• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 추계 학술대회 학술발표 논문집
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• pp.141-144
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• 2003

A composite adaptive dual fuzzy controller combining the approximate mathematical model, linguistic model description, linguistic control rules and identification modeling error into a single adaptive fuzzy controller is developed for a nonlinear system. It ensures the system output tracks the desired reference value and excites the plant sufficiently for accelerating the parameter estimation process so that the control performances are greatly improved. Using the Lyapunov synthesis approach, proposed controller is analyzed and simulation results verify the effectiveness of the proposed control algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.247-250
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• 2003

In this paper, we propose a robust controller for motion control of n-link robot manipulators using visual feedback. The desired joint velocity and acceleration is obtained by the feature-based visual systems and is used in the joint velocity control loop for trajectory control of the robot manipulator. We design a robust controller that compensates for bounded parametric uncertainties of robot dynamics. The stability analysis of robust joint velocity control system is shown by Lyapunov Method. The effectiveness of the proposed method is shown by simulation results on the 5-link robot manipulators with two degree of freedom.

• 전자공학회논문지
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• 제50권7호
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• pp.239-243
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• 2013

본 논문에서는 입력에 시간 지연이 존재하는 삼각구조의 비선형시스템에 대한 출력 피드백 제어방법을 제안한다. 제안한 제어기는 고이득 관측기와 선형제어기로 구성한다. Lyapunov-Krasovskii 정리를 이용하여 점근적 안정도를 보장하는 입력지연의 크기를 유도한다. 마지막으로 제안한 결과의 유효성을 증명하기 위하여 모의실험 예제를 제공한다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.101-106
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• 1997

This paper proposes a stable adaptive neural network control(NNC) for fixable joint manipulators. For designing the stable adaptive NNC, the flexible system dynamics is separated into fast and slow subdynamics according to singular perturbation concept. For the slow subdynamics, an adaptive NNC is designed to warrant the system stability and NN learning by lyapunov stability criterion. And to stabilize the fast dynamics, derivative control loop is installed. Through numerical simulation, the performance of the proposed NNC was compared to that of an adaptive controller designed based on the knowledge of the system dynamics. The proposed NNC shows much improvement over the conventional adaptive controller.

• 제어로봇시스템학회논문지
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• 제15권1호
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• pp.67-71
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• 2009

This paper presents a rank-constrained linear matrix inequality (LMI) approach to the design of a multi-objective controller such as $H_2/H_{\infty}$ control. Multi-objective control is formulated as an LMI optimization problem with a nonconvex rank condition, which is imposed on the controller gain matirx not Lyapunov matrices. With this rank-constrained formulation, we can expect to reduce conservatism because we can use separate Lyapunov matrices for different control objectives. An iterative penalty method is applied to solve this rank-constrained LMI optimization problem. Numerical experiments are performed to illustrate the proposed method.

• 한국통신학회논문지
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• 제17권12호
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• pp.1333-1342
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• 1992

본 논문은 제어 입력 u(t)에 대하여 비선형 결합된 3차 미분 방정식으로 표현되는 조작기를 갖는 로보트 매니퓰레이터에 대하여 제어기의 설계에 관한 논문이다. 제어 방식은 두 단계로 구성되며, 첫째 단계로는 비결합된 제어가능한 선형 계통을 얻기 위하여 대역적(global)선형화를 수행하며, 둘째 단계로는 선형화 계통에 대하여, 모델의 불확실성이 존재하는 경우에도 강건성과 안정도를 보장하도록 Lyapunov 방정식과 전체 안정도 이론을 적용하여 제어기를 설계한다. 제안된 제어기를 조작기가 포함된 자유도가 3인 로보트 매니퓰레이터에 대하여 컴퓨터 시뮬레이션을 하였다.

• 제어로봇시스템학회논문지
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• 제16권3호
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• pp.239-244
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• 2010

This paper is to present map building of mobile robot using RFID (Radio Frequency Identification) technology and ultrasonic sensor. For mobile robot to perform map building, the mobile robot needs its localization and accurate driving in space. In this reason, firstly, kinematic modeling of mobile robot under non-holonomic constrains is introduced. Secondly, based on this modeling, a tracking controller is designed for tracking a given path based on backstepping method using Lyapunov function. The Lyapunov function is also introduced for proving the stability of the designed tracking controller. Thirdly, 2D map building is performed by RFID system, mobile robot system and ultrasonic sensors. The RFID mobile robot system is composed of DC motor, encoder, ultra sonic sensor, digital compass, RFID receiver and RFID antenna. Finally, the path tracking simulation results and map building experimental results are presented to show the effectiveness of the designed controller.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권7호
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• pp.385-392
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• 2003

A nonlinear speed controller for a separately excited DC motor (SEDCM) based on a newly developed adaptive backstepping approach is presented. To compensate parameter uncertainties and load torque disturbance, a nonlinear adaptive backstepping control law and adaptive law are derived systematically step by step through virtual control input and suitable Lyapunov function. Also, speed observer without using costly speed sensor is presented. Simulation results show that the proposed controller can observe real speed and track the reference speed signal generated by a reference model.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 C
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• pp.994-996
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• 1998

In this paper, the standard Dole, Glover, Khargoneker, and Francis (abbr. : DGKF 1989) $H_{\infty}$ controller $(H_{\infty}C)$ is extended to the nonlinear feedback linearization-$H_\infty$-based sliding mode controller (NFL-$H_\infty$-based SMC). A stability proof of the closed-loop stability is done by a Lyapunov function candidate using an addition form of the sliding surface vector and the estimation error.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집B
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• pp.265-270
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• 2001

In this paper, a robust controller is proposed to control a robot manipulator which is governed by highly nonlinear dynamic equations. The controller is computationally efficient since it does not require the dynamic model or parameter values of a robot manipulator. It, however, requires uncertainty bounds which are derived by using properties of revolute joint robot dynamics. The stability of the robot with the controller is proved by using Lyapunov's direct method. The results of computer simulations also show that the robot system is stable, and has excellent trajectory tracking performance.