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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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development of gauge control technology on tandem cold rolling mill combined with pickling line

SEAISI Quarterly (South East Asia Iron and Steel Institute)

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SEAISI Quarterly (South East Asia Iron and Steel Institute) 2008年第3期37卷 48-52页

作者： Sano, Kenichi Kobayashi, Masanori Morimoto, Yoshio Yanagi, Shusuke Murakami, Akira Process Engineering Development Section Kakogawa Works Kobe Steel Ltd. Kakogawa Japan Mechanical Working Research Section Technical Development Group Kobe Steel Ltd. Kobe Japan Control Technology Research Section Technical Development Group Kobe Steel Ltd. Kobe Japan

In 1972, the tandem cold mill (TCM) at Kakogawa Works was started up as 5-stand batch type mill. In 1999, to respond the customers' severe request for gauge accuracy, the multi valuable automatic gauge control system (MVAGC) was installed and high accuracy of gauge control has been achieved. In 2002, to improve the productivity and the quality of cold-rolled products, the TCM line was combined with the pickling line and the threading and tailing off operations do not have been required. Before the combination, the mill operator corrected the pass schedule to apply MVAGC at threading. After that, the mill operator could not find operating time to correct the pass schedule calculated by the process computer, and the MVAGC was not usually applied. In order to use the MVAGC at the combined pickling and tandem cold mill, we have reconstructed the pass schedule setting method and the prediction model of rolling load for the pass schedule setting. As a result, MVAGC has been applied form head to tail of coil and off-gauge length has been successfully reduced. This paper describes the outline of the MVAGC system, the newly developed pass schedule setting method, prediction model of rolling load and the actual operation in TCM.

关键词： Cold rolling

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Influence of moisture uptake in porous PAr film on electrical properties

Influence of moisture uptake in porous PAr film on electrica...

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24th Session of the advanced Metallization Conference 2007, AMC 2007

作者： Nakamura, N. Matsunaga, N. Watanabe, K. Miyajima, H. Enomoto, Y. Okada, N. Shibata, H. Advanced BEOL Technology Department Center for Semiconductor Research and Development Semiconductor Company Toshiba Corporation Process and Manufacturing Engineering Center Semiconductor Company Toshiba Corporation Semiconductor Technology Development Division Semiconductor Business Group Sony Corporation Advanced Device Development Division NEC Electronics Corporation 8 Shinsugita-cho Isogo-ku Yokohama Kanagawa 235-8522 Japan

ISBN: (纸本)9781558999923

In PAr/SiOC hybrid dual damascene structure, low-k polyarylene (PAr) films applied as trench layer material were damaged by plasma process and the damaged films absorbed moisture easily. The phenomenon was similar to that in the case of SiOC films applied as via layer material. It is confirmed that the moisture uptake degraded via properties. To achieve good electrical properties in the case of using porous PAr films, it is necessary to minimize the process damage. Optimization of metal dummy pattern is found to be one of the solutions to the issue of PAr damage and moisture uptake. © 2008 Materials research Society.

关键词： Moisture

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Disturbance Rejection in Neural Network Model Predictive control

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IFAC Proceedings Volumes 2008年第2期41卷 3527-3532页

作者： Alireza Fatehi Houman Sadjadian Ali Khaki-Sedigh Ali Jazayeri Advanced Process Automation and Control (APAC) Research Group Faculty of Electrical Eng. K. N. Toosi University of Technology Tehran Iran

Neural Network Model Predictive control (NN-MPC) combines reliable prediction of neural network with excellent performance of model predictive control using nonlinear Levenberg-Marquardt optimization. It is shown that this structure is prone to steady-state error when external disturbances enter or actual system varies from its model. In this paper, these model uncertainties are taken into account using a disturbance model with iterative learning which adaptively change the learning rate to treat gradual effect of the model mismatch differently from the drastic changes of external disturbance. Then, a high-pass filter on error signal is designed to distinguish disturbances from model mismatches. Practical implementation results as well as simulation results demonstrate good performance of the proposed control method.

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An experimental comparison of adaptive controllers on a pH neutralization pilot plant

An experimental comparison of adaptive controllers on a pH n...

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IEEE India Conference (INDICON)

作者： Ehsan Peymani Alireza Fatehi Pouya Bashivan Ali Khaki Sedigh Advanced Process Automation & Control (APAC) Research Group K.N. Toosi University of Technology Tehran Iran

Inherent nonlinearity of pH processes causes that they are recognized as an appropriate test bench for evaluation of advanced controllers. Because of special characteristics of them, it is evident that adaptive controllers outperform others. This paper presents a comparison between a conventional adaptive controller and a switching multiple-model adaptive one in both regulation and disturbance rejection points of view. A disturbance rejection supervisor is designed to improve the performance of the adaptive controllers in the presence of unmeasured disturbances. A laboratory scale pH process is used as an application example.

