• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.740-743
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• 1997

Reference models are used in many control algorithms for improvement of transient response characteristics. They provide desired trajectories that the plant should follow. Most control systems have bounded control inputs to avoid saturation of the plant. If we design reference models that do not account for limits of control inputs, control performance of the system may be deteriorated. In this paper, therefore, the way of determining variable reference models for TDC(time delay control) technique is proposed. The variable reference model is determined based on the information of bounded control inputs and reference inputs. This proposed method is also verified by application to the position control experiment using the BLDC motor.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권9호
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• pp.569-575
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for high performance of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control Performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation. and steady- state accuracy and transient response.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권2호
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• pp.107-113
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• 2004

This paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of permanent magnet synchronous motor(PMSM) drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed adaptive fuzzy controller is confirmed by performance results for PMSM drive system.

• Journal of Power Electronics
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• 제5권2호
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• pp.129-141
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• 2005

A high-performance robust hybrid speed controller for a permanent-magnet synchronous motor (PMSM) drive with an on-line trained neural-network model-following controller (NNMFC) is proposed. The robust hybrid controller is a two-degrees-of-freedom (2DOF) integral plus proportional & rate feedback (I-PD) with neural-network model-following (NNMF) speed controller (2DOF I-PD NNMFC). The robust controller combines the merits of the 2DOF I-PD controller and the NNMF controller to regulate the speed of a PMSM drive. First, a systematic mathematical procedure is derived to calculate the parameters of the synchronous d-q axes PI current controllers and the 2DOF I-PD speed controller according to the required specifications for the PMSM drive system. Then, the resulting closed loop transfer function of the PMSM drive system including the current control loop is used as the reference model. In addition to the 200F I-PD controller, a neural-network model-following controller whose weights are trained on-line is designed to realize high dynamic performance in disturbance rejection and tracking characteristics. According to the model-following error between the outputs of the reference model and the PMSM drive system, the NNMFC generates an adaptive control signal which is added to the 2DOF I-PD speed controller output to attain robust model-following characteristics under different operating conditions regardless of parameter variations and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed 200F I-PD NNMF controller. The results confirm that the proposed 2DOF I-PO NNMF speed controller produces rapid, robust performance and accurate response to the reference model regardless of load disturbances or PMSM parameter variations.

• 한국생산제조학회지
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• 제23권2호
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• pp.157-163
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• 2014

In this paper, a robust MRAC (model reference adaptive control) scheme is applied to control an electrohydraulic positioning system under various loads. The inverse dead-zone compensator in the control system cancels out the dead-zone response, and an integrator added to the controller provides good position-tracking ability. LQG/LTR (linear quadratic Gaussian control with loop transfer recovery) closed-loop model is used as the reference model for learning the MRAC system. LQG/LTR provides a systematic technique to design the linear controller that optimizes the objective function using some compromise between the control effort and the system performance in the frequency domain. Different external load tests are performed to investigate the effectiveness of the designed MRAC system in real time. The experimental results show that the tracking performance of the proposed system is highly accurate, which offers considerable robustness even with a large change in the load.

• 전자공학회논문지T
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• 제36T권4호
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• pp.60-70
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• 1999

본 논문에서는 FLC의 적응능력에 대한 단점과 제어규칙 도출의 어려움을 극복하기 위하여 모델기준 적응 퍼지제어기(MRAFC)를 제안하였다. MRAFC는 단순퍼지제어기와 플랜트로 구성된 내부 피드백 루프와 단순 퍼지제어기의 제어규칙을 동조시키는 외부 루프로 구성된다. 기준모델은 기준입력에 대해 전체 제어시스템에 요구되는 제어성능을 특성화하고 수량화하는 퍼지제어기 설계기준으로 사용되었다. 그리고 적응 매카니즘은 FLC 제어규칙을 동조하는 역할을 수행한다. 제안한 알고리즘의 성능은 DC 서보 전동기에 대한 실험에 의해 검증되었다.

• 한국기계기술학회지
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• 제20권6호
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• pp.809-817
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• 2018

The model predictive controller performance of the mobile robot is set to an arbitrary value because it is difficult to select an accurate value with respect to the controller parameter. The general model predictive control uses a quadratic cost function to minimize the difference between the reference tracking error and the predicted trajectory error of the actual robot. In this study, we construct a predictive controller by transforming it into a quadratic programming problem considering velocity and acceleration constraints. The control parameters of the predictive controller, which determines the control performance of the mobile robot, are used a simple weighting matrix Q, R without the reference model matrix $A_r$ by applying a quadratic cost function from which the reference tracking error vector is removed. Therefore, we designed the predictive controller 1 and 2 of the mobile robot considering the constraints, and optimized the controller parameters of the predictive controller using a genetic algorithm with excellent optimization capability.

• 한국정밀공학회지
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• 제16권5호통권98호
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• pp.58-65
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• 1999

A magnetic levitation system requires a robustness to overcome a dynamic instability due to disturbances. In this paper a robust controller for a magnetically levitated fine manipulator is presented. The proposed controller consists of following two parts: a model reference controller and an $H_{\infty}$ controller. First, the model reference control stabilizes the motion of the manipulator. Then, the motion of the manipulator follows that of the reference model. Second, the $H_{\infty}$ control minimizes errors generated from the model reference control due to noise and disturbance since the $H_{\infty}$ control is a kind of robust control. The experiments of position control and tracking control are carried out by use of the proposed controller under the conditions of free disturbances and forced disturbances. Also, the experiments using PID controller are carried out under the same conditions. The results from above two controllers are compared to investigate the control performances. As the results, it is observed that the proposed controller has similar position accuracy but better tracking performances comparing to the PID controller as well as good disturbance rejection effect due to the robust characteristics of the controller. In conclusion. it is verified that the proposed controller has the simple control structure, the good tracking performances and good disturbance rejection effect due to the robust characteristics of the controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 F
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• pp.1872-1875
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• 1998

In the industrial motor drive system, a shaft torsional vibration is often generated when a motor and a load are connected with a flexible shaft. This paper treats the vibration suppression control of such a system. Recently, there are new methods which estimate unknown state variables by using a reduced order observer and feedback these state variables by using a pole placement design method. But there is a trade-off between the fast command following property and the attenuation of disturbances and vibrations in these design methods. In this paper, the vibration suppression control of a two-mass system using a reference model is proposed. Because of using a reference model, the proposed control satisfy the fast command following property and the attenuation of disturbances and vibrations. Control parameter can be changed to maintain high system performance in control using a reference model. Experimental results show the validity of the proposed state feedback control using a reference model, and this controller is compared with the state feedback controller.

• 대한기계학회논문집A
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• 제28권8호
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• pp.1152-1158
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• 2004

In this study a MRAC(model reference adaptive control) for fluid power elevator model system was designed. The MRAC was compared with PI control in case of applying to the elevator model system with constant external load and changing external load. In this case external load was produced by a single fluid power cylinder combined with pressure control valve. In conclusion the MRAC control performance was better than PI control performance because overshoot and steady state error of the elevator model system controlled by the MRAC were not appeared for constant and changing external load.