• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1981-1986
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• 2004

In this study, the basic motor control system had been investigated. The controller for this study consists of two main parts, a feedforward controller part and a feedback controller part. Each part will deals with different control problems. The feedback controller deals with robustness and stability, while the feedforward controller deals with response speed. The feedforward controller, used to solve the tracking control problem, is adaptable. To make such a tracking perfect, an adaptive law based on Feedback Error Learning (FEL) is designed so that the feedforward controller becomes an inverse system of the controlled plant. The novelty of FEL method lies in its use of feedback error as a teaching signal for learning the inverse model. The theory in $H^{\infty}$-Control is selected to be applied in the feedback part to guarantee the stability and solve the robust stabilization problems. The simulation of each individual part and the integrated one are taken to clarify the study.

• 한국산학기술학회논문지
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• 제16권4호
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• pp.2647-2655
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• 2015

본 연구는 보건 계열 대학생을 대상으로 감염관리 시뮬레이션 교육에서 직소모형 협동학습을 적용한 후 감염관리 인식도, 내적동기, 학습만족도의 차이를 통해 프로그램의 효과를 평가하는데 목적이 있다. 연구 참여자는 J시에 소재한 D대학의 보건계열 2학년 학생으로 실험군 27명과 대조군 27명이다. 두군간의 동질성을 평가하기 위해 사전검사로 감염관리 인식도와 내적동기, 학습만족도에 대해 조사하였으며 두군간에는 유의한 차이가 없었다. 실험군을 대상으로 직소모형을 응용한 협동학습, 시뮬레이션 실습, 디브리핑으로 구성된 프로그램을 1회 3시간씩 1주에 2회로 총 12시간을 실시하였고 대조군에게는 전통적인 강의와 시뮬레이션 실습, 디브리핑을 실시하였다. 2주간의 교육 후 연구 대상자 모두에게 감염관리 인식도, 내적동기, 학습만족도를 조사하였다. 연구 결과 감염관리 시뮬레이션 교육에서 직소모형을 적용한 실험군에서 감염관리 인식도와 학습만족도에서 통계적으로 유의하게 향상되었다. 본 연구결과를 바탕으로 다양한 교과목의 보건계열 시뮬레이션 교육에서 직소모형을 적용한 협동학습이 이루어져 효과적인 수업이 이루어지는데 적극적으로 활용될 것을 기대한다.

• 전기학회논문지
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• 제56권3호
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• pp.611-614
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• 2007

In this paper, a Direct Learning Control (DLC) method is presented to generate a virtual reference input for linear feedback systems to improve the output tracking performance. The original reference input is effectively modified by the DLC without any iterative learning process. The presented DLC is designed based on the information on the relative degree of a system and previously generated virtual reference inputs. It is illustrated by simulations that the virtual reference input generated by the proposed DLC can achieve high tracking performance, although the reference input cannot be appropriately shaped by using existing DLC methods.

• International Journal of Aeronautical and Space Sciences
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• 제11권2호
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• pp.87-97
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• 2010

A fault tolerant satellite attitude control scheme with a modified iterative learning law is proposed for dealing with actuator faults. The actuator fault is modeled to reflect the degradation of actuation effectiveness, and the solar array-induced disturbance is considered as an external disturbance. To estimate the magnitudes of the actuator fault and the external disturbance, a modified iterative learning law using only the information associated with the state error is applied. Stability analysis is performed to obtain the gain matrices of the modified iterative learning law using the Lyapunov theorem. The proposed fault tolerant control scheme is applied to the rest-to-rest maneuver of a large satellite system, and numerical simulations are performed to verify the performance of the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.421-426
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• 2005

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes particle swarm optimization algorithm based optimal learning fuzzy-neural network (PSOA-FNN). The proposed learning scheme is the fuzzy-neural network structure which can handle linguistic knowledge as tuning membership function of fuzzy logic by particle swarm optimization algorithm. The learning algorithm of the PSOA-FNN is composed of two phases. The first phase is to find the initial membership functions of the fuzzy neural network model. In the second phase, particle swarm optimization algorithm is used for tuning of membership functions of the proposed model.

