• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.827-829
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• 1999

The identification of nonlinear system using Extended GMDH(EGMDH) is studied in this paper. The proposed EGMDH algorithm is based on GMDH(Group Method of Data handling) method and its structure is similar to Neural Networks. The each node of EGMDH structure utilizes several types of high-order polynomial such as linear, quadratic and cubic, and is connected as various kinds of multi-variable inputs. As the operating condition changes, the parameters of EGMDH will also change, so the proposed scheme by means of the EGMDH method is capable of adapting rapidly to the changing environment. The simulation result shows that the simple nonlinear process can be modeled reasonably well by the proposed method which are simple but efficient.

• Journal of Electrical Engineering and Technology
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• v.5 no.4
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• pp.597-605
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• 2010

This paper presents a contribution to parameter identification of a non-linear system using a new strategy to improve the genetic algorithm (GA) method. Since cost function plays an important role in GA-based parameter identification, we propose to improve the simple version of GA, where weights of the cost function are not taken as constant values, but varying along the procedure of parameter identification. This modified version of GA is applied to the induction motor (IM) as an example of nonlinear system. The GA cost function is the weighted sum of stator current and rotor speed errors between the plant and the model of induction motor. Simulation results show that the identification method based on improved GA is feasible and gives high precision.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.815-817
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• 1999

In this paper, we developed a fuzzy identification system to evaluate sensation of equilibrium objectively and quantitatively. By using caloric test. we estimated ECG(electro-cardiogram) and EOG(electro-oculogram), which were biomedical signals related to sensation of equilibrium, and used them as inputs of fuzzy identification system input. Fuzzy identification system analyzed the relationality between biomedical signals and sensation of equilibrium automatically, and evaluated it taking the co-relation between these signals into consideration.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.648-662
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• 2020

Bluetooth low energy (BLE) beacon is an actively push-to-broadcast electronic signal and can be used for object identification. This paper uses such beacon-based identification and Internet of Things (IoT) technologies for the elder health management service system to simplify the user interfaces and steps for preventive elder care. In the proposed system, an elder's family member, caregiver, or medical worker can conveniently and quickly record daily health management information. Besides, through the statistics and analysis of the data on the back end of the system, it is helpful for the elderly to refer to the data of daily care management and future management trends. Similarly, it is also an essential reference data for system maintenance and the new preventive health care services development.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1710-1713
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• 2003

We developed the synthetic library automation system. Developed system is comprised of two main units: an auto sorting system of books and a wireless management system. An auto sorting system is composed of a book return machine, a robot system, and an emergency bookshelf. A book return machine is operated by magnetic removal-revival. A wireless management system is development of RFID, or radio frequency identification, and is composed of a RF module and uninhabited return machine and a loss prevention system. The software for the synthetic library automation system is divided into three groups. We realized the developed automation system, and then get the features.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.5
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• pp.494-500
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• 2010

In this paper, we newly propose a wireless optical identification system and carried out experiments. A wireless optical identification system consists of a reader and a transponder. The configuration of a reader is the same as that of a transponder, which uses LED light as transmission media and detects the signal light with a solar cell. Optical alignment with a lens is not required because the absorption area of a solar cell is wide and flat, and it is very easy to attach a solar cell on the surface of an object. As the light wavelength does not interfere with radio frequency, a wireless optical identification system shows stable operation. In experiments, we realized a wireless optical identification system that automatically identifies the transponder data at a distance of 1 m using solar cells.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.3
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• pp.419-426
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• 2018

An useful and effective design method for the gas identification system is presented in this paper. The proposed gas identification system adopts hierarchical structure with two level rule base combining fuzzy sets with rough sets. At first, a hybrid genetic algorithm is used in grouping the array sensors of which the measured patterns are similar in order to reduce the dimensionality of patterns to be analyzed and to make rule construction easy and simple. Next, for low level identification, fuzzy inference systems for each divided group are designed by using TSK fuzzy rule, which allow handling the drift and the uncertainty of sensor data effectively. Finally, rough set theory is applied to derive the identification rules at high level which reflect the identification characteristics of each divided group. Thus, the proposed method is able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, we demonstrated the effectiveness of the proposed methods by identifying five types of gases.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.401-405
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• 1993

This paper presents a neuro adaptive control method for nonlinear dynamical systems based on artificial neural network systems. The proposed neuro adaptive controller consists of 3 layers artificial neural network system and parallel PD controller. At the early stage in learning or identification process of the system characteristics the PD controller works mainly in order to compensate for the inadequacy of the learning process and then gradually the neuro contrller begins to work instead of the PD controller after the learning process has proceeded. From the simulation studies the neuro adaptive controller is seen to be robust and works effectively for nonlinear dynamical systems from a practical applicational points of view.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.257-269
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• 2023

This paper presents a method for detecting faults in data obtained from the Automatic Identification System (AIS) of surface vessels. The data include latitude, longitude, Speed Over Ground (SOG), and Course Over Ground (COG). We derive two methods that utilize two models: a constant state model and a derivative augmented model. The constant state model incorporates noise variables to account for state changes, while the derivative augmented model employs explicit variables such as first or second derivatives, to model dynamic changes in state. Generally, the derivative augmented model detects faults more promptly than the constant state model, although it is vulnerable to potentially overlooking faults. The effectiveness of this method is validated using AIS data collected at a harbor. The results demonstrate that the proposed approach can automatically detect faults in AIS data, thus offering partial assistance for enhancing navigation safety.