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IEEE International Symposium on Computer Aided control system Design (CACSD)

作者： M. Volker A. Liefeldt S. Engell C. Schmid Department of Biochemical and Chemical Engineering Universität Dortmund Dortmund Germany Institute of Automation and Computer Control Ruhr Universität Bochum Bochum Germany

LEARN2control is a new computer-based learning system, that can be used to deepen basic knowledge in control engineering by self-study in a project-oriented environment. The didactic concept aims at teaching the depen... 详细信息

关键词： Education control engineering Temperature control control systems Automatic control Educational institutions Knowledge engineering Chemical engineering Learning systems control system analysis

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Non linear system identification and control design using adaptive wavelet network

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IFAC Proceedings Volumes 2004年第13期37卷 507-512页

作者： H.R. Karimi B. Lohmann B. Moshiri P. Jabehdar Maralani Control and Intelligent Processing Center of Excellence. Department of Electrical and Computer Engineering Faculty of Engineering University of Tehran. Tehran. Iran Institute of Automation University of Bremen Otto-Hahn-Allee NW1 Bremen D-28359 Germany

This paper presents an application of wavelet networks in identification and control design for a class of non-linear dynamical systems. The technique of feedback linearization, supervisory control and H ∞ control are used to design an adaptive control law and also the parameters of the wavelet networks are adapted using a Lyapunov-based design. By some theorems, it will be proved that even in the presence of modelling errors, named network error, the stability of the overall identification scheme and the convergence of the network parameters and the boundedness of the state errors are guaranteed.

关键词： system Identification Supervisory control He control Stability Analysis Wavelet Network.

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Genetic algorithm for edge extraction of glomerulus area

Genetic algorithm for edge extraction of glomerulus area

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International Conference on Information and automation (ICIA)

作者： Jun Zhang Hong Zhu XueMing Qian Tao Huang Institute of Information and Automation Engineering Xi''an University of Technology Xi'an Shaanxi China Department of system integration Shannxi GLNPU Software Company Limited Xi'an Shaanxi China

ISBN: (纸本)0780386299

The automatic analysis of kidney-tissue image is an important subsystem in the computer aided diagnosis system of kidney disease. In this subsystem, the correct extraction of glomerulus is an important premise to the exact analysis of kidney-tissue image. A glomerulus edge extraction method based on genetic algorithm (GA) is proposed by considering complex characteristics of the image. Firstly, different scale binary images are obtained by adjusting the parameters of LOG filter. Secondly, the crude spline curve fitting for the glomerulus area boundary is got by genetic algorithm based on the small-scale binary image. Thirdly, elaborate adjustment of spline fitting curve is performed according to more boundary information of large-scale binary image to get the optimal spline curve. Finally, the glomerulus area can be extracted correctly according to the fitting curve. Experimental result indicates high precision of glomerulus edge extraction from the kidney-tissue image.

关键词： Genetic algorithms Curve fitting Data mining Filters Spline Pathology Image analysis Diseases Biopsy automation

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Performance assessment of model predictive control in industrial distillation column

Performance assessment of model predictive control in indust...

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World Congress on Intelligent control and automation (WCICA)

作者： Maying Yang Xiaoming Jin Fei Chen Automation Department Information Engineering College Zhejiang University of Technology Hangzhou China National Key Laboratory of Industrial Control Technology Institute of Advanced Process Control University of Zhejiang Hangzhou China

ISBN: (纸本)0780382730

A synthetical method of multivariable control system performance assessment is proposed in this paper, which uses multivariable minimum variance control (MVC) benchmark to determine the stochastic performance, and normalized multivariate impulse response (NMIR) curve as an alternative measure of performance to test the dynamic performance, and with the help of auto-correlation function (ACF) and cross-correlation function (CCF) to analyse if there are oscillations exist. The method is applied to assess the performance of multivariable predictive control system of industrial distillation column.

关键词： Predictive models Predictive control Industrial control Distillation equipment Electrical equipment industry control systems system performance Benchmark testing Stochastic systems Impulse testing

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Optimizing the structure of hierarchical mixture of experts using genetic algorithms

Optimizing the structure of hierarchical mixture of experts ...

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International IEEE Conference on Intelligent systems, IS

作者： D.A. Karras C.E. Vlitakis Y.S. Boutalis B.G. Mertzios Chalkis Institute of Technology Department Automation and Hellenic Open University Athens Greece Department Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Department of Automation Thessdoniki Institute of Technology Laboratory of Automatic Control Systems Thessaloniki Hellas and Democritus University Xanthi Greece

This study is an effort to give a practical solution in the problem of optimizing the structure of the hierarchical mixture of experts model, which is a natural extension of the associative Gaussian mixture of experts system. We present two novel methods for optimizing such structures using genetic algorithms. Special concern is taken for reducing the computational time so as to efficiently allow the structure to "grow" while it evolves with the genetic algorithm. The main contribution of the paper lies on the efficient, topologically oriented, representations of such architectures so as to be optimized through involving genetic algorithms.

关键词： Genetic algorithms Biological cells Optimization methods Neural networks Classification tree analysis automation Decision trees Expert systems Computer architecture Supervised learning

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Petri net-based design of modular supervisors for remotely human control systems

Petri net-based design of modular supervisors for remotely h...

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SICE Annual Conference

作者： Jin-Shyan Lee Meng-Chu Zhou Pau-Lo Hsu Department of Electrical & Control Engineering National Chiao Tung University Hsinchu Taiwan Department of Electrical & Computer Engineering New Jersey Institute of Technology Newark NJ USA Laboratory of Complex Systems & Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)4907764227

In an Internet-based control system, particular human operations may violate desired requirements and lead to destructive failure. For such human-in-the-loop systems, this paper extends the remote supervisory scheme by Lee and Hsu (2003) to a modular one so as to reduce the supervisor synthesis complexity. Also, remote human issued commands are guaranteed to meet required specifications. A rapid thermal process in semiconductor manufacturing systems is provided to show the practicability of the proposed approach.

