• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.3
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• pp.67-73
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• 2006

In this paper, a reconfigurable model following flight control method is proposed based on direct adaptive scheme using parameter estimation. Adaptive control scheme updates the control gains to make the system output follow the reference output even when fault occurs. By adopting the frequency domain parameter estimation method, system changes by the fault can be estimated. Recursive Fourier transformation is used for system identification. Using recursive Fourier transform, the proposed adaptive control algorithm guarantees the system stability and improves the system characteristics. To evaluate the performance of proposed control method, numerical simulations are performed.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.158-167
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• 1994

The design concept of varaiable structure control is useful not only to stochasic systems but also to adaptive control systems. The Dynamic equation of vertical three linkage robot was derived. And it was simplyfied according to the scheme of control strategy. And we specify the form of model. Thereafter the error dynamic equation was derived between the real state of the plant and state of the model. Some simulations were performed to control robot manipulator applying the methodology of the variable structure model following adaptive control.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.5
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• pp.464-469
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• 2009

In this study, a new fault tolerant controller based on a model following adaptive technique is applied to the reconfiguration mode of supersonic advanced trainer. The designed controller is applied to the flight control system of high performance aircraft. To verify the performance of the proposed controller, numerical simulations are executed using a non-realtime nonlinear verification tool.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.3
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• pp.50-57
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• 2003

In the paper, the design and evaluation of a helicopter trajectory tracking controller are presented. The control algorithm is implemented using the feedback linearization technique and the two time-scale separation architecture. In addition, and on-line adaptive architecture that employs a neural network compensating the model inversion error caused by the deficiency of full knowledge of helicopter dynamic is applied to augment the attitude control system. Trajectory tracking performance of the control system in evaluated using modified TMAN simulation program representing as Apache helicopter. It is show that the on-line neural network in an adaptive control architecture is very effective in dealing with the performance depreciation problem of the trajectory tracking control caused by insufficient information of dynamics.

• Proceedings of the KIEE Conference
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• 1986.07a
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• pp.145-148
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• 1986

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.197-200
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• 2001

본 논문에서는 특정한 형태의 제약 즉, 매니퓰레이터의 자유도와 주어진 제약조건의 차원의 차이가 1이며, 매니퓰레이터의 동역학을 작업영역에서의 축차모델로 나타내었을 때, 변환행렬이 단위행렬로 나타나는 제약을 가지는 불확실한 로봇 매니퓰레이터의 위치/힘 추종을 위한 적응제어기를 제안한다. 제안된 제어기는 비선형 좌표변환을 통하여 얻어진 로봇의 축차모델(reduced-order model)을 이용하여 위치제어와 힘제어의 문제를 분리한다. 특히, 비선형 동적 필터를 이용하여 위치의 측정만을 필요로 하며, 적응제어 기법을 통하여 전역 점근적인 안정성을 보장한다.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.5
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• pp.609-616
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• 2003

The purpose of this study is to design the adaptive speed control system of a marine diesel engine by combining the Model Matching Method and the Nominal Model Tracking Method. The authors proposed already a new method to determine efficiently the PID control Parameters by the Model Matching Method. typically taking a marine diesel engine as a non-oscillatory second-order system. But. actually it is very difficult to find out the exact model of a diesel engine. Therefore, when diesel engine model and actual diesel engine are unmatched as an another approach to promote the speed control characteristics of a marine diesel engine, this paper Proposes a Model Reference Adaptive Speed Control system of a diesel engine, in which PID control system for the model of a diesel engine is adopted as the nominal model and Fuzzy controller and derivative operator are adopted as the adaptive controller.

• Transactions of the Korean Society of Mechanical Engineers
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• v.13 no.6
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• pp.1346-1360
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• 1989

본 연구에서는 기준 모델 적응제어 방식에서 직접 적응제어 방식을 사용하여 부하의 변동 및 외란이 발생할 경우에도 매니퓰레이터의 정확한 궤적의 추종 및 속도 의 실시간 제어가 가능한 적응제어시스템을 설계하고자 한다. 제2절에서는 로봇 매니퓰레이터의 기구학적 이론 및 동적 모델링에 대한 기본이론을 전개하고, 제3절 에서는 제어시스템의 설계를 위한 제어 알고리즘과 초안정(hyperstability)이론을 통한 안정성 해석을 다룬다. 그리고 제4절에서는 제안된 제어기의 성능 평가를 위해 6관절 로봇인 스탠포드 로봇 매니퓰레이터에 대한 시뮬레이션을 통한 결과를 토오크 계산법(computed torque method)에 의한 결과와 비교 검토함으로서 제안된 제어기의 성능을 예증한다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.228-235
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• 2010

This paper deals with an autonomous flight controller design problem for a tilt-rotor aircraft in rotary-wing mode. The inner-loop algorithm is designed using the output-based approximate feedback linearization. The model error originated from the feedback linearization is cancelled within allowable tolerance by using single-hidden-layer neural network. According to Lyapunov direct stability theory, the adaptive update law is derived to run the neural network on-line, which is based on the linear observer dynamics. Moreover, the outer-loop algorithm is designed to track the trajectory generated from way-point guidance. Especially, heading and flight-path angle line-of-sight guidance are applied to the outer-loop to improve accuracy of the landing tracking performance. The 6-DOF nonlinear simulation shows that the overall performance of the flight control algorithm is satisfactory even though the collective input response shows instantaneous actuator saturation for a short time due to the lack of the neural network and the saturation protection logic in that loop.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.564-570
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• 2003

This paper presents an adaptive fuzzy control scheme for nonlinear helicopter system which has uncertainty or unknown variations in parameters. The proposed adaptive fuzzy controller is a model reference adaptive controller. The parameters of fuzzy controller are adjusted so that the plant output tracks the reference model output. It is shown that the adaptive law guarantees the stability of the closed-loop system by using Lyapunov function. Several experiments with a small model helicopter having parameter variations are performed to show the usefulness of the proposed adaptive fuzzy controller.