• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.263-268
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• 2001

A new control scheme s proposed for the control of reactive batch distillation (RBD) column. A nonlinear wave model captures the essential dynamic behavior of the RBD process. The proposed control scheme is based on both Generic Model Control(GNC) and nonlinear wave model. The control scheme uses a profile position of the column as a controlled variable. Ethanol esterification process using RBD is chosen as an example process. Tight control of the distillate purity is obtained with the use of the proposed control scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.403-410
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• 1999

In this study, a parallel algorithm has been developed that can quickly solve the optiaml control problem of large-scale dynamic systems. The algorithm adopts the sequential quadratic programming methods and achieves domain decomposition-type parallelism in computing sensitivities for search direction computation. A silicon wafer thermal process problem has been solved using the algorithm, and a parallel efficiency of 45% has been achieved with 16 processors. Practical methods have also been investigated in this study as a way to further speed up the computation time.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.115-120
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• 1993

It is difficult to establish a mathematical furnace model and automatic-fumace control because of the difficulty in direct measurement of the inner condition of a blast furnace. To solve this problem, we has developed and actually operated a blast furnace operation control system using artificial intelligence tool to be applied to the blast furnace process computer system. Since this system has a function of automatic Treat level control, higher practicality has been proved than the previous guidance-level expert system. This paper introduces an outline of the system and the result of application.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.246-255
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• 1998

This paper presents a novel method for real-time malfunction detection of plasma etching process using EPD signal traces. First, many reference EPD signal traces are collected using monochromator and data acquisition system in normal etching processes. Critical points are defined by applying differentiation and zero-crossing method to the collected reference signal traces. Critical parameters such as intensity, slope, time, peak, overshoot, etc., determined by critical points, and frame attributes transformed signal-to symbol of reference signal traces are saved. Also, UCL(Upper Control Limit) and LCL(Lower Control Limit) are obtained by mean and standard deviation of critical parameters. Then, test EPD signal traces are collected in the actual processes, and frame attributes and critical parameters are obtained using the above mentioned method. Process malfunctions are detected in real-time by applying SPC(Statistical Process Control) method to critical parameters. the Real-time malfunction detection method presented in this paper was applied to actual processes and the results indicated that it was proved to be able to supplement disadvantages of existing quality control check inspecting or testing random-selected devices and detect process malfunctions correctly in real-time.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.51-65
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• 2002

This paper presents a design method of the neural network-based controller using an indirect adaptive control method to deal with an intelligent control for chaotic nonlinear systems. The proposed control method includes the identification and control Process for chaotic nonlinear systems. The identification process for chaotic nonlinear systems is an off-line process which utilizes the serial-parallel structure of multilayer neural networks and simple state space neural networks. The control process is an on-line process which uses the trained neural networks as the system model. An error back-propagation method was used for training of identification and control for chaotic nonlinear systems. The performance of the proposed neural network controller was evaluated by application to the Duffing equation and the Lorenz equation, and the proposed controller was compared with other neural network-based controllers by computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.268-271
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• 2004

This paper describes the development of a fuzzy logic control based on PID controller to improve the performances of the control system using conventional PID controller for the cascade process control systems. The structure of the proposed control system consists of two fuzzy-based PID controllers. One is used to eliminate the input disturbances of the inner loop and the other is used to regulate output response of the outer loop. The fuzzy PID design is derived from the linear-time continuous function of the conventional PID controller. The performance of the proposed controller is verified by MATLAB/SIMULINK simulation. Results of simulation studies demonstrates the outstanding of the control system using fuzzy-based PID controller in terms of reduced overshoot and fast response compared with the conventional PID controller.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.620-625
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• 2008

The $H_{\infty}$ entropy in $H_{\infty}$ control theory is discussed based on investigating information transmission in continuous-time linear stochastic systems. It is proved that the stabilizing feedback does not change the time-average information transmission between system input and output, and the $H_{\infty}$ entropies of open- and closed-loop stable transfer functions are bounded by mutual information rate between input and output in the open-loop system. Furthermore, a new $H_2$ upper bound for $H_{\infty}$ entropy is introduced with a numerical example. Thus the $H_{\infty}$ entropy of a stable transfer function is sandwiched between $H_2$ norms of the original system and a static feedback system.

• Journal of Korea Society of Industrial Information Systems
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• v.1 no.1
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• pp.111-125
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• 1996

This paper presents a statistical process control(SPC) system in the electronic parts manufacturing process. In this system, an SPC method is integrated into the automated inspection technology on a real time base. It shows how the collected data can be analyzed with the SPC to provide process information. also presented are stuided of subpixel image processing technology to improve the accuracy of parts mearements , and the cumulative-sum(CUSUM) control chart for fraction defectives.An application of the developed system to connector manufacturing process as a part of computer integrated manufacturing (CIM) is presented.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1265-1270
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• 1990

A prototype integrated system and its theories for distributed SISO control structure synthesis of complete chemical plants is developed. The scope of this work includes control structure synthesis not only of simple units with unspecified control loops but also of the complex process at preliminary and basic design stage. Hierarchical approach and dual-decomposition strategy (that is multi-layer decomposition and multi-echelon decomposition) is applied to this system. Because automatic control structure synthesis of complex plants is a problem defined as a series of knowledge-intensive tasks within multiple spaces, the established methodology is complemented by not only techniques from knowledge-based expert systems but also shortcut and rigorous control theories. This system is used for education of control designers, process engineers, operators and students as well as for operability studying, in-line and on-line process control structure synthesis.

• Journal of Computing Science and Engineering
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• v.2 no.4
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• pp.394-411
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• 2008

The data in automation and control systems can be achieved not only from different field devices but also from different OPC (OLE for Process Control) servers. However, current OPC clients can only read and decode the simple data from OPC servers. They will have some problems to acquire structured data and exchange the structured data. In addition to the large network control systems, the OPC clients can read, write, and subscribe to thousands of data points from/to OPC servers. Due to that, the most important factor for building a high performance and scalable industrial control system is the ability to transfer the process data between server and client in the most efficient and fastest way. In order to solve these problems, we propose a means to implement the OPC DA (Data Access) server supporting the OPC complex data, so that the OPC DA clients are able to read and decode any type of data from OPC servers. We also propose a method for caching the process data in large industrial control systems to overcome the limitation of performance of the pure OPC DA system. The performance analysis and discussion indicate that the proposed system has an acceptable performance and is feasible in order for applying to real-time industrial systems today.