关键词： Humans control systems Supervisory control Automatic control Internet control system synthesis Rapid thermal processing Error correction control engineering Intelligent systems

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Predicting the product yield profile and cracking degrees in an industrial ethylene pyrolysis furnace

Predicting the product yield profile and cracking degrees in...

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International Conference on control, automation, Robotics and Vision (ICARCV)

作者： Qiang Zhou Jie Zhang Yongmao Xu Institute of Process Control Department of Automation Tsinghua University Beijing Beijing China Centre for process Analytics and Control Technology School of Chemical Engineering & Advanced Materials University of Newcastle Newcastle-upon-Tyne UK

ISBN: (纸本)0780386531

This paper presents two soft-sensing models for predicting the product yields profile and the cracking degree of an ethylene pyrolysis furnace. The model based on single neural network with only one hidden layer trained by Levenberg-Marquardt algorithm with regularisation was first developed. It was found that the single neural network lack generalisation capability in that they can give undesirable performance when applied to unseen data. To improve the generalisation capability of the soft-sensing model, multi-model soft-sensors based on bootstrap aggregated neural networks with sequential training are used. In the sequential training of bootstrap aggregated networks, the first network is trained to minimise its prediction error whereas the rest of the networks are trained not only to minimise their prediction errors but also minimise the correlation among the trained networks. The overall output is obtained by combining all the individual networks. Application results show that the multi-model soft-sensors possess good generalisation capability in that they give good performance when applied to unseen data.

关键词： Furnaces Neural networks Process control Predictive models Petrochemicals Chemical industry automation Postal services Chemical analysis Automatic control

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Experimental Demonstration of Disturbance Suppression control with Novel Nonlinear Disturbance Predictor based on Reconstructed Attractor

Experimental Demonstration of Disturbance Suppression Contro...

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第4届国际电力电子及运动控制国际会议

作者： Nobutaka Bando Yoichi Hori Department of Electrical Engineering Division of Engineering University of Tokyo Ce-501 Institute of Industrial Science 4-6-1 Komaba Meguro Tokyo 153-8505 Japan Information & System Division Electrical Control System Engineering Institute of Industrial Science University of Tokyo Ce-501 Institute of Industrial Science 4-6-1 Komaba Meguro Tokyo 153-8505 Japan

In this paper, disturbance suppression control with a novel nonlinear disturbance predictor to be used for motion control system is proposed. By design of the novel disturbance predictor. we develop Disturbance Observer to realize disturbance feedback without time *** predictor is built from the reconstructed at-Iractor which is often used in chaos analysis. The reconstructed attractor consists of the lime series of disturbance and expresses the dynamics of disturbance. Due to the characteristics of the reconstructed altractor, it is not necessary to identify or model the dynamics of disturbance. Therefore the proposed method is especially effective to compensate the interference force of multiple axes robot manipulator, friction force and to on which contiol tends to be complicated in the conventional *** the proposed method, one-step-ahcad prediction can be realized by extension of the trajectory in the state space of disturbance intuitively. But in the reconstructed attaraclor, the order of the space can be selected arbitrarily as prediction is succeeded. Additionaly the state transition equation of disturbance is not *** verify the effectiveness of the prposed method, some simulation results using a double pendulum system are shown. In this simulation, though the chaotic interference force gives bad influence to the system, the proposed method can be succeeded in stabilizing the behavior of the double pendulum.

关键词： -robot manipulator reconstructed attractor nonlinear prediction

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Multiple models adaptive decoupling controller for a nonminimum phase system

Multiple models adaptive decoupling controller for a nonmini...

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Asian control Conference

作者： Xin Wang Shaoyuan Li Zhongjie Wang Yanxin Zhang Institute of Automation Shanghai Jiaotong University Shanghai China Shanghai Jiao Tong University Shanghai CN Department of Control Science and Engineering University of Tongji Shanghai China China

ISBN: (纸本)0780388739

For a nonminimum-phase system, when the parameters of the system change abruptly, a multivariable multiple models adaptive decoupling controller (MMMADC) is presented to improve the transient response. The controller is composed of multiple fixed controller models and two adaptive controller models. The fixed controller models are derived from the corresponding fixed system models directly and guaranteed to cover the controller parameter set, without partitioning the controller parameter set again. By the choice of the weighting polynomial matrix, it not only eliminates the steady-state error but also decouples the system. The global convergence is obtained and simulation examples are presented to illustrate that the derived MMMADC can improve the transient response and get the satisfied decoupling performance.

关键词： Programmable control Adaptive control control systems Power system modeling Transient response Automatic control Convergence control system synthesis Stability Adaptive algorithm

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Numerical Properties of a Polynomial Algorithm for Solving Scalar Rational Bezout Identity 1

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IFAC Proceedings Volumes 2004年第21期37卷 357-361页

作者： Jiří Lidinský Martin Hromčík Michael Šebek Department of Control Engineering Czech Technical University Prague Czech Republic Institute of Information Theory and Automation 182 08 Prague Czech Republic Centre for Applied Cybernetics Czech Technical University Prague Czech Republic

Numerical properties of a computational algorithm for the scalar Bezout identity in the ring of proper stable rational functions is studied in this paper. The method has been implemented in the MATLAB 6.5 computational environment using the pre-release version 3.0 of the Polynomnial Toolbox and exposed to extensive numerical testing. The results are summarized and some useful guidelines for using this well known algorithm are given.

关键词： polynomial design methods numerical algorithms Bezout equation

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