• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2005년도 학술대회 논문집
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• pp.315-320
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• 2005

This paper is proposed adaptive fuzzy-neuro controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network 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 nor measured between the motor speed and output of a reference model. The control performance of the adaptive fuzy-neuro controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• 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.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1995년도 추계학술대회 학술발표 논문집
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• pp.145-152
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• 1995

This paper presents a novel SOFLIC(self organizing fuzzy logic intelligent controller) for reactor rod control system in nuclear power plant. The output of fuzzy controller is gener ated by using two signal : the error between reference and average temperature, and the error between reference and neutron flux-converted temperatures. Flexibility of the controller is enhanced by using self-organizing feature and the controller respond to variation of system parameter with more precision. performances of the SOFLIC and PID are simulated with the model developed for a nuclear power plant. The SOFLIC is superior to PID : SOFLIC provides more rapid load following capability. more robustiness for variation in process dynamics and minimization of engineer's mistakes in controller design.

• 동력기계공학회지
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• 제17권1호
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• pp.77-84
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• 2013

The proportional pressure control valve that was used to relief valve has different dynamic characteristics on each case. Because this valve has different assembling or processing error and environmental condition. However, a customer who used the relief valve wants to have a steadily performance even if the dynamic characteristics of valve was changed. For this reason, the manufacturer try to make the robust controller that has simple structure. This paper concerns about the design of robust controller that didn't affected by plant parameter's changing. The control strategy is a model reference control that conducted by on line identification problem, gradient method and Lyapunov equation. This adaptvie control law's validity that this paper deal with was confirmed by an results of step response test or hysteresis test.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.403-405
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• 1999

The model reference adaptive control(MRAC) algorithm is applied to the speed control of an inverter driven permanent magnet brushless do motor MRAC is compared to a standard PI controller. Applying this algorithm has also been proved by simulations that quick speed response without over-shoot could be obtained for the motor system with variable parameters. Simulation results show that the adaptive controller is superior to the PI controller.

• 드라이브 ㆍ 컨트롤
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• 제9권3호
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• pp.1-7
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• 2012

This paper deals with the issue of model reference adaptive control strategy to control the injection molding machine. Prior to controller design, a pair of transfer functions are derived for the injection and dwelling process based on mathematical models of components. As external disturbances to examine the robustness of the proposed controller, nozzle clogging and contraction of molded objects are considered and realized by proportional valve. The overall simulation system, consisting of hydraulic components, controller and sensors, is implemented using the components of commercial software SimulationX. The simulation results confirm the proposed scheme's efficiency and robustness.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.621-623
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• 1999

In this paper, Model following PID control system, which is combined PID controller with Model Reference Adaptive Controller, is proposed. To decrease complex and much calculation which is produced in tuning process, the tuning method of parameter with fuzzy algorithm is introduced. Fuzzy algorithm isn't used in the form of controller generally much used, but tuner. Experimental results show that proposed controller has the PID parameter be tuned by fuzzy algorithm. Therefore, We expect model following PID to be operated in the real-time control.

• 제어로봇시스템학회논문지
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• 제12권7호
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• pp.644-649
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• 2006

In this paper, a methodology for estimating the model parameters of a discrete-time system and tuning a digital PID controller based on the estimated model and a genetic algorithm is presented. To deal with optimization problems regarding parameter estimation and controller tuning, pseudo-parallel genetic algorithms(PPGAs) are used. The parameters of a discrete-time system are estimated using both the model adjustment technique and a PPGA. The digital PID controller is described by the pulse transfer function and then its three gains are tuned based on both the model reference technique and another PPGA. A set of experimental works on two processes are carried out to illustrate the performance of the proposed method.

• 한국정밀공학회지
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• 제14권5호
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• pp.92-99
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• 1997

A model reference adaptive control(MRAC) theory is very useful for controlling a plant of which the parameters are unknown or vary during operation usint only input-output signal of plant. In this study, 2' nd order discreter time MRAC controller is designed for an electrohydraulic position control system which is represented with nonlinear mathematical model and the least square method is adopted for the para-meter adjustment law. This control algorthm is applied to the position control of electrohydraulic servosystem through computer simulation and the effect of the change of load, sampling time upon the performance following reference model and upon the performance of estimating plant parameters are examined.

• 제어로봇시스템학회논문지
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• 제8권5호
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• pp.373-384
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• 2002

This paper presents a robust PID controller design technique using the concept of model matching method in the frequency domain. To design the robust PID controller satisfying disturbance attenuation and robust tracking property for a reference input, first an H$\infty$ controller satisfying given performance is designed using the H$\infty$ control method. And then, the parameters(proportional, integral, and derivative gains) of the robust PID controller are determined using the model matching at frequency domain. The proposed technique is applied to a position controller design of the web. The simulation results show that the proposed robust PID controller satisfies disturbance attenuation and tracking property.