• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.832-835
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• 2002

This paper presents a new approach integrated Case-Based Reasoning with Self. Organization Map(SOM) in diagnosis systems. The causes of faults are obtained by case-base trained from SOM. When the vibration problem of rotating machinery occurs, this provides an exact diagnosis method that shows the fault cause of vibration problem. In order to verify the performance of algorithm, we applied it to diagnose the fault cause of the electric motor.

• Journal of the Korean Society of Industry Convergence
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• v.3 no.1
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• pp.3-8
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• 2000

This paper describes a development of self tuning scheme for PI and PO type fuzzy controllers. The output scaling factor(SF) is adjusted on-line by fuzzy rules according to the current trend of the controlled process. The rule-base for tuning the output SF is defined on error and change of error for the controlled variable using the most natural and unbiased membership functions. Simulation results demonstrate the better control performance can be achieved in comparison with Ziegler-Nichols(Z-N) PID controllers.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.6
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• pp.49-56
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• 1995

In this study, self-tuning adaptive control using state observer is developed. Self-tuning adaptive controller that estimates the parameters of the system in real time and generates the optimal control signals has robust characteristic about varying load and external disturbances. In addition, state observer without sensors is applied, thus the control can be performed more quickly and exactly. Since chopper is used commonly in practical drives, the characteristics of the chopper are included in state observer algorithm, which, in turn, makes the system exact estimation. Since series type DC motor has nonlinear models, linearizing approach are investigated. to realize the proposed algorithm it requires fast calculation in real time. TMS320C31, digital signal processor, is applied to realized the adaptive control algorithms.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.364-370
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• 1990

In this paper, we propose a self-tuning PID controller for unknown systems with time-varying delay. Using pole placement equations, we derive the controller that can be extended to the multi-step time delay case. The time-varying delays are estimated by a prediction error delay method using multiple predictors. Since the order of the estimation vector is not increased, the persistant exciting condition of control input is alleviated. Since the least square method gives biased parameter estimates for colored noise cases, the recursive instrumental variable method is used to estimate system parameters. The computational burden of the proposed method is less than the conventional adaptive methods. Computer simulations are performed to illustrate the efficiency of the proposed method.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1182-1184
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• 2001

This paper presents a neural network based self-tuning fuzzy PID control scheme for induction motor speed control. The PID controller is being widely used in industrial applications. When continuously used long time, the electric and mechanical parameters of induction motor change, degrading the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, and proposes a neural network based self-tuning fuzzy PID controller whose scaling factors are adjusted automatically. Proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink is performed to verify the effectiveness of the proposed scheme.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.488-490
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• 1999

This paper describes the design of self-tuning speed controller for DC motor drive system using RLS(Recursive Least Squares) algorithm and Pole-Placement method. The model parameters, related to inertia and damping coefficient of motor, are estimated on-line by using RLS estimation algorithm. And a control signal is calculated by using pole placement method. Simulation and experimental results show that the proposed controller possesses excellent adaptation capability than a conventional PI/IP controller under parameter change.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1056-1059
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• 1996

In this paper, we analyzed the effect of the change of the rotor time constant on the performance of the indirect vector control system. By employing indirect field orientation technique, we have also suggested an optimal control algorithm that allows an induction motor to maintain the maximum torque under the changing environment of rotor time constant. A computer simulation on the transient response of the output torque was demonstrated. To verify the validity of the method that has been proposed in this paper, an experiment has been performed utilizing TMS32OC31(40MHz) DSP chip which is capable of performing floating-point arithmetic in real time.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.125-128
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• 1989

This paper presents a DC servo motor controller using self-tuning PID algorithm, which can support Multi-processor for the real time processing. Computer simulation as well as experiment using Multi-processor(8088) are implemented with self-tuning PID algorithm. Presented algorithm is used to compare the performance of the controller with that of the classical PID controller through computer simulation and experiment. The result which use the Self-Tuning algorithm show that motor output follows the reference input trajectory fairly well inspite of load disturbances and parameter variations.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.327-331
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• 1989

This paper concerned about a study on the direct pole placement PID self-tuning controller design for Robot manipulator control system. The method of a direct pole placement self-tuning PID control for a DC motor of robot manipulator tracks a reference velocity in spite of the parameters uncertainties in nonminimum phase system. In this scheme, the parameters of controller are estimated by the recursive least square(RLS) identification algorithm, the pole placement method and diophantine equation. A series of simulation in which minimum phase system and nonminimum phase system are subjected to a pattern of system parameter changes is presented to show some of the features of the proposed control algorithm. The proposed control algorithm which shown are effective for the practical application, and experiments of DC motor speed control for Robot manipulator by a microcomputer IRH-PC/AT are performed and the results are well suited.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.333-336
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• 1992

In this paper, We propose a PID-type of self-tuning algorithm which is based on the parameter estimation and the minimization of the cost function. We use the CARIMA model for parameter estimation and determine the discrete PID controller parameters by minimizing the cost function which considers the quadratic deviations of the predicted output over the set-point as well as the control efforts. Also, The algorithm is extended by incorporating constraints of the control signal. Simulations are performed to illustrate the efficiency of the proposed method.