• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.660-662
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• 1997

A new improved excitation control system for power plant synchronous generators has been developed by KEPRI (Korea Electric Power Research Institute). The reliability of the excitation system is increased by designing a dual channel automatic voltage regulator(AVR). Also the performance of the excitation system is improved by Self-Tuning adaptive Controller. A software package is developed for the excitation control system, and a field test is conducted to verify the system performance.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.370-372
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• 1986

In this paper we propose a Generalized Minimum Variance Self-tuning Control of the system with an autoregressive noise model. To establish a Generalized Minimum Variance Control, the control input is also included in a cost function and a novel identity is introduced. The effectiveness of this algorithm is demonstrated by the computer simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.3-12
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• 1996

Sliding mode controller(SMC) is a simple but powerful nonlinear controller, because it guarantees the stability and the robustness. However, it leads to the high frequency chattering of the control input. Although the phenomenon can be avoided by introducing a thin boundary layer to the sliding surface, the method results in a steady state: error proportional to the boundary layer thickness. In this paper, we proposed a new sliding mode controller with self-tuning the thickness of a boundary layer. It uses a fuzzy rule base for tuning the thickness of a boundary layer. That is, the thickness is increased to some degree to reject a discontinuous control input at the initial state and then it is decreased as the states approaches to the steady states for improving the tracking performance. In order to assure the control performance, we perf'ormed the computer simulation using an inverted pendulum system as a controlled plant.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.189-191
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• 1995

This paper proposes a design of self-tuning fuzzy controller based on evolutionary computation. Optimal membership functions are found by using evolutionary computation. Genetic algorithms and evolution strategy are used for tuning of fuzzy membership function. An arbitrarily speed trajectory is selected to show the performance of the proposed methods. Experiment results show the good performance in the DC motor control system with the self-tuning fuzzy controller based on evolutionary computation.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.174-178
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• 1987

In the design of reference model based STC (self-tuning controllers), parameters of the controllers are determined not from the true plant but from the estimated model. In this paper, we suggest a power spectrum estimation method for visualling the sensitivity of the closed loop system without knowing the explicit original plant.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.223-226
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• 1991

In this paper, the problem of designing on adaptive controller for dc drives using state observers, which is operated under varying load conditions, is addressed. A robust self-tuning controller that can track a constant reference and reject constant load disturbances is also studied. This scheme is very attractive since the estimates of system parameters are available in real time. Parameter estimation is based on the recursive least squares method and the control algorithm of the pole placement technique. Also, state observer systems are applied. State observer systems are required to estimate the states quickly and exactly without being affected by the disturbances.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1071-1084
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• 1992

In this paper, the method for navigation and obstacle avoidance of the autonomous mobile robot is proposed. The proposed algorithms are based on the fuzzy inference system which is able to deal with imprecise and uncertain information. The self-tuning algorithm, which adopts the simplex method, modifies the parameters of membership functions of the input-output linguistic variables by changing the support of these fuzzy sets according to the integral of absolute error(IAE) of the system response. The wall-follwing navigation and obstacle avoidance of the mobile robot are based on range data measured from the internal sensors(encoder) and the outer sensors(sonar sensor). In addition, the algorithm for the obstacle detection proposed in this paper is based on the expert's experience. Finally, the effectiveness of navigation and obstacle avoidance algorithm is demonstrated through simulation and experiment.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.375-378
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• 1991

This paper presents a design method of synchronous generator excitation controller using self-tuning PID algorithm. Controller parameter is determined by using adaptive control theory in order to maintain optimal operation of generator under the various operating conditions. To determine the optimal parameter of controller. minimum variance algorithm using the recursive leastsquare(RLS) indentification method is adopted and the difference between the speed deviation with weighted factor and voltage deviation is used as the input signal of adaptive controller, which provides good damping and conversion characteristics. The results tested on a single machine infinite bus system verify that the proposed controller has better dynamic performances than conventional controller.

• 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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• 1993.11a
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• pp.299-303
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• 1993

There can be two methods in control systems: one is to use a linear controller, the other is to use a nonlinear controller. The PID controller and the fuzzy controller can be said to belong the linear and the nonlinear controller respectively. In this paper, a new hybrid controller which is consist of the linear PID controller of which the gain is tuned and the nonlinear self tuning fuzzy controller is proposed. In the PID controller, an algorithm which parameterizes the proportional, the intergral, and the derivative gain as a single parameter is used to improve the performance of the PID controller. In the self tuning fuzzy controller, an algorithm which changes the shape of the triangle membership function and changes the scaling factor which is multiplied to the error and the error change. The evaluation of the performance of the suggested algorithm is carried on by the simulation for the Rhino XH-2 robot manipulator with 5 links revolute joints.