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World Congress on Intelligent control and Automation (WCICA)

作者： Xiong Luo Song Hu Zengqi Sun Xintao Qiu School of Information Engineering Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing Beijing China State Key Laboratory of Intelligent Technology and System Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China

Because of strong coupling, nonlinear, and time-varying characteristics, it is difficult to control complex spacecraft. By means of combining with controlled object dynamics and performance requirements, characteristic modeling and control approach is an effective way to solve this problem. Aimed at the flexible satellites described by using characteristic modeling approach, with the help of fuzzy rules, fuzzy dynamic characteristic modeling method and intelligent adaptive controller are designed to control this complex spacecraft. Meanwhile, based on the satellite system simulation platform, we validate the correctness and efficiency of the proposed modeling and control method by comparing with the simulation results of the other similar methods.

关键词： Adaptation model Laboratories Satellites Space vehicles Intelligent control Artificial intelligence Information science

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Dynamic modeling and tracking control of fuel filled space robotic system with flexible manipulators

Dynamic modeling and tracking control of fuel filled space r...

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International Symposium on Systems and control in Aerospace and Astronautics (ISSCAA)

作者： Xinxin Yang Xiong Luo Fuchun Sun Fengge Wu Huaping Liu School of Information Engineering Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing Beijing China State Key Laboratory of Intelligent Technology and System Department of Computer Science and TechnologyTsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China

In recent years, dynamics model and control of space robot system are the hot topics in the research field. In this paper, a new dynamics model and control strategy of space robotic system with a flexible manipulator and a liquid fuel tank are investigated. Based on Lagrange equation method, the dynamics model of the space robotic system coupling with liquid sloshing, flexibility vibration and base movement is derived. The elastic deflection of the flexible manipulator is described by the assumed mode method and equivalent mechanical model is adopted instead of liquid sloshing under the environment of low-gravity. The inverse dynamics control algorithm combined with PD control method is performed to solve the trajectory tracking problem. Some simulation results are given to verify the effectiveness of the proposed method.

关键词： Mathematical model Aerospace electronics Manipulator dynamics Equations Space vehicles

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Dynamical modeling and identification of a GnRH neuron

Dynamical modeling and identification of a GnRH neuron

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作者： Csercsik, Dávid Szederkényi, Gábor Hangos, Katalin M. Farkas, Imre Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Budapest Hungary Department of Endocrine Neurobiology Institute of Experimental Medicine HAS Budapest Hungary

ISBN: (纸本)9783902661494

GnRH neurons, as key elements of the reproductive neuroendocrine system, have important central regulating role in the dynamics of the hormonal cycle. A Hodgkin-Huxley type neural model is proposed in this paper, that takes into account up-to-date biological literature data related to ion channels. The proposed neuron model is highly nonlinear in parameters and the evaluation of the objective function is computationally flexpensive, therefore the asynchronous parallel pattern search (APPS) procedure has been used for identification. The model with high number of estimated parameters provides a qualitatively good fit of both voltage clamp and current clamp traces. © 2009 IFAC.

关键词： Neurons

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Model synthesis identification a Hodgkin-Huxley-type neuron model 10

Model synthesis identification a Hodgkin-Huxley-type neuron ...

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2009 10th European control Conference, ECC 2009

作者： Csercsik, David Szederkenyi, Gabor Hangos, Katalin M. Farkas, Imre Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Budapest Hungary Department of Endocrine Neurobiology Institute of Experimental Medicine HAS Budapest Hungary

ISBN: (纸本)9783952417393

GnRH neurons are key elements of the reproductive neuroendocrine system and play important central regulating role in the dynamics of the hormonal cycle. A conductance-based Hodgkin-Huxley model structure is proposed in this paper in the form of nonlinear ordinary differential equations that is able to take into account up-to-date biological literature data related to ion channels. Measurement data were available for parameter estimation, which are originated from laboratory experiments done in the Institute of Experimental Medicine of the Hungarian Academy of Sciences in the form of whole cell patch-clamp recordings. The proposed neuron model is highly nonlinear in parameters and the evaluation of the objective function is computationally expensive, therefore the asynchronous parallel pattern search (APPS) procedure has been used for identification which is a gradient-free optimization method that can handle linear equality and inequality constraints and has advantageous convergence properties. The model with high number of estimated parameters provides a qualitatively good fit of both voltage clamp and current clamp traces. © 2009 EUCA.

