• Journal of the Korea Society of Computer and Information
• /
• v.23 no.4
• /
• pp.65-70
• /
• 2018

This paper describes a effective information compressor algorithm for the fourth industrial technology. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because input images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a effective information algorithm for variable environment variable under outdoor is proposed, which apply the Kalman Estimation Modeling and adaptive threshold on pixel level to separate foreground and background images from current input image. In results, the better SNR of about 3dB~5dB and about 10%~25% noise distribution rate in the proposed method. Furthermore, it was showed that the moving objects can be detected on various shadows under outdoor and better result Information.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.49 no.4
• /
• pp.219-225
• /
• 2000

This paper presents the shape optimization considering the uncertainty of design variable to find robust optimal solution that has insensitive performance to its change of design variable. Stochastic finite element method (SFEM) is used to treat input data as stochastic variables. It is method that the potential values are series form for the expectation and small variation. Using correlation function of their variables, the statistics of output obtained form the input data distributed. From this, design considering uncertainty of design variables.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.41 no.8
• /
• pp.883-892
• /
• 1992

In order to remove the assumption of full state availability which is one of the major difficulties with the practical realization of variable structure control system (VSCS), an output feedback variable structure control scheme for multivariable systems is proposed. The proposed output feedback VSCS is composed of a switching surfaces with dynamic structure and a new output feedback control input that can be constructed by using conventional output feedback control input design methodologies. With the proposed scheme, the practical realization of VSCS for the systems with unmeasurable states and for high order systems that conventional schemes cannot be applied is possible. Simulation results show that proposed scheme is a viable method to achieve the desired control performance, for example, good transient response, robustness against process parameter variations and external disturbance without measuring all the state variables.

• Proceedings of the IEEK Conference
• /
• 2001.06c
• /
• pp.185-188
• /
• 2001

In this paper, a cascade fuzzy control method is proposed, which presents a robustness of the effect of disturbances, and in which the number of rules of the controller increase linearly instead of exponentially with the number of input variables. The proposed fuzzy control method is composed of cascade structure. Each stage has a state and a change of state, and one consequent control variable, and previous consequent control variable is an input of next stage. Simulation of the proposed controller, which is applied to the linear and nonlinear system as SISO (single-input single-output) system, showed that the proposed control method has a good control performance and robustness of disturbances compared with a conventional fuzzy control method.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1883-1887
• /
• 1991

Identification theory for linear discrete system has been presented by a great many reference, but research works for identification of continuous-time system are less than preceding identification. In fact, a great man), systems for engineering are continuous-time systems, hence, research for identification of continuous-time system has important meaning. This paper offers the following results: 1. Corresponding relations for the parameters of continuous-time model and discrete model may be shown, when single input-output system has general characteristic roots. 2. To do identification of single variable continuity linear system with stability constraints from samples of input-output data, it is necessary to use optimization with stability constraints. 3. Main results of this paper may be explained by a simple example.

• Nuclear Engineering and Technology
• /
• v.31 no.3
• /
• pp.257-266
• /
• 1999

A simplified statistical methodology is developed in order to both reduce over-conservatism of deterministic methodologies employed for PWR fuel rod internal pressure (RIP) calculation and simplify the complicated calculation procedure of the widely used statistical methodology which employs the response surface method and Monte Carlo simulation. The simplified statistical methodology employs the system moment method with a deterministic approach in determining the maximum variance of RIP The maximum RIP variance is determined with the square sum of each maximum value of a mean RIP value times a RIP sensitivity factor for all input variables considered. This approach makes this simplified statistical methodology much more efficient in the routine reload core design analysis since it eliminates the numerous calculations required for the power history-dependent RIP variance determination. This simplified statistical methodology is shown to be more conservative in generating RIP distribution than the widely used statistical methodology. Comparison of the significances of each input variable to RIP indicates that fission gas release model is the most significant input variable.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.27 no.6
• /
• pp.59-67
• /
• 2013

This paper presents a neural net type process model for enhancing learning compensation function in hot strip finishing rolling mill. Adequate input and output variables of process model are chosen, the proposed model was designed as single layer neural net. Equivalent carbon content, strip thickness and rolling speed are suggested as input variables, and looper's manipulation variable is proposed as output variable. According to simulation result using process data to show the validity of the proposed process model, neural net type process model's outputs give almost similar data to process output under same input conditions.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.51 no.8
• /
• pp.467-474
• /
• 2002

In this paper, a wind power simulator is designed and implemented. To realize the torque of wind blade, a DC motor is used as a variable torque input device. An induction machine is used as a generator of which speed is controlled to maintain the optimal tip speed ratio during wind speed change. Input torque of system is controlled by armature current of DC motor and speed is controlled by generator control unit using field oriented control algorithm. Various control algorithms such as MPPT, soft start up, the simulator reactive power control, can be developed and tested using the simulator.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.5
• /
• pp.950-960
• /
• 2010

In this paper, a multi-input multi-output(MIMO) integral variable structure system with an integral-augmented sliding surface is designed for the improved robust control of uncertain multivariable system under the matched persistent disturbance. To effectively remove the reaching phase problems, the integral augmented sliding surface is proposed. Then for its design, the eigenstructure assignment technique is introduced to. To guarantee the designed performance against the persistent disturbance, the stabilizing control for multi-input system is also designed to generate the sliding mode on the integral sliding surface. The stability of the global system together with the existence condition of the sliding mode are investigated and proved for the case of multi input system in the presence of uncertainty and disturbance. The reaching phase is completely removed in proposed MIMO VSS by satisfying the two requirements. An example and computer simulations will be present for showing the usefulness of algorithm.

• Proceedings of the IEEK Conference
• /
• 2002.07b
• /
• pp.786-789
• /
• 2002

A recurrent artificial neural network (ANN) model is developed to simulate hydrocarbon recovery process at petroleum-contaminated site. The groundwater extraction rate, vacuum pressure, and saturation hydraulic conductivity are selected as the input variables, while the cumulative hydrocarbon recovery volume is considered as the output variable. The experimental data fer establishing the ANN model are from implementation of a multiphase flow model for dual phase remediation process under different input variable conditions. The complex nonlinear and dynamic relationship between input and output data sets are then identified through the developed ANN model. Reasonable agreements between modeling results and experimental data are observed, which reveals high effectiveness and efficiency of the neural network approach in modeling complex hydrocarbon recovery behavior.