关键词： Programmable control Adaptive control process control Automatic control Power system modeling Chemical processes Nonlinear control systems control design Wastewater Automation

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H∞ and QFT robust control designs for level control plant

H∞ and QFT robust control designs for level control plant

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IEEE India Conference (INDICON)

作者： Y. Kouhi B. Labibi A. Fatehi R. Adlgostar Advanced Process Automation and Control (APAC) Research Group K.N. Toosi University of Technology Tehran Iran

In this paper two robust controllers are designed for a practical process trainer level plant. The system nonlinearity, time delay and change of parameters are the main problems in design of a desired controller for this plant. To design a controller, the linear models of the system and the disturbance models at different operating points are derived. Then, a parametric uncertainty profile is obtained by system identification strategies which is used in QFT control design. Indeed, for H infin control design a multiplicative unstructured model is extracted from the parametric uncertainty. All constraints in control design, disturbance rejection and control signal are derived. Based on these constraints, appropriate controllers are determined. To improve robust performance mu-synthesis with DK iteration is used. Finally all results are compared by applying the different controllers to the plant.

关键词： Robust control Level control Uncertainty Valves control design process control control systems Pressure control Automatic control Phase frequency detector

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Multiple-model control of pH neutralization plant using the SOM neural networks

Multiple-model control of pH neutralization plant using the ...

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IEEE India Conference (INDICON)

作者： Pouya Bashivan Alireza Fatehi Ehsan Peymani Advanced Process Automation and Control (APAC) Research Group Department of Control Engineering K.N. Toosi University of Technology Tehran Iran

A multiple-model adaptive controller is developed using the self-organizing map (SOM) neural network. The considered controller which we name it as multiple controller via SOM (MCSOM) is evaluated on the pH neutralization plant. An improved switching algorithm based on excitation level of plant has also been suggested for systems with noisy environments. Identification of pH plant using SOM is discussed and performance of the multiple-model controller is compared to the self tuning regulator (STR) controller.

关键词： Neural networks Automatic control Adaptive control Clustering algorithms Switches Programmable control Mathematical model State feedback Performance analysis Estimation error

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Nonlinear identification and MIMO control of a laboratory helicopter using genetic algorithm

Nonlinear identification and MIMO control of a laboratory he...

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IEEE India Conference (INDICON)

作者： H. Tahersima A. Fatehi Advanced Process Automation & Control (APAC) research group Faculty of Electrical Engineering Khaje Nasir Toosi University of Technology Tehran Iran

Closed loop identification of nonlinear model and control of a laboratory helicopter using genetic algorithm is proposed in this paper. The derived model has a nonlinear structure. Using the previous results of the physical modeling of the studied plant, a nonlinear model is considered based on the physical dynamics of the system. However, there is no need to perform numerous physical experiments to estimate the model parameters. Instead, genetic algorithm as a nonlinear optimization technique is used to obtain the parameters of the model. Therefore, the advantage of both modeling and identification methods are employed. In the next step, the parameters of a multi input-multi output (MIMO) PID controller for the derived model will be tuned by GA using the obtained nonlinear model as a simulator of the plant. Applying the controller to both the real plant and the simulation model, the accuracy of the model and the performance of the controller is examined. The results demonstrate that the achieved model accurately fits to the behavior of the real plant and the controller designed based on this model, can control the real system appropriately.

关键词： MIMO Laboratories Helicopters Genetic algorithms Parameter estimation Automatic control Mathematical model Electronic mail Nonlinear dynamical systems control system synthesis

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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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Robust Predictive PI controller Based on First-Order Dead Time Model

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IFAC Proceedings Volumes 2008年第2期41卷 5808-5813页

作者： F. Arousi U. Schmitz R. Bars R. Haber Dept. of Automation and Applied Informatics Budapest University of Technology and Economics MTA-BME Control Research group Dept. of Advanced Process Control Shell Rheinland Refinery Köln/Wesseling Germany Inst. of Chemical Process Engineering and Plant Design University of Applied Science Cologne Germany

Predictive control algorithms compute the manipulated variable minimizing a cost function considering expected future errors. PI control algorithms can be equipped with predictive properties. Simple predictive control algorithms are derived using approximation of an aperiodic process by a first-order model with dead time. Applying a noise model the robustness properties of the algorithm are enhanced considering plant-model mismatch. The noise filter is considered as a design parameter. Simulation examples demonstrate the behavior of the predictive PI algorithm and the robustifying effect of the noise filter.

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