• 한국소음진동공학회논문집
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• 제12권8호
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• pp.609-615
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• 2002

본 논문에서는 단순하고 효율적인 학습제어 로직을 운동기구용 로봇팔 시스템에 적용하였다. 일반적으로 운동시에 운동기구에 적용되는 힘은 사용자마다 다르고 같은 사용자라 하더라도 운동시마다 다를 것이다. 이미 사용자의 신체조건에 따라 입력된 최적의 힘과 실제 가해지는 힘 사이의 오차를 보상하는데 본 논문에서는 학습제어를 적용하여 가해지는 힘의 종류(시변 또는 시불변함수)와 상관없이 빠르게 오차를 제거하고 원하는 운동을 추종함을 시뮬레이션을 통하여 확인할 수 있었다.

• 한국군사과학기술학회지
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• 제21권6호
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• pp.850-856
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• 2018

In this paper, a controller based on repetitive learning control is designed to control an unmanned surface vessel with nonlinear characteristics and unknown parameters. First, we define the equations of motion and error system of the unmanned vessel, and then design an repetitive learning controller composed of system error and estimated unknown parameters based on repetitive learning control and adaptive control. The stability of the unmanned vessel model controlled by the designed controller is verified through the analysis of the Lyapunov stability. Simulation shows that the error converges asymptotically to zero with semi-global result, confirming that the unmanned vessel is moving toward a given ideal path, and verifies that the controller is also feasible.

• 드라이브 ㆍ 컨트롤
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• 제19권2호
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• pp.17-26
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• 2022

Recently, automatic transmissions caused a good improvement in the shift quality of a forklift. An advanced shift control algorithm, which was based on TCU firmware, was applied with embedded control technology and microcontrollers. In the clutch-to-clutch shifting, one friction element is released and the other friction element is activated. During this process, if the release and application timings are not synchronized, an overrun or tie-up occurs and ultimately leads to a shift shock. The TCU, which measures only the speed of the forklift, inevitably applies the open-loop shift control. In this situation, the speed ratio does not change during the clutch fill. The torque phase occurs until the clutch is disengaged. In this study, an offline shift logic of the learning control was proposed. It induced a synchronous shift when the learning control progressed. During this process, the reference current trajectory of the release clutch was corrected and applied to the next upshift. We considered the results of the overrun/tie-up characteristics of the upshift performed immediately before. The vehicle test proved that the deviation in shift quality, which was caused by the difference in the mechanical characteristics of the clutch, could be improved by the learning control.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제19권1호
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• pp.81-88
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• 2015

This study used a posttest control group design and to find out differences between students' self-regulated learning strategies in traditional and non-traditional classroom. To this end, 131 first year university students within the experimental and control groups took part in the study. While ICT-based approach was used as the main medium of instruction in the experimental group, in the control group the paper-based traditional method was used. A survey adapted from Davaanyam [Davaanyam, T. (2013). The structural relationships among Mongolian students' attitudes toward mathematics, motivational beliefs, self-regulated learning strategies, and mathematics achievement. Ph. D. Dissertation. Jeonju, Jeonbuk, Korea: Chonbuk National Unversity.] was used to gather the data. The results of the study indicated a significant difference between the control and experimental groups in regard with their self-regulated learning. That is to say, the experimental group taught through ICT tools acquired higher levels of self-regulation as compared with the control group instructed through the traditional teaching method.

• 제어로봇시스템학회논문지
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• 제3권6호
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• pp.555-562
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• 1997

With only the classical PID controller applied to control of a DC motor, good (target) performance characteristic of the controller can be obtained if all the model parameters of DC motor and operating conditions such as external load torque, disturbance, etc. are known exactly. However, in case when some of system parameters or operating conditions are uncertain or unknown, the fixed PID controller does not guarantee good performance, which is assumed with precisely known system parameters and operating conditions. In view of this and the robustness enhancement of DC motor control system, we propose a PID learning controller which consists of a set of learning rules for PID gain tuning and learning of an auxiliary input. The proposed PID learning controller is shown to drive the state of uncertain DC motor system with unknown system parameters and external load torque to the desired one world wide asymptotically. Computer simulation and experimental results are given to demonstrate the effectiveness of the proposed PID learning controller, thereby showing its superiority to the conventional fixed PID controller.