• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 학술대회 논문집 전문대학교육위원
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• pp.51-54
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• 2007

In this paper, the dynamic models of a SOFC are rearranged. It consists of electrochemical model, thermal model, voltage equation and several loss equations. Experiment results of the real SOFC system are shown to evaluate the steady voltage characteristics. Control problems on tracking steady voltage by air flow is discussed and an adaptive controller is designed to withstand to the variation of stack current. Simulation is done to prove the solution of control algorithms.

• 한국식품영양학회지
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• 제1권2호
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• pp.31-36
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• 1988

An adaptive on-line optimization method has been applied to test the ability to maximize the cellular productivity of a continuous methylotroph culture system which was simulated by a variable yield Monod-type model. Optimum dilution rate and productivity were successively obtained and maintained at all times by the algorithm that utilizes steepest descent technique as optimization method and recursive least-square method with forgetting factor as dynamic model identification.

• Journal of Biosystems Engineering
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• 제21권3호
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• pp.283-292
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• 1996

Automatic guidance of farm tractors would improve productivity by reducing operator fatigue and increasing machine performance. To control tractors within $\pm$5cm of the desired path, fuzzy and adaptive steering controllers were developed to evaluate their characteristics and performance. Two input variables were position and yaw errors, and a steering command was fed to tractor model as controller output. Trapezoidal membership functions were used in the fuzzy controller, and a minimum-variance adaptive controller was implemented into the 2-DOF discrete-time input-output model. For unit-step and composite paths, a dynamic tractor simulator was used to test the controllers developed. The results showed that both controllers could control the tractor within $\pm$5cm error from the defined path and the position error of tractor by fuzzy controller was the bigger of the two. Through simulations, the output of self-tuning adaptive controller was relatively smooth, but the fuzzy controller was very sensitive by the change of gain and the shape of membership functions. Contrarily, modeling procedure of the fuzzy controller was simple, but the adaptive controller had very complex procedure of design and showed that control performance was affected greatly by the order of its model.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 추계학술대회
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• pp.737-742
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• 2004

In this paper, a family of decentralized adaptive controller is proposed to control robot manipulators which are governed by highly nonlinear dynamic equations. The controller is computationally efficient since it does not require mathematical model or parameter values of the manipulators. The stability of the manipulators with the controller is proved by Lyapunov theory. The results of numerical simulations show that the system is stable, and has excellent trajectory tracking performance.

• International Journal of Precision Engineering and Manufacturing
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• 제2권3호
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• pp.34-40
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• 2001

Robot manipulator has highly nonlinear dynamics. Therefore the control of multi-link robot arms is a challenging and difficult problem. In this paper a decentralized adaptive fuzzy sliding mode scheme is developed for control of robot manipulators. The proposed scheme does not require an accurate manipulator dynamic model, yet it guarantees asymptotic trajectory tracking despite gross robot parameter variations. Numerical simulation for decentralized control of a 3-axis PUMA arm will also be included.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.125.3-125
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• 2001

Recently, aircraft is designed to have high maneuverable at high angle of attack. However, it is very hard to obtain the accurate dynamic model for the high performance, because aerodynamic characteristics are nonlinear and include a lot of uncertainties. Therefore, nonlinear controller without considering uncertainties may degrade the control system performance. On this paper, to overcome these defects, the neural networks based adaptive nonlinear controller is proposed making use of the backstepping technique. Neural networks are implemented to guarantee robustness to uncertainties caused by aerodynamic coefficients variation. The main feature of the proposed controller is that the adaptive controller is developed under the assumption ...

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.959-962
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• 2003

In this paper, a decentralized adaptive controller is proposed to control robot manipulators which are governed by highly nonlinear dynamic equations. The controller is computationally efficient since it does not require mathematical model or parameter values of robot manipulators. The stability of the manipulators with the controller is proved by Lyapunov theory. The results of computer simulations show that the robot manipulator system is stable, and has excellent trajectory tracking performance.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.403-407
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• 1999

In this paper we present an architecture, implementation, and performance evaluation of an adaptive communication system (ACS) for wide-area ATM clusters. Our approach capitalizes on thread-based programming model to overlap computation and communication and develop a dynamic message-passing environment with separate data and control paths. This leads to a flexible and adaptive message-passing environment that can support multiple flow control, error control, and multicasting algorithms. We show the performance of ACS applications and compare them with p4, PVM, and MPI applications.

• 대한전기학회논문지
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• 제37권9호
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• pp.655-662
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• 1988

An adaptive control scheme has been recognized as an effective approach for a robot manipulator to track a deired trajectory in spite of the presence of nonlinearies and parameter uncertainties in robot dynamic models. In this paper, an adaptive control scheme for a robot manipulator is proposed to design the self-tuning controller which controls the extended linearized perturbaton model via the pole placement, and this control. The feasibility of the controller is demonstrated by the simulation about position control of a three-link manipulator with payload and parameter uncertainty.

• 한국정밀공학회지
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• 제21권11호
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• pp.110-116
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• 2004

In this paper, a decentralized adaptive controller is proposed to control robot manipulators which are governed by highly nonlinear dynamic equations. The controller is computationally efficient since it does not require mathematical model or parameter values of robot manipulators. The stability of the manipulators with the controller is proved by Lyapunov theory. The results of numerical simulations show that the system is stable, and has excellent trajectory tracking performance.