• Journal of Power Electronics
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• v.5 no.3
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• pp.198-205
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• 2005

The mechanical system of a drive can often be modeled as a two- or three-mass-system. The load is coupled to the driving motor by a shaft able to perform torsion oscillations. For the automatic tuning of the control, it is necessary to know the mathematical description of the system and the corresponding parameters. As the manpower and setup-time necessary during the commissioning of electrical drives are major cost factors, the development of self-operating identification strategies is a task worth pursuing. This paper presents an identification method which can be utilized for the assisted commissioning of electrical drives. The shaft assembly can be approximated as a two-mass non-rigid mechanical system with four parameters that have to be identified. The mathematical background for an identification procedure is developed and some important implementation issues are addressed. In order to avoid the excitation of the system with its natural resonance frequency, the frequency response can be obtained by exciting the system with a Pseudo Random Binary Signal (PRBS) and using the cross correlation function (CCF) and the auto correlation function (ACF). The reference torque is used as stimulation and the response is the mechanical speed. To determine the parameters, especially in advanced control schemes, a numerical algorithm with excellent convergence characteristics has also been used that can be implemented together with the proposed measurement procedure in order to assist the drive commissioning or to achieve an automatic setting of the control parameters. Simulations and experiments validate the efficiency and reliability of the identification procedure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.745-753
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• 2010

Many studies using RFID which can identify the movement of targeted objects has been conducted actively. In this paper, we propose improved tagging method to check exactly the amount of fish feed by the aquaculture tank in a land-based aquaculture farm and design the RFID feeding system to perform auto feeding history. Also, we implement the prototype system which it includes development program for auto-identification and auto-recording and self-made RFID feeding cart equipped the weight device, RFID reader, control module and display device.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.545-550
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• 2004

Recent natural disasters like flooding and slope collapse have shown the need for natural risk management system, as they endanger directly public health and cause severe damages on the national economy. In order to improve the efficiency of risk management systems, this management system based on AANN(Auto-Associative Neural Network)is proposed in this paper. AANN can be effectively used for identification of abnormal data and data compression. The proposed AANN-based risk management system collects and stores measurement data from sensors and transmits them to remote server for web-monitoring. Generally, it is desirable to transmit the compressed data instead of raw data in normal state. However, if dangerous situation happens, rapid tramission of measurement data should be required. These requirements are easily satisfied by using AANN. In order to verify the feasibilities of the proposed system, The AANN-based risk management system is applied to slope collapse monitoring system.

• International Journal of Aeronautical and Space Sciences
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• v.3 no.1
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• pp.86-94
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• 2002

The initial alignment of inertial platform for navigation system was considered. An adaptive filtering technique is developed for the system with unknown and varying sway disturbance. It is assumed that the random sway motion is the second order ARMA(Auto Regressive Moving Average) model and performed parameter identification for unknown parameters. Designed adaptive filter contain both a Kalman filter and a self-tuning filter. This filtering system can automatically adapt to varying environmental conditions. To verify the robustness of the filtering system, the computer simulation was performed with unknown and varying sway disturbance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.438-444
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• 1997

Recently, optical disk drives are increasingly demanded to have higher speed as well as high information density, especially for applications like CD-ROM drives. To this end, improvement of their optical pick-up structure and control is recognized the very challenging issue. In this paper, the 2-D motion of the pick-up is first analytically modelled to identify the cause and effect of the troublesome cross coupling between auto-focusing and tracking directions. Subsequently, the overall system equations are derived to include the dynamics of the related components in the auto-focusing servo system. While its unmeasurable parameters being estimated by the least square error method, a simple but decent linear model can be obtained within its operating frequency range. To design the high speed and robust positional servo controller, the design specifications are detailed and H$\sub$.inf./ control method is employed based on the simple model. Using the pickup in a commercial 8 fold speed CD-ROM drive as an example, performance of the designed controller is verified by realtime experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.555-565
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• 1999

The optimal identification algorithm of fuzzy systems is presented for rule-based fuzzy modeling of nonlinear complex systems. Nonlinear systems are expressed using the identification of structure such as input variables and fuzzy input subspaces, and parameters of a fuzzy model. In this paper, the rule-based fuzzy modeling implements system structure and parameter identification using the fuzzy inference methods and hybrid structure combined with two types of optimization theories for nonlinear systems. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. The proposed hybrid optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Here, a genetic algorithm is utilized for determining initial parameters of membership function of premise fuzzy rules, and the improved complex method which is a powerful auto-tuning algorithm is carried out to obtain fine parameters of membership function. Accordingly, in order to optimize fuzzy model, we use the optimal algorithm with a hybrid type for the identification of premise parameters and standard least square method for the identification of consequence parameters of a fuzzy model. Also, an aggregate performance index with weighting factor is proposed to achieve a balance between performance results of fuzzy model produced for the training and testing data. Two numerical examples are used to evaluate the performance of the proposed model.

• Journal of Platform Technology
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• v.11 no.3
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• pp.56-67
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• 2023

Recently, de-identification of personal information, which has been a long-cherished desire of the data-based industry, was revised and specified in August 2020. It became the foundation for activating data called crude oil[2] in the fourth industrial era in the industrial field. However, some people are concerned about the infringement of the basic rights of the data subject[3]. Accordingly, a development study was conducted on the Batch De-Identification Tool, a personal information de-identification automation tool. In this study, first, we developed an image labeling tool to label human faces (eyes, nose, mouth) and car license plates of various resolutions to build data for training. Second, an object recognition model was trained to run the object recognition module to perform de-identification of personal information. The automated personal information de-identification tool developed as a result of this research shows the possibility of proactively eliminating privacy violations through online services. These results suggest possibilities for data-based industries to maximize the value of data while balancing privacy and utilization.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.797-803
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• 2012

Proportional solenoid valves are a modulating type that can control the displacement of valves continuously by means of electromagnetic forces proportional to the solenoid coil current. Because the solenoid-type modulating valves have the advantages of fast response and compact design over air-operated or motor-operated valves, they have been gaining acceptance in chemical and power plants to control the flow of fluids such as water, steam, and gas. This paper deals with the auto tuning of the position controller that can provide the proportional and integral gain automatically based on the dynamic system identification. The process characteristics of the solenoid valve are estimated with critical gain and critical period at a stability limit based on implemented relay feedback, and the controller parameters are determined by the classical Ziegler-Nichols design method. The auto-tuning algorithm was verified with experiments, and the effects of the operating point at which the relay control is activated as well as the relay amplitude were investigated.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.10a
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• pp.46-50
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• 1989

Methods for the estimation of the coefficient matrices in the equation of motion for a linear multi-degree-of-freedom structure arc studied. For this purpose, the equation of motion is transformed into an auto-regressive and moving average with auxiliary input (ARMAX) model. The ARMAX parameters are evaluated using several methods of parameter estimation; such as toe least squares, the instrumental variable, the maximum likelihood and the limited Information maximum likelihood methods. Then the parameters of the equation of motion are recovered therefrom. Numerical example is given for a 3-story building model subjected to an earthquake exitation.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.6
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• pp.928-934
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• 1998

This paper describes a fully digitalized driver for BLDC motors which is realized by a single chip microprocessor. The speed change can be done by using the signal obtained from the position detecting sensor and adjusting the pulse width at the input channel of power module. In order to establish a speed control system a repetitive control method is adopted to track a periodic refer-ence change in the BLDC motor system. The experimental results show accurate reference track-ing performance under the given periodic reference in the repetitive controller design.