• 한국정보통신학회논문지
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• 제13권5호
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• pp.913-921
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• 2009

본 연구에서는 강인한 성능을 가지는 해집단내에서 기준모델의 출력을 최적으로 추종하도록 유전 알고리즘을 사용하여 가중치 함수와 설계 파라메타 ${\gamma}$를 동시에 최적화함으로써, 강인한 성능에 관한 필요충분조건식을 만족함은 물론 설계사양에 따른 만족스러운 응답특성을 보이는 강인한 성능을 가지는 모델추종형 $H_{\infty}$ 제어기의 설계법을 제시하고 시뮬레이션을 통하여 그 유용성을 확인한다.

• Journal of Advanced Marine Engineering and Technology
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• 제36권1호
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• pp.126-132
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• 2012

본 연구에서는 강인한 성능을 가지는 모델추종형 H${\infty}$ 제어기의 설계법을 제시한다. 이를 위해 강인한 성능을 보장하는 해집단내에서 기준모델의 출력을 최적으로 추종하도록 유전 알고리즘을 사용하여 가중치 함수와 설계 파라미터 ${\gamma}$를 동시에 최적화한다. 설계된 H${\infty}$ 제어기는 강인한 성능에 관한 필요충분조건식을 만족함은 물론 설계사양에 따른 만족스러운 응답특성을 가진다. 제시된 방법을 보일러-터빈 제어 시스템에 적용하여 그 유용성을 확인한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.485-485
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• 2000

A design method of model following control system using neural networks is proposed. An unknown nonlinear single-input single-output plant is identified using a multilayer neural networks. A linear controller is designed fer the linear approximation model obtained by linearinzing the identification model. The identification model is also used as a plant emulator to obtain the prediction error. Deficient servo performance due to controlling nonlinear plant with only linear controller is mended by adjusting the linear controller output using the prediction output and the parameters of the identification model. An optimal preview controller is adopted as the linear controller by reason of having good servo performance lowering the peak of control input. Validity of proposed method is illustrated through a numerical simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.130-134
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• 1992

The ability of a robot system to comply to an environment via the control of tool-environment interaction force is of vital for the successful task accomplishment in many robot application. This paper presents the implementation of external force control for two dimensional contour following task using a commercial robot system. Force accommodation is used since a constraint imposed in our work is not to modify the commercial robot system. A linear, decoupled model of two dimensional contour following system in the discrete time domain is derived first. Then the experimental verification of linear control is obtained using a PUMA 560 manipulator with standard Unimation controller, Astek FS6-120A six axis wrist force sensor attached externally to the arm and LSI-11173 microcomputer. Experimentally obtained data shows that the RMS contact force error is 0.8246 N when following the straight edge and 2.3768 N when following 40 mm radius curved contour.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.135-139
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• 1992

Control of tool-environment interaction force to comply the robot system to an environment is of vital in many automated process. This paper presents the implementation of an adaptive force control with commercial robot system in two dimensional contour following task. A model reference adaptive control system, combined with the linear compensators, is implemented. That is, a use of adaptive control is to provide an auxiliary control system so that the contour following performance can be improved from that of using linear control system only. Hyperstability is used to derive the adaptive control law. Experimental verification of the proposed control system is obtained using PUMA 560 robot system. Data obtained experimentally shows that the use of additional adaptive control system improves the contour following performance about 30% in RMS contact force errors upon that of the system controlled by the linear compensators only.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.746-748
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• 1988

A way of improving the transient performance is suggested for a class of model reference adaptive control systems. To increase the convergence rate of a model following error, an error feedback term is incorporated into the control law.

• 한국정밀공학회지
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• 제17권12호
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• pp.176-184
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• 2000

TDC(Time Delay Control) deals with the time-varying system parameters, unknown dynamics and unexpected disturbances using time delay. TDC can be divided into two separate parts: an auxiliary controller and a servo controller. The two controllers can be designed independently. The auxiliary controller is used to reduce sensitivity to parameter variations, nonlinear effects, and other disturbances. The servo controller is to reduce the error between the desired command and output. We propose the model-following time delay controller with modified error feedback controller. This was applied to follow the desired reference model for the uncertain time-varying overhead crane. The model generates the damped-out swinging motion trajectory to suppress the swinging motion caused by the acceleration and the deceleration of crane transportation. The control performance was evaluated through simulations. The theoretical results indicate that this control method shows excellent performance to an overhead crane with the uncertain time-varying parameters.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.57-62
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• 2004

This paper deals with a waypoint trajectory following problem for the tilt-rotor UAV under development in Korea (TR-KUAV). In this problem, dynamic model inversion based on the linearized model and Sigma-Phi neural network with adaptive weight update are involved to realize the waypoint following algorithm for the vehicle in the helicopter flight mode (nacelle angle=0 deg). This algorithms consists of two main parts: outer-loop system as a command generator and inner-loop system as stabilizing controller. In this waypoint following problem, the position information in the inertial axis is given to the outer-loop system. From this information, Attitude Command/Attitude Hold logic in the longitudinal channel and Rate Command/Attitude Hold logic in the lateral channel are realized in the inner-loop part of the overall structure of the waypoint following algorithm. The nonlinear simulation based on the TR-KUAV is carried out to evaluate the stability and performance of the algorithm. From the numerical simulation results, the algorithm shows very good tracking performance of passing the waypoints given. Especially, it is observed that ACAH/RCAH logic in the inner-loop has the satisfactory performance due to adaptive neural network in spite of the model error coming from the linear model based inversion.

• 제어로봇시스템학회논문지
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• 제5권4호
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• pp.411-418
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• 1999

Generally PI controller is used in the servo system, But the time response of the system which is designed by the PI control scheme is deviated from the desired time response by the system parameter variation or the perturbation like the torque disturbance. LMFC(Linear Model Following Controller) is used to make the response of the system follow that of the model even though the parameter variation or the perturbation exists. In this paper, the design method which uses auxiliary model to construct the robustness enhancer in LMFC is proposed. And this robustness enhancer is designed by robust control theory. The proposed method has facter convergence time against low frequency torque disturbance than LMFC. The results are verified by SIMULINK simulation and experiments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 정기총회 및 추계학술대회 논문집 학회본부
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• pp.329-331
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• 1993

A new RMFSOC(Reference Model Following Self-Organizing Controller) is proposed. It is composed by adding the reference model and decision rule to the Mamdani's SOC. The reference model is introduced to explicitly specify the control performance. The self-organizing level of the RMFSOC organizes the control rule which makes the process output follow the reference output generated by the reference model. In order to avoid unnecessary control rule modification, a decision rule is also introduced to determine whether the control rule modification is needed or not.