关键词： Parameter estimation

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A NEW NON-INVASIVE METHOD FOR VALVE STICTION DECTION USING WAVELET TECHNOLOGY

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Journal of Electronics(China) 2009年第5期26卷 673-680页

作者： Xu Zhanyang Charles Zhan Zhang Shunyi Institute of Information Network Technology Nanjing University of Posts ＆ Telecommunications Nanjing 210003 China Department of Computer Sciences~ Nanjing University of Information Science and Technology Nanjing 210044 China Advanced Process Control Research and Development Group Honeywell Process Solutions Phoenix AZ 85027 USA

In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavelet transform is used to decompose the data at different resolution scales. Based on the Lipschitz regularity theory, wavelet coefficients analysis across scales is performed to detect the jumps in the controlled variables. Adaptive wavelet de-noising is then applied to the data. Features of the valve stiction patterns are extracted from the de-noised data and the valve stiction probability is calculated.

关键词： Valve stiction Wavelet de-noising Jump Features extraction

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Dynamical Modeling and Identification of a GnRH neuron *

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IFAC Proceedings Volumes 2009年第12期42卷 425-430页

作者： Dávid Csercsik Gábor Szederkényi Katalin M. Hangos Imre Farkas Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute HAS Budapest Hungary Department of Endocrine Neurobiology Institute of Experimental Medicine HAS Budapest Hungary

GnRH neurons, as key elements of the reproductive neuroendocrine system, have important central regulating role in the dynamics of the hormonal cycle. A Hodgkin-Huxley type neural model is proposed in this paper, that takes into account up-to-date biological literature data related to ion channels. The proposed neuron model is highly nonlinear in parameters and the evaluation of the objective function is computationally expensive, therefore the asynchronous parallel pattern search (APPS) procedure has been used for identification. The model with high number of estimated parameters provides a qualitatively good fit of both voltage clamp and current clamp traces.

关键词： Neural dynamics Dynamic modelling Identification Nonlinear systems

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Comparison of rotary cement kiln identified models

Comparison of rotary cement kiln identified models

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International Conference on control and Automation (ICCA)

作者： G. Noshirvani A. Fatehi B. Araabi M. Shirvani M. Azizi ACER Markaz Branch Arak Iran Advanced Process Automation & Control Research group Electrical Engineering Department K.N. Toosi University of Technology Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran Chemical Engineering Department and member of Cement Research Center University of Science and Technology Tehran Iran Saveh Cement Company Saveh Iran

Rotary cement kiln is the main part of a cement plant that clinker is produced in it. Clinker is the main ingredient of cement. Continual and prolonged operation of rotary cement kiln is vital in cement factories. However, prolonged operation of the kiln is not possible and periodic repairs of the refractory lining would become necessary, due to non-linear phenomena existing in the kiln, such as sudden falls of coatings in the burning zone and probability of damages to the refractory materials during production. This is the basic reason behind the needs for a comprehensive model which is severely necessary for better control of this process. Such a model can be derived based on the mathematic analysis with consultation of expert operator experiences. In this paper both linear and nonlinear model are identified for rotary kiln of Saveh white cement factory. The linear model is introduced using Box-Jenkins structure. The results of the obtained model were satisfactory compared to some other linear models and can be used for designing adaptive or robust controllers. Also, nonlinear system identification via Neural Network technique is performed and its result was compared to linear models.

关键词： Kilns Production facilities Coatings Building materials process control Mathematical model Mathematics Programmable control Adaptive control Robust control

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Fuzzy case-based system for classification tasks on missing and noisy data

Fuzzy case-based system for classification tasks on missing ...

