plus-linear s...

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IEEE Conference on Decision and control

作者： T.J.J. van den Boom B. De Schutter B. Heidergott Control Systems Engineering Faculty of Information Technology and Systems Delft University of Technnology Delft Netherlands Department of Mathematics and Computing Science Eindhovan University of Technology Eindhoven Netherlands

Model predictive control (MPC) is a popular controller design technique in the process industry. Conventional MPC uses linear or nonlinear discrete-time models. Previously, we have extended MPC to a class of discrete event systems that can be described by a model that is "linear" in the max-plus algebra. In our previous work we have considered MPC for the perturbations-free case and for the case with noise and/or modeling errors in a bounded or stochastic setting. In this paper we consider a method to reduce the computational complexity of the resulting optimization problem, based on variability expansion. We show that the computational load is reduced if we decrease the level of 'randomness' in the system.

关键词： Stochastic systems Predictive models Predictive control Electrical equipment industry Industrial control Discrete event systems Algebra Stochastic resonance Computational complexity Optimization methods

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Overshoot controlled servo system synthesis using bode plot and its application to PM brushless DC motor drive

Overshoot controlled servo system synthesis using bode plot ...

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International Workshop on Advanced Motion control (AMC)

作者： P. Crnosija Z. Ban R. Krishnan Faculty of Electrical Engineering and Computing Department of Control and Comp. Eng. in Automation University of Zagreb Zagreb Croatia The Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Blacksburg VA USA

The design of current and speed controllers remains to a large extent a mystery to many engineers in the motor drives field. An attempt is made in this paper to simplify the design of the current and speed controllers using Bode plots. This paper outlines the theoretical background behind the techniques of symmetric optimum and dominant time constant compensation methods. The techniques are compared and contrasted using the overshoot and phase margin criteria. An application of these techniques to controller design for permanent magnet brushless DC motor (PMBDCM) drive system is made and verified with simulation. In order to apply these techniques to PMBDCM drive for the design of the current and speed controllers, the model of the motor drive is given for the benefit of the reader. The current and speed controller synthesis of a PMBDCM drive is achieved with the presented technique. Simulation results demonstrate for reference (current or speed) changes, symmetric optimum and dominant time compensation methods perform similarly. But for a load torque disturbance, the adverse effect on the speed is compensated faster only with the symmetric optimum method.

关键词： control system synthesis Servomechanisms Automatic control Brushless DC motors Frequency domain analysis Motor drives control systems DC motors Network synthesis Electric variables control

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MILESTONE REPORT COORDINATING COMMITTEE ON COMPUTER control

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IFAC Proceedings Volumes 2002年第1期35卷 217-225页

作者： Henk B. Verbruggen Jaehyun Park Wolfgang Halang George Irwin Janusz Zalewski Faculty of Information Technology and systems Delft University of Technology Delft the Netherlands Department of Automation Engineering Inha University Inchon Korea Faculty of Electrical Engineering Fern Universität Hagen Germany Intelligent Control and Systems Group School of Electrical and Electronic Engineering Queen's University Belfast UK Department of Electrical and Computing Engineering University of Central Florida Orlando USA

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Software quality knowledge discovery: a rough set approach

Software quality knowledge discovery: a rough set approach

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： S. Ramanna J.F. Peters T. Ahn Department of Business Computing University of Winnipeg Winnipeg MAN Canada Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada Intelligent Information Control & System Lab School of Electrical & Electronic Engineering Wonkwang University Iksan South Korea

This paper presents a practical knowledge discovery approach to software quality and resource allocation that incorporated recent advances in rough set theory, parameterized approximation spaces and rough neural computing. In addition, this research utilizes the results of recent studies of software quality measurement and prediction. A software quality measure quantifies the extent, to which some specific attribute is present in a system. Such measurements are considered in the context of rough sets. This research provides a framework for making resource allocation decisions based on evaluation of various measurements of the complexity of software. Knowledge about software quality is gained when preprocessing during which, software measurements are analyzed using discretization techniques, genetic algorithms in deriving reducts, and in the derivation of training and testing sets, especially in the context of the rough sets exploration system (RSES) developed by the logic group at the Institute of Mathematics at Warsaw University. Experiments show that both RSES and rough neural network models are effective in classifying software modules.

关键词： Software quality Software measurement Resource management Rough sets Logic testing Set theory Algorithm design and analysis Genetic algorithms Software testing System testing

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A software engineering approach to constraint programming systems

A software engineering approach to constraint programming sy...

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Asia-Pacific Conference on Software engineering

作者： K.B.K. Ng Chiu Wo Choi M. Henz Advanced Application Technologies Honeywell Automation and Control Solutions ACS Laboratory USA Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong China School of Computing National University of Singapore Singapore

Constraint programming (CP) systems are useful for solving real-life combinatorial problems, such as scheduling, planning, rostering and routing problems. The design of modern CP systems has evolved from a monolithic to an open design in order to meet the increasing demand for application-specific customization. It is widely accepted that a CP system needs to balance various design factors such as efficiency versus customizability and flexibility versus maintenance. This paper captures our experience with using different software engineering approaches in the development of constraint programming systems. These approaches allow us to systematically investigate the different factors that affect the performance of a CP system. In particular we review the application of reuse techniques, such as toolkits, framework and patterns, to the design and implementation of a finite-domain CP system.

关键词： Software engineering Knowledge based systems Software systems Application software Engines Computer industry Software algorithms Information systems System software Software quality

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A general updating rule for discrete Hopfield-type neural network with delay

A general updating rule for discrete Hopfield-type neural ne...

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17th International Joint Conference on Artificial Intelligence, IJCAI 2001

作者： Qiu, Shenshan Tsang, Eric C.C. Yeung, Daniel S. Wang, Xizhao Dept. of Computing Hong Kong Polytechnic University Hong Kong Department of Automatic Control Engineering South China University of Technology Guangzhou 510640 China

In this paper, the Hopfield neural network with delay (HNND) is studied from the standpoint of regarding it as an optimized computational model. Two general updating rules for network with delay (GURD) are given based on Hopfield-type neural networks with delay for optimization problems and characterized dynamic thresholds. It is proved that in any sequence of updating rule modes, the GURD monotonously converges to a stable state of the network. The diagonal elements of the connection matrix are shown to have an important influence on the convergence process, and they represent the relationship of the local maximum value of the energy function with the stable states of the networks. All ordinary DHNN algorithms are instances of GURD. It can be shown that the convergence conditions of GURD may be relaxed in the context of applications, for instance, the condition of nonnegative diagonal elements of the connection matrix can be removed from the original convergence theorem. New updating rule mode and restrictive conditions can guarantee the network to achieve a local maximum of the energy function.

关键词： Hopfield neural networks

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Automatic generation of digital filters by NN based learning: An application on paper pulp inspection

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6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001

作者： Campoy-Cervera, Pascual Munoz-García, David F. Pena, Daniel Calderón-Martínez, José A. Department of Automatic Control Electrical Engineering and Industrial Computing Universidad Politecnica de Madrid C/ Jose Gutierrez Abascal 2 Madrid28006 Spain Instituto Tecnologico de Aguascalientes SEP CONACYT Mexico

ISBN: (纸本)9783540422372

This paper presents an implementation of a digital filtering inspection system applied on a paper pulp sheet production process. The automation of the inspection phase is particularly critical during this process and its solution is highly complex. The system is based on neural network learning, allowing a compromise between resolution and processing speed. The experimental results demonstrating the use of this algorithm for the visual detection of defects in images obtained from a real factory environment are presented. These results show that the developed learning method generates filters that fulfil the required inspection standard. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Inspection

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