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作者： Schmitz, Ulrich Haber, Robert Bars, Ruth Shell Deutschland Oil Rhineland Refinery Department for Technology and Services Ludwigshafener Strasse l D-50389 Wesseling Germany University of Applied Science Cologne Institute of Process Engineering and Plant Design Betzdorfer Str. 2 D-50679 Cologne Germany Budapest Univ. of Technology and Economics Dept. of Automation and Applied Informatics MTA-BME Control Research Group Goldmann Gy.ter 3 H-1111 Budapest Hungary

ISBN: (纸本)9783902661661

On-off control is still widely used in the industry, especially for discontinuous actuators, e.g. compressors, steam turbines or furnace burners. Exact set-point control is not possible by an on-off controller. Lower and upper limits are defined for the control signal which should not be violated. For this predictive gap control quadratic and horizon dependent cost functions are defined. Traditional numerical optimization fails with longer prediction horizons, but a genetic algorithm can be effectively applied even for long horizons.

关键词： Actuators

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Data Mining Based Feedback Regulation in Operation of Hematite Ore Mineral processing Plant

Data Mining Based Feedback Regulation in Operation of Hemati...

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2009 American control Conference (ACC 2009)

作者： Jinliang Ding Qi Chen Tianyou Chai Hong Wang Chun-Yi Su Key Laboratory of Integrated Automation of Process Industry (Northeastern University) Ministry of Education and Research Center of Automation Northeastern University Shenyang 110004 China Control Systems Centre The University of Manchester Manchester M60 1QD UK Department of Mechanical Engineering Concordia University Montreal Quebec H3G 1M8 Canada

ISBN: (纸本)9781424445233

To deal with the variation of production operation of the mineral processing plant, the data-mining based feedback regulation strategy is proposed to compensate the open loop steady state setting of the production unit at the plant-wide level. Rough set and increment association rule learning are used for the feedback regulation rule extraction from the historical operation data. To realize the feedback compensator two steps are carried out: (1) Determining the variables to be compensated based on rough set, (2) Mining the compensation rules through the increment association rule learning and rough set. The efficiency of the proposed strategy is proven by the experiments.

关键词： Data mining Ores Minerals control systems Production Steady-state Association rules Optimal control Feedback loop State feedback

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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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Evolutionary optimization methods for predictive on-off control

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IFAC Proceedings Volumes 2009年第19期42卷 408-413页

作者： Ulrich Schmitz Robert Haber Ruth Bars Shell Deutschland Oil Rhineland Refinery Department for Technology and Services Ludwigshafener Strasse l D-50389 Wesseling Germany University of Applied Science Cologne Institute of Process Engineering and Plant Design Betzdorfer Str. 2 D-50679 Cologne Germany Budapest Univ. of Technology and Economics Dept. of Automation and Applied Informatics MTA-BME Control Research Group Goldmann Gy.ter 3 H-1111 Budapest Hungary

Abstract On-off control is still widely used in the industry, especially for discontinuous actuators, e.g. compressors, steam turbines or furnace burners. Exact set-point control is not possible by an on-off controller. Lower and upper limits are defined for the control signal which should not be violated. For this predictive gap control quadratic and horizon dependent cost functions are defined. Traditional numerical optimization fails with longer prediction horizons, but a genetic algorithm can be effectively applied even for long horizons.

关键词： predictive control on-off control discontinuous actuators genetic algorithms

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Identification of the primary circuit dynamics in a pressurized water nuclear power plant

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IFAC Proceedings Volumes 2008年第2期41卷 10640-10645页

作者： Csaba Fazekas Gábor Szederkényi Katalin M. Hangos Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences P.O. Box 63 H-1518 Budapest Hungary

This paper presents the results of the parameter estimation procedure for the primary circuit dynamics of a VVER-type nuclear power plant. The model structure is a low dimensional lumped nonlinear model published previously in Fazekas et al. [2007a]. The parameter estimation method uses the modular decomposition of the system model for obtaining physically meaningful initial parameter estimates. The final parameter estimates are computed using the integrated model.

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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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