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8th International Conference on Hybrid Intelligent Systems, HIS 2008

作者： Rodríguez, Yanet Morell, Carlos Grau, Ricardo García, Maria M. De Baets, Bernard Department of Computer Science UCLV Cuba Department of Applied Mathematics Biometrics and Process Control Ghent University Belgium

ISBN: (纸本)9780769533261

Hybrid models combine different technologies to obtain a product that shares their advantages and minimizes their deficiencies. The solutions given by a Case-based System (CBS) rely on similar past experiences, which are commonly described in terms of both symbolic and continuous attributes. The Nearest Neighbor (NN) principle commonly followed to develop CBS for classification task proceeds from the assumption that similar cases have similar solutions, having the definition of the distance (similarity) function a central attention for obtaining a good accuracy on a given data set. This paper presents a hybrid model to solve classification tasks using NN principle but including generalized knowledge from the set of given instances to improve the performance in contrast to pure lazy learning algorithms. The Fuzzy Case-based System, referred as FuCiuS, interprets predictive numeric attributes in terms of fuzzy sets defining in a conceptually uniform way a one-dimensional (local) criterion to compare mixed and missing data. Experimental analysis show good performance for FuCiuS in comparison with well-known classifiers on missing and noisy data, while a more natural framework to include expert knowledge by using linguistic is provided guaranteeing both robustness and interpretable solutions. © 2008 IEEE.

关键词： Electric circuit breakers

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Fuzzy Case-Based System for Classification Tasks on Missing and Noisy Data

Fuzzy Case-Based System for Classification Tasks on Missing ...

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International Conference on Hybrid Intelligent Systems (HIS)

作者： Yanet Rodríguez Carlos Morell Ricardo Grau Maria M. García Bernard De Baets Department of Computer Science UCLV Cuba Department of Applied Mathematics Biometrics and Process Control Ghent University Belgium

Hybrid models combine different technologies to obtain a product that shares their advantages and minimizes their deficiencies. The solutions given by a case-based system (CBS) rely on similar past experiences, which are commonly described in terms of both symbolic and continuous attributes. The nearest neighbor (NN) principle commonly followed to develop CBS for classification task proceeds from the assumption that similar cases have similar solutions, having the definition of the distance (similarity) function a central attention for obtaining a good accuracy on a given data set. This paper presents a hybrid model to solve classification tasks using NN principle but including generalized knowledge from the set of given instances to improve the performance in contrast to pure lazy learning algorithms. The fuzzy case-based system, referred as FuCiuS, interprets predictive numeric attributes in terms of fuzzy sets defining in a conceptually uniform way a one-dimensional (local) criterion to compare mixed and missing data. Experimental analysis show good performance for FuCiuS in comparison with well-known classifiers on missing and noisy data, while a more natural framework to include expert knowledge by using linguistic is provided guaranteeing both robustness and interpretable solutions.

关键词： Classification algorithms Distance measurement Accuracy Artificial neural networks Correlation Fuzzy sets Noise measurement

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Decentralized Robust PI controller Design For An Industrial Utility Boiler - An IMC Method

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IFAC Proceedings Volumes 2008年第2期41卷 14235-14240页

作者： Horacio Jose Marquez Batool Labibi Tongwen Chen Advanced Process Automation and Control (APAC) Research Group K. N. Toosi University of Technology Tehran Iran Electrical and Computer Engineering Department University of Alberta Edmonton Canada

This paper presents a scheme for designing a robust decentralized PI controller for an industrial utility boiler system. First, a new method for designing robust decentralized PI controllers for uncertain LTI MIMO systems is presented. Sufficient conditions for closed-loop stability and diagonal dominance of a multivariable system are given. For each isolated subsystem a first order approximation is obtained. Then, achieving robust stability and closedloop diagonal dominance is formulated as local robust performance problems. It is shown by selecting time constants of the closed-loop isolated subsystems appropriately, these local robust performance problems are solved and the interactions between closed-loop stabilized subsystems are attenuated. The internal model control (IMC) method is used to design local PI controllers. The suggested design strategy is applicable to unstable systems as well. Thereafter, the nonlinear model of an industrial utility boiler is linearized about its operating points and the nonlinearity is modeled as uncertainty for a nominal LTI MIMO system. Using the new proposed method, a decentralized PI controller for the uncertain LTI nominal model is designed. The designed controller is applied to the real system. The simulation results show the effectiveness of the proposed methodology.

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