• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.8
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• pp.495-497
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• 2005

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a neural network used for identification of the process dynamics of s signal input and signal output system and it was shown that this method offered superior capability over the conventional back propagation algorithm. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident. This paper goal estimate input signal about controller using neural networks.

• Journal of Korean Society for Quality Management
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• v.30 no.3
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• pp.186-194
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• 2002

In this paper we introduce formulae for estimating the failure rate of a large scaled software by using the Bayesian rule when a black-box random testing which selects an element(test case) at random with equally likely probability, is performed. A program or software can be treated as a mathematical function with a well-defined (input)domain and range. For a large scaled software, their input domains can be partitioned into multiple subdomains and exhaustive testing is not generally practical. Testing is proceeding with selecting a subdomain, and then picking a test case from within the selected subdomain. Whether or not the proportion of selecting one of the subdomains is assumed probability, we developed the formulae either case by using Bayesian rule with gamma distribution as a prior distribution.

• Journal of Korean Society for Quality Management
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• v.33 no.3
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• pp.135-148
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• 2005

This paper considers a six sigma project for reducing the project costs through project risk management. The project follows a disciplined process of five phases: define, measure, analyze, improve, and control. A risk management process map is used to identify process input and output variables. Seven key process input variables are selected by using C&E diagram and X-Y matrix and finally four vital few input variables are selected by the related statistical analysis. The optimum alternatives of the vital few input variables are obtained by the method of PUGH matrix. The process is running on control plan and we obtained substantial project cost reductions in early stage of the control phase.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1946-1950
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• 2011

This paper deals with an input device without the touch. The existing touch screens have some problems such as the week durability by frequent contact and the high cost by complex hardware configuration. In this paper, a non-touch input device is proposed to overcome these problems. The proposed method uses a skin color generated by the HCbCr color model and a hand region obtained by the labeling technique. In Addition, the skeleton model is employed to improve the recognition performance of the hand motion. Finally, the experiment results show the applicability of the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1223-1229
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• 2009

The performance of Radial Basis Function Neural Networks depends on setting up the Radial Basis Functions over the input space which are the important design procedure of Radial Basis Function Neural Networks. The existing method to initialize the location of the radial basis functions over the input space is to use the conditional fuzzy C-means clustering. However, the researchers which are interested in the conditional fuzzy C-means clustering cannot get as good modeling performance as they expect because the conditional fuzzy C-means clustering cannot project the information which is extracted over the output space into the input space. To compensate the above mentioned drawback of the conditional fuzzy C-means clustering, we apply a fuzzy K-nearest neighbors approach to project the auxiliary information defined over the output space into the input space without lose of the information.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.109-116
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• 2008

Model matching problem of asynchronous sequential machines is addressed in this paper. The main topic is to design a corrective controller such that the closed-loop behavior of the asynchronous sequential machine can follow a given model, i.e., their models can be "matched" in stable states. In particular, we assume that the considered asynchronous machine suffers from the presence of an input disturbance that can cause undesirable state transitions. The proposed controller can realize both model matching and elimination of the adverse effect of the input disturbance. Necessary and sufficient condition for the existence of a corrective controller that solves model matching problem is presented. Whenever controller exists, algorithms for their design are outlined and demonstrated in a case study.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.11
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• pp.59-65
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• 2007

A new optimal state feedback and disturbance feedforward control design in the sense of minimizing $L_2$-gain from disturbance to control output is proposed for disturbance attenuation of systems with bounded control input and measurable disturbance. The controller is derived in the framework of linear matrix inequality(LMI) optimization. A gain scheduled state feedback and disturbance feedforward control design is also suggested to improve disturbance attenuation performance. The control gains are scheduled according to the proximity to the origin of the state of the plant and the magnitude of disturbance. This procedure yields a stable linear time varying control structure that allows higher gain and hence higher performance controller as the state and the disturbance move closer to the origin. The main results give sufficient conditions for the satisfaction of a parameter-dependent performance measure, without violating the bounded control input condition.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.591-597
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• 2009

The problem of controlling a finite-state asynchronous sequential machine is examined. The considered machine is governed by input/output control, where access to the state of the machine is not available. In particular, disturbance inputs can infiltrate into the asynchronous machine and provoke unauthorized state transitions. The control objective is to use output feedback to compensate the machine so that the closed-loop system drive the faulty asynchronous machine from a failed state to the original one. Necessary and sufficient condition for the existence of appropriate controllers are presented in a theoretical framework. As a case study, the closed-loop system of an asynchronous machine with the proposed control scheme is implemented in VHDL code.

• Journal of the Korean Society of Industry Convergence
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• v.2 no.1
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• pp.53-59
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• 1999

Input shaping technique has been used as a simple method of controlling vibration. With the conventional methods previously proposed by several authors, the frequency range that shows a good performance is restricted. When the designed frequency being different from the natural frequency of a system, the performance of control degrades remarkably. This paper introduced a new technique that uses digital IIR filter to control vibration. This technique has robustness for changing of parameter. In order to prove this we applied input shaping method to 2 axial overhead crane.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.8
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• pp.836-846
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• 1990

This paper presents a Static Var Compensator (SVC) system compensating the reactive power for power system, which consists of a voltage type Pulse Width Modulation (PWM) converter and a reactance linking the converter to the source. The system drives the four quadrant modes. The system determines the magnitude of the input voltage, and then compares it with the magnitude of the source voltage by regulating the phase of the SVC about the source. Therefore, the system generates leading compensation currents when the input voltage is larger than the source in magnitude, and lagging compensation currents for smaller input voltage. Reactive power about voluntary load in power system is smoothly compensated by those compensation currents, and also power factor of source is improved. Furthermore, the SVC system using PWM method may improve the source current waveforms by eliminating the 5th and 7th harmonic components from the input voltages.