• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.45 no.1
• /
• pp.60-66
• /
• 1996

Brushless DC(BLDC) motor have been increasingly used in machine tools and robotics applications due to the reliability and the efficiency. In control of BLDC motor, it is important to construct the controller which is robust to parameter variations and external disturbances. Variable structure controller(VSC) has been known as a powerful tool in robust control of time varying systems. In practical systems, however, VSC has a high frequency chattering which deteriorates system performances. In this paper, a binary controller(BC) which takes the form of VSC and MRAC combined is presented to solve this problem. BC consists of the primary loop controller and the external loop controller to change the gain of primary loop controller smoothly. So it can generate the continuous control input and is insensitive to parameter variations in the given domain. To confirm the validity, various investigations of control characteristics for various design parameters in a position control system of BLDC motor are carried out. (author). 11 refs., 18 figs., 1 tab.

• Proceedings of the KIPE Conference
• /
• 2007.07a
• /
• pp.391-393
• /
• 2007

The rotor speed and flux information is most important in the vector control. The accuracy of flux observers for induction machine inherently depends on parameter sensitivity. The control strategy is using online flux observer for flux estimation. In the proposed system, the speed control characteristics using a online flux observer control isn't affected by a load torque parameter disturbance. Simulation results are presented to prove the effectiveness of the adaptive sliding mode controller for the drive variable load of induction motor.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.3
• /
• pp.835-840
• /
• 2010

This study develops a variable structure controller using nonlinear surface instead of the fixed, which has been the robustness against parameter variations and extraneous disturbance during the reaching phase. reaching time of the system trajectory is faster than the fixed method. This proposed scheme has better performance than the conventional method in reaching time, parameter variation and extraneous disturbance. The effectiveness of the proposed control scheme is verified by simulation results.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.7
• /
• pp.1007-1013
• /
• 2012

Modeling of photovoltaic power systems is significant to analytically predict its dynamics in practical applications. This paper presents a novel modeling algorithm of such system by using probability and statistic theories. We first establish a linear model basically composed of Fourier parameter sets for mapping the input/output variable of photovoltaic systems. The proposed model includes solar irradiation and ambient temperature of photovoltaic modules as an input vector and the inverter power output is estimated sequentially. We deal with these measurements as random variables and derive a parameter learning algorithm of the model in terms of statistics. Our learning algorithm requires computation of an expectation and joint expectation against solar irradiation and ambient temperature, which are analytically solved from the integral calculus. For testing the proposed modeling algorithm, we utilize realistic measurement data sets obtained from the Seokwang Solar power plant in Youngcheon, Korea. We demonstrate reliability and superiority of the proposed photovoltaic system model by observing error signals between a practical system output and its estimation.

• Journal of the Korean Society of Physical Medicine
• /
• v.4 no.4
• /
• pp.249-255
• /
• 2009

Purpose：To investigate of gait component in Parkinson's Disease patient. Methods：participated Parkinson's Disease patient(n=12) and Normal adult(n=13). gait measure used by GaitRite. Results：SPSS for win version 12 was used for statistic analysis and independent t-test used to find between two groups. In the comparison of temporal parameter of gait between groups, the swing phase was significant decreased in Parkinson's groups, in the stance phase was significant increased in Normal groups, in the single support was significant decreased in Parkinson's groups and in the double support was significant increased in Parkinson's groups(p<.05). In the asymmetrical ratio of singele support was significant increased in Parkinson's groups(p<.05), and the swing phase and stance phase was significant increased in Parkinson's groups(p<.05). Conclusion：In the Parkinson's Disease patient gait showed temporal and spatial component variable changes comparison normal adult. therefore, it was seems to very important considerable at gait tranning in clinical intervention.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.11a
• /
• pp.666-669
• /
• 2004

Substructures position is considered as design parameter to obtain optimal structural changes to raise its dynamic characteristics. In conventional SDM (structural dynamics modification) method, the layout of modifying substructures position is first fixed and at that condition the structural optimization is performed by using the substructures size and/or material property as design parameters. But in this paper as a design variable substructures global translational and rotational position is treated. For effective structural modification the eigenvalue sensitivity with respect to that design parameter is derived based on measured frequency response function. The optimal structural modification is calculated by combining eigenvalue sensitivities and eigenvalue reanalysis technique iteratively. Numerical examples are presented to the case of beam stiffener optimization to raise the natural frequency of plate.

• Journal of the Semiconductor & Display Technology
• /
• v.16 no.2
• /
• pp.79-84
• /
• 2017

This paper outlines the Taguchi optimization methodology, which is applied to optimize cutting parameters in end milling when machining STS304 with TiAlN coated SKH59 tool under up and down end milling conditions. The end milling parameters evaluated are depth of cut, spindle speed and feed rate. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to analyze the effect of these end milling parameters. The Taguchi design is an efficient and effective experimental method in which a response variable can be optimized, given various control and noise factors, using fewer resources than a factorial design. An orthogonal array of $L_9(33)$ was used. The most important input parameter for cutting force, however, is the feed rate, and depending on the cutter rotation direction. Finally, confirmation tests verified that the Taguchi design was successful in optimizing end milling parameters for cutting force.

• Journal for History of Mathematics
• /
• v.37 no.1
• /
• pp.1-17
• /
• 2024

In this study, we identified the intellectual triggers for Bayesian inference and what key ideas contributed to its occurrence and discussed the practical implications of introducing Bayesian inference into the school mathematics curriculum by reflecting them. The results of the study show that the need for statistical inference about the parameter itself served as a trigger for the occurrence of Bayesian inference, and the most important idea for the occurrence of that inference was to regard the parameter itself as a probability variable rather than any fixed value. On the other hand, these research results suggest that the meaning of introducing Bayesian inference into the secondary mathematics curriculum is 'statistics education that expands the scope of uncertainty'.

• Proceedings of the KIEE Conference
• /
• 2002.07b
• /
• pp.1165-1168
• /
• 2002

This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for sensorless vector controlled induction motor drives. MRAS(Model Reference Adaptive System) is used for rotor speed estimation. When induction motor is continuously used long time. its electrical and mechanical parameters will change, which degrade the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. The proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using DS1102 board show the robustness of the proposed controller to parameter variations.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.9 no.4
• /
• pp.55-61
• /
• 1995

Variable structure control (VSC) can be used for the control of power plants required stability and robustness such as elevator control. It has no overshoot and is insensitive to parameter variations and disturbances in the sliding mode where the system structure is changed with the sliding surface in the center. But in the real system, VSC has a high frequency chattering which has a bad influence upon the control system proformances. In this paper, to alleviate the high frequency chattering, a binary controller (BC) with inertial type external loop is implemented by DSP and applied to position control of brushless DC motor. Binary controller has external loop to generate the continuous control input with the flexible variation of primary loop gain. Thus it has the property of chattering alleviation in addition to advantages of the conventional variable structure control.