• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.351-354
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• 2001

In this paper, we present self-tuning control of switched reluctance motor for maximum torque with phase current and shaft position sensor. Determination method of turn-on/off angle is realized by using self-tuning control method. During the sampling time, micro-controller checks the number of pulse from encoder and compare with the number of pre-checked pulse. After micro-controller calculates between two data, it moves forward or backward turn-off angle. When the turn-off angle is fixed optimal turn-off angle, the turn-on angle automatically moves forward or backward by a step using self-tuning control method. And then, optimal turn-off angle is searched once again. As such a repeating process, turn-on/off angle is moved automatically to obtain the maximum torque. The experimental results are presented to validate the self-tuning algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.754-758
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS320C50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator, In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters we determined by the pole-placement method. Performance of self-tuning adaptive controller is illusrated by the simulation and experiment for a SCARA robot.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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• pp.168-175
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• 1995

A robust speed control algorithm under disturbances and reference change is developed using the self tuning control method in order to control induction motors. The method incorporates the concepts of the well known internal model principle and the annihilator polynomial. The effectiveness of the method is evaluated through the speed control experimental results of an induction motor for refernce change and arbitrary distrbance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1560-1564
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• 2008

Robust control for DC motor is needed according to the highest precision of industrial automation. However, when a motor control system with PID controller has an effect of load disturbance, it is very difficult to guarantee the robustness of control system. In this paper, PID-Self Tuning control method for motor control system as a compensation method solving this problem is presented. If the PID control system is stable in the sense that the error is inside the constraint set, the supervisory control is idle. If the error hits the boundary of the constraint, the supervisory controller begins operation to force the error back to the constraint set. We prove that the PID-Self Tuning control system is globally stable in the sense that the error is guaranteed to be within the tolerance limits specified by the system designer.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.214-217
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• 1987

In this paper self tuning control of interconnected systems are dealt in view point of large scale system control. The plant model is given in multiple ARMA process. This process is simplified as independent SISO ARMA process having offset terms. This offset was considered as effects of interconnections. In each decentralized system, self tuning controller with instrumental variable method is adopted. As a result, this algorithm enables the parameter estimation to be unbiased and non-drift. This controller contains a new implicit offset rejection technique. Simulation results considers well with the analysis in case of linear interconnection.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.77.6-77
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• 2001

R/C helicopter has been used to several fields of military affairs, investigation, searching and toys because it has small size, hovering and vertical take-off characteristics etc. Therefore it needs more realizable control method. The paper introduces simulation and experimental results for control of a helicopter training simulator by self tuning control method. It is assumed that the helicopter is operated at the state of hovering motion and the model is induced. The self tuning control method incorporates the concepts of the well known internal model principle and annihilator polynomial for reference input and disturbance. The controller design is separated into two cases that the plant parameters are known or not. To realize ...

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.7
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• pp.66-77
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• 1997

This paper presents an automatic tuning method for parameters of a multivaiable self-tuning velocity-type PID controller which adapts to changes in the system parameters with time delays and noises. The velocity-type PID control structure is determined in the process of minimizing the variance of the auxiliarly output, and self-tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optiminzing the design parameters of the controller. The proposed PID type multivariable self-tuning method is simple andeffective compared with other esisting multivariable self-tuning methods. Computer simulation has shown that the proposed algorithm is beter than the trial-and-error method in the tracking performance.

• Computers and Concrete
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• v.30 no.5
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• pp.357-367
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• 2022

In this paper, we propose an efficient control method that can be transformed into a general building control problem for building structure control using these reliability criteria. To facilitate the calculation of controller H∞, an efficient solution method based on Linear Matrix Inequality (LMI) is introduced, namely H∞-based LMI control. In addition, a self-tuning predictive grey fuzzy controller is proposed to solve the problem caused by wrong parameter selection to eliminates the effect of dynamic coupling between degrees of freedom (DOF) in Self-Tuning Fuzzy Controllers. We prove stability using Lyapunov's stability theorem. To check the applicability of the proposed method, the proposed controller is applied and the control characteristics are determined. The simulation assumes system uncertainty in the controller design and emphasizes the use of acceleration feedback as a practical consideration. Simulation results show that the performance of the proposed controller is impressive, stable, and consistent with the performance of LMI-based methods. Therefore, an effective control method is suitable for seismic reinforcement of civil buildings.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.179-181
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• 1987

In this paper, a self-tuning controller design is proposed by using pole-zero placement method and considering a system time delay. To got better tracking for the generalized self-tuning controller, pole placement method for the closed loop system and zero placement method for the error transfer function are Introduced. The proposed method shows better efficiency than pole placement method for minimizing tracking error. Simulation gives good results in tie reference signal tracking.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.629-632
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• 1997

This paper presents the design method of controller which is combined Genetic Algorithms with the Generalized minimum variance self tuning controller. It is shown that the controllers adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a polynomial parameters. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.