• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.512-514
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• 1998

The paper presents a model reference adaptive control containing a fuzzy algorithm for tuning the gain coefficient which adjusts the level of the fuzzy controller output. The synthesis of a fuzzy tuning algorithm has been performed for the inverted pendulum system. The computer simulation results have proved the efficiency of the proposed method, showing stable system responses.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.151-152
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• 2008

본 논문에서는 도립 역진자 시스템에서의 진자의 도립 상태를 유지하도록 하기 위하여, DSP와 FPGA를 결합하여 ANFIS 뉴로퍼지 제어기를 구현하여 실험하였다. 도립진자의 위치 추종 성능을 PID 제어기와 비교 평가하였다.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.3 no.4
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• pp.62-69
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• 1989

휴대용 전기톱을 비롯한 학습 기계장치, 자동차 연동장치, 각종 화학 분석장치 및 산업용 로봇 시스템등의 전기설비에 광범위하게 응용되고 있는 고유 불안정 도립진자 시스템의 동적 안정화 제어기 설계기법이 소개된다. 복잡한 비선형 동특성을 고려한 수학적 모델링과 C. D. Johnson에 의해 제시된 외란 적응 제어 이론을 적응하여, 최적 레귤레이터형 안정화 제어기를 설계하였으며, 컴퓨터 시뮬레이션 및 실험결과가 만족스럽게 나타났다.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.176.5-176
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• 2001

This paper presents a fuzzy dynamic output feedback controller design method for Parallel Distributed Compensation (PDC)-type Takagi-Sugeno (T-S) model based fuzzy dynamic system with H$\infty$ performance and additional constraints on the closed pole placement. Design condition for these controller is obtained in terms of the linear matrix inequalities (LMIs). The proposed fuzzy controller satisfies the disturbance rejection performance and the desired transient response. The design method is verified by this method for an inverted pendulum with a cart using the proposed method.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.2
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• pp.178-189
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• 1995

In this pater, authors derive the state - space equiation about the patallel - type inverted pendulum which is adopted as control object, and constitute the control system by $H_\infty$control theory. The modeling error is unavoidably existed by linearization error, and so on. We regard this modeling error which is determined from the identification through frequency response as unstructured model uncertainty. An augmented state - space equiation with frequency weighting function is constructed for application of the $H_\infty$theory, and the mixed sensitivity problem is considered. The weighting functions are determined in consideration of the model uncertainty and the response of system in frequency region. The $H_\infty$controller is designed by using software package for controller design. From results of response simulation, the control system designed with $H_\infty$theory guarantees low sensitivity for disturbance as well as robustness against the model uncertainties.

• Journal of Advanced Marine Engineering and Technology
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• v.21 no.4
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• pp.393-403
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• 1997

In this paper, we proposed an optimal identification method of identifying the membership func¬tions and the fuzzy rules for the stabilization controller of the nonlinear system by RVEGA( Real Variable Elitist Genetic Algo rithm l. Although fuzzy logic controllers have been successfully applied to industrial plants, most of them have been relied heavily on expert's empirical knowl¬edge. So it is very difficult to determine the linguistic state space partitions and parameters of the membership functions and to extract the control rules. Most of conventional approaches have the drastic defects of trapping to a local minima. However, the proposed RVEGA which is similiar to the processes of natural evolution can optimize simulta¬neously the fuzzy rules and the parameters of membership functions. The validity of the RVEGA - based fuzzy controller was proved through applications to the stabi¬lization problems of an inverted pendulum system with highly nonlinear dynamics. The proposed RVEGA - based fuzzy controller has a swing -. up control mode(swing - up controller) and a stabi¬lization one(stabilization controller), moves a pendulum in an initial stable equilibrium point and a cart in an arbitrary position, to an unstable equilibrium point and a center of the rail. The stabi¬lization controller is composed of a hierarchical fuzzy inference structure; that is, the lower level inference for the virtual equilibrium point and the higher level one for position control of the cart according to the firstly inferred virtual equilibrium point. The experimental apparatus was imple¬mented by a DT -- 2801 board with AID, D/A converters and a PC - 586 microprocessor.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.758-765
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• 2015

This paper proposes an attitude control system to keep the balance for a two-wheeled mobile manipulator which consists of a mobile platform and a three D.O.F. manipulator. In the conventional control scheme, complicated dynamics of the manipulator need to be derived for balancing control of a mobile manipulator. The method proposed in this paper, however, three links are considered as one body of mass and the dynamics are derived easily by using an inverted pendulum model. One of the best advantage of a sliding mode controller is low sensitivity to plant parameter variations and disturbances, which eliminates the necessity of exact modeling to control the system. Therefore the sliding mode control algorithm has been adopted in this research for the attitude control of mobile platform along the pitch axis. The center of gravity for the whole mobile manipulator is changing depending on the motion of the manipulator. And the orientation variation of center of gravity is used as reference input for the sliding mode controller of the pitch axis to maintain the center of gravity in the middle of robot to keep the balance for the robot. To confirm the performance of controller, MATLAB Simulink has been used and the resulting algorithms are applied to a real robot to demonstrate the superiority of the proposed attitude control.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2538-2541
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• 2005

This paper deals one of the methods of system identification, especially on-line system identification in time-domain. The algorithm in this study needs all states of the system as well input to it for system identification. In this reason, Kalman filter is used for state estimation. But in order to implement a state estimator, the fact that a system model must be known is logical contradiction. To overcome this, state estimation and system parameter estimation are performed simultaneously in one sample. And the result of the system parameter estimation is used as basis to state estimation in next sample. On-line system identification comes, in every sample by performing both processes of state estimation and parameter estimation that are related mutually and recursively. This paper demonstrates the validity of proposed algorithm through an example of an unstable inverted pendulum system. This algorithm can be useful for on-line system identification of a system that has fewer number of measurable output than system order or number of states.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.124-133
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• 1996

This paper presents the implementation of variable structure control system for a linear or nonlinear system using neural networks. The overall control system consists of neural network controller and a reaching mode controller. While the former approximates the equivalent control input on the sliding surface, the latter is used to bring the entire system trajectories toward the sliding surface. No supervised learning procedures are needed and the weights of the neural network are tuned on-line automatically. The neural netowrk-based variable structure control system is applied to a nonlinare unstable inverted pendulum system through computer simulations, and implemented using a microcomputer (80486-50MHz) and applied to the DC servomotor position control system. Simulation and experimental results show the expected approximation sliding property is occurred. The proposed controller is compared with a PID controller and shows better performance than the PID controller in abrupt plant parameter change.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.578-584
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• 2015

In this study a moving platform for a mobile robot that can be traveling with a full automatic standing arm was developed. Conventional mobile robots generally may equip 4 wheels or 3 wheels with a caster wheel or independent driven wheels and have good statistic stability. When a mobile robot travels on a sharply perpendicular and narrow crossroad, it may need a special steering scheme such as going forward and backward repeatedly or it is sometimes physically impossible for the robot to go through the crossroad because of the size limit. The upright running mobile robot changes its posture to the upright posture which has a small planar area and is able to go through the crossroad. The upright control which was manually performed step by step before such as sequences of uprighting (returning), checking, and balancing, is now automated.