• Journal of IKEEE
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• v.23 no.4
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• pp.1353-1359
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• 2019

It is presented in this paper that the static output feedback (SOF) pole-assignment problem of some linear time-invariant systems can be completely resolved by parametrization in real Grassmann space. For the real Grassmannian parametrization, the so-called Plucker matrix is utilized as a linear matrix formula formulated from the SOF variable's coefficients of a characteristic polynomial constrained in Grassmann space. It is found that the exact SOF pole assignability is determined by the linear independency of columns of Plucker sub-matrix and by full-rank of that sub-matrix. It is also presented that previous diverse pole-assignment methods and various computation algorithms of the real SOF gains for 2-input, 2-output, 4^th order systems are unified in a deterministic way within this real Grassmannian parametrization method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.108.2-108
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• 2001

This paper presents the application of adaptive phase-locked loop (adaptive PLL) technique to control the process variable of the process control system. The adaptive algorithm is related to the error. When the error of the system is changed, the adaptive gain will be directly changed according to the error. If the value of the adaptive gain is large, the value of the error will be large. In this experiment, the reference input is 50% step input. The experimental result in controlling the first order lag process by the adaptive PLL shows that the response of the controlled system has no overshoot, short rise time, and zero steady-state error. The experimental result also shows that when the output disturbance enters to the process control system, the adaptive PLL can maintain the stability of the system and the effect of the output disturbance can also be fast rejected. The adaptive PLL has better performance ...

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.435-442
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• 1997

The roof crane system is used for transporting a variable load to a target position. The goal of crane control system is transporting the load to a goal position as quick as possible without rope oscillation. The crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid tansportation is required. In this paper, we developed a simple fuzzy controller which has been introduced expert's knowledge base for anti-swing and rapid tranportation to goal position. In particular, we proposed the synthesis reasoning method which synthesizes on the basis of expert knowledge of the angle control input and position control input which are inferenced parallel and simultaneously. And we confirmed that the performance of the developed controller is effective as a result of applying it to crane simulator and also verified whether the proposed synthesis rules have been applied correctly using clustering algorithm from the measured data.

• ETRI Journal
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• v.28 no.1
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• pp.1-8
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• 2006

A novel all-optical gain-controlled (AOGC) bidirectional amplifier is proposed and demonstrated in a compact structure. The AOGC function using fiber Bragg grating (FBG) pairs controls both directional signals independently, and combinations of optical interleavers and isolators suppress Rayleigh backscattering (RB) noise. The amplifier achieves high and constant gain with a wide dynamic input signal range and low noise figure. The performance does not depend on the input signal conditions, whether static-state or transient signals, or whether there is symmetric or asymmetric data traffic on bidirectional transmission. Transmission comparison experiments between invariable symmetrical and random variable asymmetric bidirectional data traffic verify that the all-optical gain control and bidirectional amplification functions are successfully combined into this proposed amplifier.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.34-41
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• 2005

Generally, it is not easy to get a suitable controller for multi variable systems. If the modeling equation of the system can be found, it is possible to get LQR control as an optimal solution. This paper suggests an LQR learning method to design LQR controller without the modeling equation. The proposed algorithm uses the same cost function with error and input energy as LQR is used, and the LQR controller is trained to reduce the function. In this training process, the Jacobian matrix that informs the converging direction of the controller Is used. Jacobian means the relationship of output variations for input variations and can be approximately found by the simple experiments. In the simulations of a hydrofoil catamaran with multi variables, it can be confirmed that the training of LQR controller is possible by using the approximate Jacobian matrix instead of the modeling equation and this controller is not worse than the traditional LQR controller.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.53-56
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• 2005

Aircraft noise is a important problem to inhabitants near airports. INM is one of programs for determining the predicted noise impact in the vicinity of airports. It has been widely using for engineers to evaluate aircraft noise. However it is difficult to predict aircraft noise in case of lack of exact INM input data. The exact informations about a fighter plane are not known well for a security problem. This study presents methods of reducing errors between measurement and simulation when the exact INM input data is not known. Especially we adjusted the thrust force of aircraft engine and reduced the error.

• Journal of Korean Society for Quality Management
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• v.34 no.1
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• pp.1-12
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• 2006

This paper presents a six sigma project for improving gate painting quality in a medium-sized automotive part company. The project follows a disciplined process of five macro phases: Define, Measure, Analyze, Improve, and Control. A CTQ(critical to quality) is determined based on COPQ(cost of poor quality) analysis, and a process map is utilized for identifying process input variables. Three KPIV s(key process input variable) are selected; Painting Temperature, Painting Quantity, and Painting Viscosity, and DOE(design of experiments) is utilized for finding the optimal process conditions for three KPIVs. MINITAB software is used for data analyses and DOE. The sigma level of defects rate has improved from 2.93 to 3.66.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2455-2458
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• 2003

In this paper, the Classification of Energy Labeling has been Proposed. Energy Parameters of input signal which is extracted from each phoneme is labelled. And groups of labelling according to detected energies of input signals are detected. Next, DTW processes in a selected group of labeling. This leads to DTW processing faster than a previous algorithm. In this Method, because an accurate detection of parameters is necessary on the assumption in steps of a detection of speeching duration and a detection of energy parameters, variable windows which are decided by pitch period is used. Extract algorithms don't search for exact frame energy, because 256 frame window-sizes is fixed. For this reason, a new energy extraction method has been proposed. A pitch period is detected firstly; next window scale is decided between 200 frames and 300 frames. The proposed method make it possible to cancel an influence of windows.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.192-194
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• 2006

Backlash between meshing gear teeth causes impact, tracking error and undesired vibrations. It is usually minimized by precision gear, spring-loaded anti-backlash gears and precise mechanical adjustment. Although these techniques can help to reduce the backlash gap, its cost is relatively high and performance is limited. And the classic controller is insufficient to control the dynamic system with nonlinearity. For these reason, a fuzzy controller is proposed to compensate the backlash effect at a robot system. The input variables are position error and change in error. The output variable can be defined by input voltage of motor. The performance of a fuzzy controller is verified by comparing with a PID controller. The results show that the undesired vibration is suppressed. And then diminishing the position error is observed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.10
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• pp.1894-1899
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• 2010

This note is concerned with a robust sliding mode control(SMC) for a class of unmatched uncertain system with severe commensurate state time delay. The suggested method is extended to the control of severe state time delay systems with unmatched uncertainties except the matched input matrix uncertainty. A transformed sliding surface is proposed and a stabilizing control input is suggested. The closed loop stability together with the existence condition of the sliding mode on the proposed sliding surface is investigated through one Lemma and two Theorems by using the Lyapunov direct method with the concept of the control Lyapunov function instead of complex Lyapunov-Kravoskii functionals. Through an illustrative example and simulation study, the usefulness of the main results is verified.